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BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM
DIVISION OF BANKING SUPERVISION AND REGULATION
Date:
To:
From:
Subject:
July 3, 2003
Board of Governors of the Federal Reserve System
Federal Reserve Staff1
Implementation of the New Basel Capital Accord in the United States
ACTION REQUESTED: Board approval to issue for public comment three interagency
documents relating to the implementation of the new Basel Capital Accord (the New Accord) in
the United States: 1) an Advance Notice of Proposed Rulemaking (ANPR); 2) “Supervisory
Guidance on Internal Ratings-Based Systems for Corporate Credit”; and 3) “Supervisory
Guidance on Operational Risk Advanced Measurement Approaches for Regulatory Capital.”
Staff also requests Board approval to continue to make non-substantive edits to the documents to
accommodate further interagency discussions.
The latter two documents containing draft supervisory guidance are intended to serve as
complementary material to the ANPR. They set forth supervisory expectations for banking
organizations implementing the Advanced Internal Ratings-Based (A-IRB) approach for credit
risk and the Advanced Measurement Approaches (AMA) for operational risk (together, the
advanced approaches). If the Board and the other banking agencies approve this package, the
documents will be submitted to the Federal Register for publication. Current drafts of each of
the documents are attached.2
‘Rich Spillenkothen, Roger Cole, Steve Hoffman, Barbara Bouchard, Division of Banking Supervision and
Regulation; Ed Ettin and David Jones, Division of Research and Statistics; Mark Van Der Weide, Legal Division;
Danyll Hendricks, Federal Reserve Bank of New York.
2 Staff notes that the other banking agencies will not be finished with their internal review procedures of the ANPR
until next week. In the event that substantive issues come to light, staffwill circulate to the Board any revised
sections of the ANPR as soon as possible.
BACKGROUND: Over the past several years, the Basel Committee on Banking Supervision
(BSC) has been developing a new international agreement to enhance the Basel Accord agreed to
in 1988. The Basel Accord sets forth the framework for capital adequacy standards for large,
internationally active banks and serves as a basis for the risk-based capital adequacy standards
now in place for all U.S. banks and bank holding companies.
As part of the New Accord development process, the BSC released a third Consultative
Paper (CP 3) in April 2003, with public comments due by July 31, 2003. The New Accord is
intended to strengthen the regulatory capital framework for large internationally active banking
organizations through minimum capital requirements that are more sensitive to an institution’s
risk profile and that reinforce incentives for strong risk management. The framework is based
upon modern risk measurement and management methodologies, robust supervisory review and
capital adequacy assessment, and enhanced disclosure requirements.
The U.S. Federal banking agencies are coordinating closely their efforts to implement the
New Accord. Together, they have identified a number of steps they must take and prerequisites
that supervised organizations must meet before the fundamental changes implicit in the New
Accord can adopted for depository institutions in the United States. A first step is issuing the
attached ANPR and supervisory guidance for public comment, followed by a full analysis of all
public comments received on these documents, as well as on CP 3. Based on the comments, the
agencies would develop a unified U.S. position on further appropriate modifications to the New
Accord.
The New Accord agreed by the BSC would serve as the basis for the next step in our
domestic process, namely developing for public comment a Notice of Proposed Rulemaking
(NPR) in 2004. As with prior Basel capital agreements, we have made clear to the BSC that
adoption of a final capital rule in the United States would be contingent on the results of the
2
comments received on the NPR, as well as other quantitative analyses of the potential impact of
the proposed framework. Further, based on subsequent impact reviews and other information
developed in future years, the agencies will continue to reserve the right to revise the final U.S.
capital rule.
The ANPR presents an overview of the New Accord as well as details of the proposed
U.S. implementation of the advanced approaches to determining minimum capital requirements.
Specifically, the ANPR:
•
Outlines the scope of application for the advanced approaches; i.e., large,
internationally active banking organizations that meet certain size or foreign
exposure thresholds (core banks) would be required to meet rigorous
infrastructure requirements and to implement the advanced approaches. Other
institutions could choose to apply voluntarily the advanced approaches (opt-in
banks), after meeting the same infrastructure requirements that core banks must
satisfy. Institutions not applying the advanced approaches (general banks) would
continue to apply the agencies’ existing risk-based capital rules.
•
Describes, in detail, the A-IRB approach to credit risk and its application to
particular portfolios of credit exposures (wholesale, retail, and equity), including
minimum qualifying criteria that an institution would have to meet.
•
Describes the A-IRB approach to credit risk mitigation.
•
Describes the A-IRB approach for securitization exposures.
•
Provides guidance and qualifying criteria for the AMA to operational risk.
•
Outlines the proposed approaches for supervisory review and disclosure (pillars 2
and 3 in the New Accord).
•
Raises certain competitive considerations.
3
To assist the agencies in eliciting useful comments on particular issues, the ANPR
contains a series of specific questions in appropriate sections of the document.
High standards and clear guidance for implementing and validating systems are critical to
the success of both the A-IRB framework and the AMA. These are necessary because the
advanced approaches would rely on an banking organization’s own internal risk measurement
capabilities for estimates of important risk factors that would be used in the calculation of its
regulatory capital requirement.
The second document – “Supervisory Guidance on Internal Ratings-Based Systems for
Corporate Credit” – is intended to set forth the agencies’ expectations for banking organizations
that use the A-IRB framework for their corporate credit. The guidance sets forth A-IRB
supervisory standards, many of which are principle-based so as to allow institutions to
implement the framework in a flexible manner. Other standards are more specific in order to
address prudential concerns or consistency issues. It should be noted that the draft supervisory
guidance is not intended to dictate the precise manner in which institutions must meet
supervisory expectations or to provide a technical roadmap for developing such a framework.
Rather, it describes supervisory expectations regarding the four principal, interdependent
components of an acceptable A-IRB system, which are:
•
a system that assigns ratings and validates the accuracy of those ratings;
•
a quantification process that translates risk ratings into A-IRB parameters;
•
a data maintenance system that supports the A-IRB system; and
•
oversight and control mechanisms that ensure the system is functioning as
intended and generating accurate ratings.
While supervisors would evaluate banking organizations’ compliance with the A-IRB
supervisory standards for each of these four components, the simple evaluation of compliance
4
with each of the standards individually would not be sufficient to determine an institution’s
overall compliance. A supervisory evaluation also would have to be made of the adequacy and
effectiveness of the interaction of each of the components with one another to achieve the overall
objective of the accurate measurement of risk.
The final document is entitled “Supervisory Guidance on Operational Risk Advanced
Measurement Approaches for Regulatory Capital.” This guidance sets forth supervisory
expectations for banking organizations that would use the AMA for calculating operational risk
exposure under the proposed capital framework. The AMA requires each banking organization
to use its own internal measurement systems to calculate its exposure to operational risk, taking
into account operational risk mitigants such as insurance and the quality of controls.
Accordingly, the supervisory guidance is designed to provide assurance that banking
organizations have developed credible infrastructures for the governance, measurement,
monitoring, and control of operational risk.
Staff is recommending that the Board approve issuance of this package for public
comment. If approved by the U.S. banking agencies, the ANPR and the two supervisory
guidance documents will be submitted to the Federal Register for simultaneous publication, and
a 90-day comment period will be provided.
Attachments
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ATTACHMENT 1
DEPARTMENT OF THE TREASURY
Office of the Comptroller of the Currency
12 CFR Part 3
[Docket No. 03-XX]
RIN Number 1557-AB14
FEDERAL RESERVE SYSTEM
12 CFR Parts 208 and 225
[Regulations H and Y; Docket No.
]
FEDERAL DEPOSIT INSURANCE CORPORATION
12 CFR Part 325
RIN
DEPARTMENT OF THE TREASURY
Office of Thrift Supervision
12 CFR Part 567
[Docket No. ]
RIN
Risk-Based Capital Guidelines; Implementation of New Basel Capital Accord
AGENCIES: Office of the Comptroller of the Currency, Treasury; Board of Governors of the
Federal Reserve System; Federal Deposit Insurance Corporation; and Office of Thrift
Supervision, Treasury.
ACTION: Advance notice of proposed rulemaking.
SUMMARY: The Office of the Comptroller of the Currency (OCC), the Board of Governors of
the Federal Reserve System (Board), the Federal Deposit Insurance Corporation (FDIC), and the
Office of Thrift Supervision (OTS) (collectively, the Agencies) are setting forth for industry
comment their current views on a proposed framework for implementing the New Basel Capital
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Accord in the United States. In particular, this advance notice of proposed rulemaking (ANPR)
describes significant elements of the Advanced Internal Ratings-Based approach for credit risk
and the Advanced Measurement Approaches for operational risk (together, the advanced
approaches). The ANPR specifies criteria that would be used to determine banking
organizations that would be required to use the advanced approaches, subject to meeting certain
qualifying criteria, supervisory standards, and disclosure requirements. Other banking
organizations that meet the criteria, standards, and requirements also would be eligible to use the
advanced approaches. Under the advanced approaches, banking organizations would use
internal estimates of certain risk components as key inputs in the determination of their
regulatory capital requirements.
DATES: Comments must be received no later than [INSERT DATE 90 DAYS AFTER DATE
OF PUBLICATION IN THE FEDERAL REGISTER].
ADDRESSES: Comments should be directed to:
OCC: Written comments may be submitted electronically to regs.comments@occ.treas.gof or
by mail to Docket No. 03- , Communications Division, Third Floor, Office of the Comptroller of
the Currency, 250 E Street, SW, Washington D.C., 20219. Comments will be available for
inspection and photocopying at that address.
Board: Comments should refer to Docket No. R-
and may be mailed to Ms. Jennifer J.
Johnson, Secretary, Board of Governors of the Federal Reserve System, 20th Street and
Constitution Avenue, NW, Washington, D.C., 20551. However, because paper mail in the
Washington area and at the Board of Governors is subject to delay, please consider submitted
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your comments by e:mail to regs.comments@federalreserve.gov., or faxing them to the Office of the
Secretary at 202-452-3819 or 202/452-3102. Members of the public may inspect comments in
Room MP-500 of the Martin Building between 9:00 a.m. and 5:00 p.m. weekdays pursuant to §
261.12, except as provided by § 261.14 of the Board's Rules Regarding Availability of
Information, 12 CFR 261.12 and 261.14.
FDIC: Written comments should be addressed to Robert E. Feldman, Executive
Secretary, Attention: Comments, Federal Deposit Insurance Corporation, 550 17th Street, NW,
Washington, D.C., 20429. Commenters are encouraged to submit comments by facsimile
transmission to (202) 898-3838 or by electronic mail to Comments@FDIC.gov. Comments also
may be hand-delivered to the guard station at the rear of the 550 17th Street Building (located on
F Street) on business days between 8:30 a.m. and 5 p.m. Comments may be inspected and
photocopied at the FDIC’s Public Information Center, Room 100, 801 17th Street, NW,
Washington, D.C. between 9 a.m. and 4:30 p.m. on business days.
OTS: Send comments to Regulation Comments, Chief Counsel’s Office, Office of Thrift
Supervision, 1700 G Street, NW, Washington, D.C. 20552, Attention 2003- . Delivery: Hand
deliver comments to the Guard’s desk, east Lobby entrance, 1700 G Street, NW, from 9:00 a.m.
to 4:00 p.m. on business days, Attention: Regulation Comments, Chief Counsel’s Office,
Attention: No 2003- . Facsimiles: Send facsimile transmissions to FAX Number (202) 9066518, Attention No: 2003- . E:Mail: Send e-mails to regs.comments@ots.treas.gov, Attention: No.
2003- and include your name and telephone number. Due to temporary disruptions in mail
service in the Washington, D.C. area, commenters are encouraged to send comments by fax or email, if possible.
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FOR FURTHER INFORMATION CONTACT:
OCC: Roger Tufts, Senior Economic Advisor (202-874-4925 or roger.tufts@occ.treas.gov),
Tanya Smith, Senior International Advisor (202-874-4735 or tanya.smith@occ.treas.gov), or Ron
Shimabukuro, Counsel (202/874-5090 or ron.shimabukuro@occ.treas.gov).
Board: Barbara Bouchard, Assistant Director (202/452-3072 or barbara.bouchard@frb.gov),
David Adkins, Supervisory Financial Analyst (202/452-5259 or david.adkins@frb.gov), Division of
Banking Supervision and Regulation, or Mark Van Der Weide, Counsel (202/452-2263 or
mark.vanderweide@frb.gov), Legal Division. For users of Telecommunications Device for the Deaf
(“TDD”) only, contact 202/263-4869.
FDIC: Keith Ligon, Chief (202/898-3618 or kligon@fdic.gov), Jason Cave, Chief
(202/898-3548 or jcave@fdic.gov), Division of Supervision and Consumer Protection, or Michael
Phillips, Counsel (202/898-3581 or mphillips@fdic.gov).
OTS: Michael D. Solomon, Senior Program Manager for Capital Policy (202/906-5654);
David W. Riley, Project Manager (202/906-6669), Supervision Policy; or Teresa A. Scott,
Counsel (Banking and Finance) (202/906-6478), Regulations and Legislation Division, Office of
the Chief Counsel, Office of Thrift Supervision, 1700 G Street, NW, Washington, D.C. 20552.
SUPPLEMENTARY INFORMATION:
I.
II.
Executive Summary
A. Introduction
B. Overview of the New Accord
C. Overview of U.S. Implementation
The A-IRB Approach for Credit Risk
The AMA for Operational Risk
Other Considerations
D. Competitive Considerations
Application of the Advanced Approaches in the United States
A. Threshold Criteria for Mandatory Advanced Approach Organizations
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III.
IV.
V.
VI.
VII.
Application of Advanced Approaches at Individual Bank/Thrift Levels
U.S. Banking Subsidiaries of Foreign Banking Organizations
B. Implementation for Advanced Approach Organizations
C. Other Considerations
General Banks
Majority-Owned or Controlled Subsidiaries
Transitional Arrangements
Advanced Internal Ratings-Based Approach (A-IRB)
A. Conceptual Overview
Expected Losses versus Unexpected Losses
B. A-IRB Capital Calculations
Wholesale Exposures: Definitions and Inputs
Wholesale Exposures: Formulas
Wholesale Exposures: Other Considerations
Retail Exposures: Definitions and Inputs
Retail Exposures: Formulas
A-IRB: Other Considerations
Purchased Receivables
Credit Risk Mitigation Techniques
Equity Exposures
C. Supervisory Assessment of A-IRB Framework
Overview of Supervisory Framework
U.S. Supervisory Review
Securitization
A. General Framework
Operational Criteria
Differences Between the General A-IRB Framework and the A-IRB Approach for
Securitization Exposures
B. Determining Capital Requirements
General Considerations
Capital Calculation Approaches
Other Considerations
AMA Framework for Operational Risk
A. AMA Capital Calculation
Overview of the Supervisory Criteria
B. Elements of an AMA Framework
Disclosure
A. Overview
B. Disclosure Requirements
Regulatory Analysis
A. Executive order 12866
B. Regulatory Flexibility Act
C. Unfunded Mandates Reform Act of 1995
D. Paperwork Reduction Act
List of Acronyms
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I. Executive Summary
A. Introduction
In the United States, banks, thrifts, and bank holding companies (banking organizations
or institutions) are subject to minimum regulatory capital requirements. Specifically, U.S.
banking organizations must maintain a minimum leverage ratio and two minimum risk-based
ratios.1 The current U.S. risk-based capital requirements are based on an internationally agreed
framework for capital measurement that was developed by the Basel Committee on Banking
Supervision (Basel Supervisors Committee or BSC) and endorsed by the G-10 Governors in
1988.2 The international framework (1988 Accord) accomplished several important objectives.
It strengthened capital levels at large, internationally active banks and fostered international
consistency and coordination. The 1988 Accord also reduced disincentives for banks to hold
liquid, low-risk assets. Moreover, by requiring banks to hold capital against off-balance-sheet
exposures, the 1988 Accord represented a significant step forward for regulatory capital
measurement.
While the 1988 Accord has been a stabilizing force for the international banking system,
the world financial system has become increasingly more complex over the past fifteen years.
The BSC has been working for several years to develop a new regulatory capital framework that
recognizes new developments in financial products, incorporates advances in risk measurement
1
The leverage ratio measures regulatory capital as a percentage of total on-balance-sheet assets as reported in
accordance with generally accepted accounting principles (GAAP) (with certain adjustments). The risk-based
ratios measure regulatory capital as a percentage of both on- and off-balance-sheet credit exposures with some
gross differentiation based on perceived credit risk. The Agencies’ capital rules may be found at 12 CFR Part 3
(OCC), 12 CFR Parts 208 and 225 (Board), 12 CFR Part 325 (FDIC), and 12 CFR Part 567 (OTS).
2
The BSC was established in 1974 by the central-bank governors of the Group of Ten (G-10) countries. Countries
are represented on the BSC by their central bank and also by authorities with banking supervisory
responsibilities. Current member countries are Belgium, Canada, France, Germany, Italy, Japan, Luxembourg,
the Netherlands, Spain, Sweden, Switzerland, the United Kingdom, and the United States. The 1988 Accord is
described in a document entitled “International Convergence of Capital Measurement and Capital Standards.”
This document and other documents issued by the BSC are available through the Bank for International
Settlements website at www.bis.org.
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and management practices, and more precisely assesses capital charges in relation to risk. On
April 29, 2003, the BSC released for public consultation a document entitled “The New Basel
Capital Accord” (New Accord) that sets forth proposed revisions to the 1988 Accord. The BSC
will accept industry comment on the New Accord through July 31, 2003 and expects to issue a
final revised Accord by the end of 2003. The BSC expects that the New Accord would have an
effective date for implementation of December 31, 2006.
Accordingly, the Agencies are soliciting comment on all aspects of this ANPR, which is
based on certain proposals in the New Accord. Comments will assist the Agencies in reaching a
determination on a number of issues related to how the New Accord would be proposed to be
implemented in the United States. In addition, in light of the public comments submitted on the
ANPR, the Agencies will seek appropriate modifications to the New Accord.
B. Overview of the New Accord
The New Accord encompasses three pillars: minimum regulatory capital requirements;
supervisory review; and market discipline. Under the first pillar, a banking organization must
calculate capital requirements for exposure to both credit risk and operational risk (and market
risk for institutions with significant trading activity). The New Accord does not change the
definition of what qualifies as regulatory capital, the minimum risk-based capital ratio, or the
methodology for determining capital charges for market risk. The New Accord provides several
methodologies for determining capital requirements for both credit and operational risk. For
credit risk there are two general approaches: the standardized approach (essentially a package of
modifications to the 1988 Accord) and the internal ratings-based (IRB) approach (which uses an
institution’s internal estimates of key risk drivers to derive capital requirements). Within the
IRB approach there is a foundation methodology, in which certain risk component inputs are
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provided by supervisors and others are supplied by the institutions, and an advanced
methodology (A-IRB), where institutions themselves provide more risk inputs.
The New Accord provides three methodologies for determining capital requirements for
operational risk: the basic indicator approach, the standardized approach, and the advanced
measurement approaches (AMA). Under the first two methodologies, capital requirements for
operational risk are fixed percentages of specified risk measures (for example, gross income).
The AMA provides the flexibility for an institution to develop its own individualized approach
for measuring operational risk, subject to supervisory oversight.
The second pillar of the New Accord, supervisory review, highlights the need for banking
organizations to assess their capital adequacy positions relative to risk (rather than solely to the
minimum capital requirement), and the need for supervisors to review and take appropriate
actions in response to those assessments. The third pillar of the New Accord imposes public
disclosure requirements on institutions that are intended to allow market participants to assess
key information about an institution’s risk profile and its associated level of capital.
The Agencies do not expect the implementation of the New Accord to result in a
significant decrease in aggregate capital requirements for the U.S. banking system. Individual
banking organizations may, however, face increases or decreases in their minimum risk-based
capital requirements because the New Accord is more risk sensitive than the 1988 Accord and
the general risk-based capital rules. The Agencies will continue to analyze the potential impact
of the New Accord on both systemic and individual capital levels.
C. Overview of U.S. Implementation
The Agencies believe that the advanced risk and capital measurement methodologies of
the New Accord are the most appropriate approaches for large, internationally active banking
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organizations. As a result, large, internationally active banking organizations in the United
States would be required to use the A-IRB approach to credit risk and the AMA to operational
risk. The Agencies are proposing to identify three types of banking organizations: institutions
subject to the advanced approaches on a mandatory basis (core banks); institutions not subject to
the advanced approaches on a mandatory basis, but that choose voluntarily to apply those
approaches (opt-in banks); and institutions that are not mandatorily subject to and do not apply
the advanced approaches (general banks). Core banks would be those with total banking assets
of $250 billion or more or total on-balance-sheet foreign exposure of $10 billion or more. Both
core banks and opt-in banks (advanced approach banks) would be required to meet certain
infrastructure requirements (including complying with specified supervisory standards for credit
risk and operational risk) and make specified public disclosures before being able to use the
advanced approaches for risk-based regulatory capital calculation purposes.3
General banks would continue to apply the Agencies’ existing risk-based capital rules
(general risk-based capital rules). Because the general risk-based capital rules include a buffer
for risks not easily quantified (for example, operational risk and concentration risk), general
banks would not be subject to an additional direct capital charge for operational risk.
Under this proposal, some U.S. banking organizations would use the advanced
approaches while others would apply the general risk-based capital rules. As a result, the United
States would have a bifurcated regulatory capital framework. That is, U.S. capital rules would
provide two distinct methodologies for institutions to calculate risk-weighted assets (the
denominator of the risk-based capital ratios). Under the proposed framework, all U.S.
institutions would continue to calculate regulatory capital, the numerator of the risk-based capital
3
The Agencies continue to reserve the right to require higher minimum capital levels for individual institutions, on a
case-by-case basis, if necessary to address particular circumstances.
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ratios, as they do now. Importantly, U.S. banking organizations would continue to be subject to
a leverage ratio requirement under existing regulations, and Prompt Corrective Action (PCA)
legislation and implementing regulations would remain in effect.4 It is recognized that in some
cases, under the proposed framework, the leverage ratio would serve as the most binding
regulatory constraint.
Implementing the capital framework described in this ANPR would raise a number of
significant practical and conceptual issues about the role of economic capital calculations relative
to regulatory capital requirements. The capital formulas described in this proposal, as well as the
economic capital models used by banking organizations, assume the ability to precisely assign
probabilities to future credit and operational losses that might occur. The term ”economic
capital” is often used to refer to the amount of capital that should be allocated to an activity
according to the results of such an exercise. For example, a banking organization might compute
the amount of income, reserves, and capital that it would need to cover the 99.9th percentile of
possible credit losses associated with a given type of lending. The desired degree of certainty of
covering losses is related to several factors including, for example, the banking organization’s
target credit rating. The higher the loss percentile the institution wishes to provide protection
against, the less likely the capital held would be insufficient, and the higher the credit rating.
While the Agencies intend to move to a framework where regulatory capital is more
closely aligned to the economic capital substance of risk, the Agencies do not intend to place
sole reliance on the results of economic capital calculations for purposes of computing minimum
regulatory capital requirements. Banking organizations face other risks than credit and
operational risks, and the assumed loss distributions underlying banking organization’s economic
4
Thus, for example, to be in the well-capitalized PCA category a bank must have at least a 10 percent total riskbased capital ratio, a 6 percent Tier 1 risk-based capital ratio, and a 5 percent leverage ratio. The other PCA
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capital calculations are subject to the risk of error. Consequently, the Agencies continue to view
the leverage ratio tripwires contained in existing PCA regulations as important components of
the regulatory capital framework.
The A-IRB Approach for Credit Risk
Under the A-IRB approach for credit risk, an institution’s internal assessment of key risk
drivers for a particular exposure (or pool of exposures) would serve as the primary inputs in the
calculation of the institution’s minimum risk-based capital requirements. Formulas, or risk
weight functions, specified by supervisors would use the banking organization’s estimated inputs
to derive a specific dollar amount capital requirement for each exposure (or pool of exposures).
This dollar capital requirement would be converted into a risk-weighted assets equivalent by
multiplying the dollar amount of the capital requirement by 12.5 – the reciprocal of the 8 percent
minimum capital requirement. Generally, banking organizations using the A-IRB approach
would assign assets and off-balance-sheet exposures into one of three portfolios: wholesale
(corporate, interbank, and sovereign), retail (residential mortgages, qualifying revolving, and
other), and equities. There also would be specific treatments for securitization exposures and
purchased receivables. Certain assets that do not constitute a direct credit exposure (for example,
premises, equipment, or mortgage servicing rights) would continue to be subject to the general
risk-based capital rules and risk weighted at 100 percent. A brief overview of each A-IRB
portfolio follows.
Wholesale (corporate, interbank, and sovereign) exposures
Wholesale credit exposures comprise three types of exposures: corporate, interbank, and
sovereign. Generally, the meaning of interbank and sovereign would be consistent with the
general risk-based capital rules. Sovereign exposures are those to central governments, central
categories also would not change.
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banks, and certain other public-sector entities (PSEs); interbank exposures are primarily
exposures to banks and securities firms; and corporate exposures are exposures to private-sector
companies. Within the wholesale exposure category, in addition to the treatment for general
corporate lending, there would be four sub-categories of specialized lending (SL). These are
project finance (PF), object finance (OF), commodities finance (CF), and commercial real estate
(CRE). CRE is further subdivided into low asset correlation CRE, and high-volatility CRE
(HVCRE).
For each wholesale exposure, an institution would assign four quantitative risk drivers
(inputs): (1) probability of default (PD), which measures the likelihood that the borrower will
default over a given time horizon; (2) loss given default (LGD), which measures the proportion
of the exposure that will be lost if a default occurs; (3) exposure at default (EAD), which is the
estimated amount owed to the institution at the time of default; and (4) maturity (M), which
measures the remaining economic maturity of the exposure. Institutions generally would be able
to take into account credit risk mitigation techniques (CRM), such as collateral and guarantees
(subject to certain criteria), by adjusting their estimates for PD or LGD. The wholesale A-IRB
risk weight function would use all four risk inputs to produce a specific capital requirement for
each wholesale exposure. There would be a separate, more conservative risk weight function for
certain acquisition, development, and construction loans (ADC) in the HVCRE category.
Retail exposures
Within the retail category three distinct risk weight functions are proposed for three
product areas that exhibit different historical loss experiences and different asset correlations.5
The three retail sub-categories would be: (1) exposures secured by residential mortgages and
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related exposures; (2) qualifying revolving exposures (QRE); and (3) other retail exposures.
QRE would include unsecured revolving credits (such as credit cards and overdraft lines) and
other retail would include most other types of exposures to individuals, as well as certain
exposures to small businesses. The key inputs to the three retail risk weight functions would be a
banking organization’s estimates of PD, LGD, and EAD. There would be no explicit M
component to the retail A-IRB risk weight functions. Unlike wholesale exposures, for retail
exposures, an institution would assign a common set of inputs (PD, LGD, and EAD) to
predetermined pools of exposures, which are typically referred to as segments, rather than for
individual exposures.6 The inputs would be used in the risk weight functions to produce a capital
charge for the associated pool of exposures.
Equity exposures
Banking organizations would use a market-based internal model for determining capital
requirements for equity exposures in the banking book. The internal model approach would
assess capital based on an estimate of loss under extreme market conditions. Some equity
exposures, such as holdings in entities whose debt obligations qualify for a zero percent risk
weight, would continue to receive a zero percent risk weight under the A-IRB approach to
equities. Certain other equity exposures, such as those made through a small business
investment company (SBIC) under the Small Business Investment Act or a community and
economic development entity (CEDE), generally would continue to be risk weighted at 100
percent under the A-IRB approach to equities. Banking organizations that are subject to the
Agencies’ market risk capital rules would continue to apply those rules to assess capital against
5
Asset correlation is a measure of the tendency for the financial condition of a borrower in a banking organization’s
portfolio to improve or degrade at the same time as the financial condition of other borrowers in the portfolio
improve or degrade.
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equity positions held in the trading book.7 Banking organizations that are not subject to the
market risk capital rules would treat equity positions in the trading account as if they were in the
banking book.
Securitization exposures
Under the A-IRB treatment for securitization exposures, a banking organization that
originates a securitization would first calculate the amount of capital it would have to hold
against the pool as if it were not securitized (referred to as KIRB). If an originating banking
organization retains a position in a securitization that obligates the banking organization to
absorb losses up to or less than KIRB, the banking organization would deduct the retained
position from capital as is currently required under the general risk-based capital rules. The
general risk-based capital rules require a dollar-for-dollar risk-based capital deduction for certain
residual interests retained by originating banking organizations in asset securitization
transactions regardless of amount. The A-IRB framework would no longer require automatic
deduction of residual interests as currently defined. The amount to be deducted would be capped
at KIRB for most exposures except those specified in the securitization section. For a position in
excess of the KIRB threshold, the banking organization would use an external-ratings-based
approach (if the position has been rated by an external rating agency or a rating can be inferred)
or a supervisory formula to determine the capital charge for the position.
Non-originating banking organizations that invest in a securitization exposure generally
would use an external-ratings-based approach (if the exposure has been rated by an external
6
When the PD, LGD, and EAD parameters are assigned separately to individual exposures, it may be referred to as
a “bottom-up” approach. When those parameters are assigned to predetermined sets of exposures (pools or
segments), it may be referred to as a “top-down” approach.
7
The market risk capital rules were implemented by the banking agencies in 1996. The market risk capital rules
apply to banking organizations whose trading activity (on a consolidated worldwide basis) equals 10 percent or
more of total assets, or $1 billion or more. The market risk capital rules are found at 12 CFR Part 3, Appendix B
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rating agency or a rating can be inferred). For unrated liquidity facilities that banking
organizations provide to securitizations, capital requirements would be based on several factors,
including the asset quality of the underlying pool and the degree to which other credit
enhancements are available. These factors would be used as inputs to a supervisory formula.
Under the A-IRB approach to securitization exposures, banking organizations also would be
required in some cases to hold regulatory capital against securitizations of revolving exposures
that have early amortization features.
Purchased receivables
Purchased receivables, that is, those that are purchased from another institution either
through a one-off transaction or as part of an ongoing program, would be subject to a two-part
capital charge: one part is for the credit risk arising from the underlying receivables and the
second part is for dilution risk. Dilution risk refers to the possibility that contractual amounts
payable by the underlying obligors on the receivables may be reduced through future cash
payments or other credits to the accounts made by the seller of the receivables. The framework
for determining the capital charge for credit risk permits a purchasing organization to use a topdown (pool) approach to estimating PDs and LGDs when the purchasing organization is unable
to assign an internal risk rating to each of the purchased accounts. The capital charge for dilution
risk would be calculated using the wholesale risk weight function with some additional specified
risk inputs.
The AMA for Operational Risk
Under the A-IRB approach, capital charges for credit risk would be directly calibrated
solely for such risk and, thus, unlike the 1988 Accord, would not implicitly include a charge for
(OCC), 12 CFR Parts 208 and 225, Appendix E (Board), and 12 CFR Part 325, Appendix C (FDIC). The OTS,
to date, has not adopted the market risk capital rules.
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operational risk. As a result, the Agencies are proposing that banking organizations operating
under A-IRB also would have to hold capital for exposure to operational risk. The Agencies are
proposing to define operational risk as the risk of losses resulting from inadequate or failed
internal processes, people, and systems, or external events. Under the AMA, each banking
organization would be able to use its own methodology for assessing exposure to operational risk
provided the methodology is comprehensive and results in a capital charge that is reflective of
the operational risk experience of the organization. The operational risk exposure would be
multiplied by 12.5 to determine a risk-weighted assets equivalent, which would be added to the
comparable amounts for credit and market risk in the denominator of the risk-based capital
ratios. The Agencies will be working closely with institutions over the next few years as
operational risk measurement and management techniques continue to evolve.
Other Considerations
Boundary issues
With the introduction of an explicit regulatory capital charge for operational risk, an issue
arises about the proper treatment of losses that can be attributed to more than one risk factor. For
example, where a loan defaults and the banking organization discovers that the collateral for the
loan was not properly secured, the banking organization’s resulting losses would be attributable
to both credit and operational risk. The Agencies recognize that these types of boundary issues
are important and have significant implications for how banking organizations would compile
loss data sets and compute the regulatory capital charge.
The Agencies are proposing the following standard to govern the boundary between
credit and operational risk: A loss event that has characteristics of credit risk would be
incorporated into the credit risk calculations for regulatory capital. This would include credit-
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related fraud losses. Thus, in the above example, the loss from the loan would be attributed to
credit risk for regulatory capital purposes. This separation between credit and operational risk is
supported by current U.S. accounting standards for the treatment of credit risks.
With regard to the boundary between the trading book and the banking book, for
institutions subject to the market risk rules, positions currently subject to those rules include all
positions held in the trading account consistent with GAAP. The New Accord proposed
additional criteria for positions includable in the trading book for purposes of market risk capital
requirements. The Agencies encourage comment on these additional criteria and whether the
Agencies should consider adopting such criteria (in addition to the GAAP criteria) in defining
the trading book under the Agencies’ market risk capital rules. The Agencies are seeking
comment on the proposed treatment of the boundaries between credit, operational, and market
risk.
Supervisory considerations
The advanced approaches introduce greater complexity to the regulatory capital
framework and would require a high level of sophistication in the banking organizations that
implement the advanced approaches. As a result, the Agencies propose to require core and optin banks to meet certain infrastructure requirements and comply with specific supervisory
standards for credit risk and supervisory criteria for operational risk. In addition, banking
organizations would have to satisfy a set of public disclosure requirements as a prerequisite for
approval to using the advanced approaches. Supervisory guidance for each credit risk portfolio
type, as well as for operational risk is being developed to ensure a sufficient degree of
consistency within the supervisory framework, while also recognizing that internal systems will
differ between banking organizations. The goal is to establish a supervisory framework within
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which all institutions must develop their internal systems, leaving exact details to each
institution. In the case of operational risk in particular, the Agencies recognize that measurement
methodologies are still evolving and flexibility is needed.
It is important to note that supervisors would not look at compliance with requirements,
or standards alone. Supervisors also would evaluate whether the components of an institution’s
advanced approaches are consistent with the overall objective of sound risk management and
measurement. An institution would have to appropriately use the advanced approaches across all
material business lines, portfolios, and geographic regions. Exposures in non-significant
business units as well as asset classes that are immaterial in terms of size and perceived risk
profile may be exempted from the advanced approaches with supervisory approval. These
immaterial portfolios would be subject to the general risk-based capital rules.
Proposed supervisory guidance for corporate credit exposures and for operational risk is
provided separately from this ANPR in today’s Federal Register. The draft supervisory guidance
for corporate credit exposures is entitled “Supervisory Guidance on Internal-Ratings-Based
Systems for Corporate Credit.” The guidance includes specified supervisory standards that an
institution’s internal rating system for corporate exposures would have to satisfy for the
institution to be eligible to use the A-IRB for credit risk. The draft operational risk guidance is
entitled “Supervisory Guidance on Operational Risk Advanced Measurement Approaches for
Regulatory Capital.” The operational risk guidance includes identified supervisory standards for
an institution’s AMA framework for operational risk. The Agencies encourage commenters to
review and comment on the draft guidance pieces in conjunction with this ANPR. The Agencies
intend to issue for public comment supervisory guidance on retail credit exposures, equity
exposures, and securitization exposures over the next several months.
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Supervisory review
As mentioned above, the second pillar of the New Accord focuses on supervisory review
to ensure that an institution holds sufficient capital given its risk profile. The concepts of Pillar 2
are not new to U.S. banking organizations. U.S. institutions already are required to hold capital
sufficient to meet their risk profiles, and supervisors may require that an institution hold more
capital if its current levels are deficient or some element of its business practices suggest the
need for more capital. The Agencies also have the right to intervene when capital levels fall to
an unacceptable level. Given these long-standing elements of the U.S. supervisory framework,
the Agencies are not proposing to introduce specific requirements or guidelines to implement
Pillar 2. Instead, existing guidance, rules, and regulations would continue to be enforced and
supplemented as necessary as part of this proposed new regulatory capital framework. However,
all institutions operating under the advanced approaches would be expected by supervisors to
address specific assumptions embedded in the advanced approaches (such as diversification in
credit portfolios), and would be evaluated for their ability to account for deviations from the
underlying assumptions in their own portfolios.
Disclosure
An integral part of the advanced approaches is enhanced public disclosure practices, and thereby,
improved transparency. Under the Agencies’ proposal, specific disclosure requirements would
be applicable to all institutions using the advanced approaches. These disclosure requirements
would encompass capital, credit risk, credit risk mitigation, securitization, market risk,
operational risk, and interest rate risk in the banking book.
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D. Competitive Considerations
It is essential that the Agencies gain a full appreciation of the possible competitive equity
concerns that may be presented by the establishment of a new capital framework. The creation
of a bifurcated capital framework in the United States -- one set of capital standards applicable to
large, internationally active banking organizations (and those that choose to apply the advanced
approaches), and another set of standards applicable to all other institutions -- has created
concerns among some parties about the potential impact on competitive equity between the two
sets of banking organizations. Similarly, differences in supervisory application of the advanced
approaches (both within the United States and abroad) among large, internationally active
institutions may pose competitive equity issues among such institutions.
The New Accord relies upon compliance with certain minimum operational and
supervisory requirements to promote consistent interpretation and uniformity in application of
the advanced approaches. Nevertheless, independent supervisory judgment will be applied on a
case-by-case basis. These processes, albeit subject to detailed and explicit supervisory guidance,
contain an inherent amount of subjectivity and must be assessed by supervisors on an ongoing
basis. This supervisory assessment of the internal processes and controls leading to an
institution’s internal ratings must maintain the high level of internal risk measurement and
management processes contemplated in this ANPR.
The BSC’s Accord Implementation Group (AIG), on which the Agencies play an active
role, will seek to ensure that all jurisdictions will uniformly apply the same high qualitative and
quantitative standards to internationally active banking institutions. However, to the extent that
different supervisory regimes implement these standards differently, there may be competitive
dislocations. One concern is that the U.S. supervisory regime will impose greater scrutiny in its
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implementation standards, particularly given the extensive on-site presence of bank examiners in
the United States.
Quite distinct from the need for a level playing field among internationally active
institutions are the competitive concerns of those institutions that do not elect to adopt or may
not qualify for the advanced approaches. Some banking organizations have expressed concerns
that small or regional banks would become more likely to be acquired by larger organizations
seeking to lever capital efficiencies. There also is a qualitative concern about the impact of
being considered a “second tier” institution (one that does not implement the advanced
approaches) by the market, rating agencies, or sophisticated customers such as government or
municipal depositors and borrowers. Finally, there is the question of what, if any, competitive
distortions might be introduced by differences in regulatory capital minimums for loans or
securities with otherwise similar risk characteristics, and the extent to which such distortions
may be mitigated in an environment in which well-managed banking organizations continue to
hold excess capital.8
Because the advanced framework in the ANPR is more risk-sensitive than the 1988
Accord and the general risk-based capital rules, banking organizations under the advanced
approaches would face increases in their minimum risk-based capital charges on some assets and
decreases on others. The results of a Quantitative Impact Study (QIS3) the BSC conducted in
late 2002 indicated the potential for the advanced approaches described in this document to
produce significant changes in risk-based capital requirements for specific activities; the results
8
The Agencies note that under the general risk-based capital rules some institutions currently are able to hold less
capital than others on some types of assets (for example, through innovative financing structures or use of credit
risk mitigation techniques). In addition, some institutions may hold lower amounts of capital because the market
perceives them as highly diversified, while others hold higher amounts of capital because of concentrations of
credit risk or other factors.
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also varied on an institution-by-institution basis. The results of QIS3 can be found at
www.bis.org and some references to various results are noted at pertinent places in this ANPR.
The Agencies do not believe the results of QIS3 are sufficiently reliable to form the basis
of a competitive impact analysis, both because the inputs to the study were provided on a bestefforts basis and because the proposals in this ANPR are in some cases different than those that
formed the basis of QIS3. The Agencies are nevertheless interested in views on how the changes
in regulatory capital (for the total of credit and operational risk) of the magnitude described in
QIS3, if such changes were in fact realized, would affect the competitive landscape for domestic
banking organizations.
The Agencies plan to conduct at least one more QIS, and potentially other economic
impact analyses, to better understand the potential impact of the proposed framework on the
capital requirements for individual U.S. banking organizations and U.S. banking organizations as
a whole. This may impact the Agencies’ further proposals through recalibrating the A-IRB risk
weight formulas and making other modifications to the proposed approaches if the capital
requirements do not seem consistent with the overall risk profiles of banking organizations or
safe and sound banking practices.
If competitive effects of the New Accord are determined to be significant, the Agencies
would need to consider potential ways to address those effects while continuing to seek to
achieve the objectives of the current proposal. Alternatives could potentially include
modifications to the proposed approaches, as well as fundamentally different approaches. The
Agencies recognize that an optimal capital system must strike a balance between the objectives
of simplicity and regulatory consistency across banking organizations on the one hand, and the
degree of risk sensitivity of the regulation on the other. There are many criteria that must be
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evaluated in achieving this balance including the resulting incentives for improving risk
measurement and management practices, the ease of supervisory and regulatory enforcement, the
degree to which the overall level of regulatory capital in the banking system is broadly
preserved, and the effects on domestic and international competition. The Agencies are
interested in commenters’ views on alternatives to the advanced approaches that could achieve
this balance, and in particular on alternatives that could do so without a bifurcated approach.9
The Agencies are committed to investigate the full scope of possible competitive impact
and welcome all comments in this regard. Some questions are suggested below that may serve to
focus commenters’ general reactions. More specific questions also are suggested throughout the
ANPR. These questions should not be viewed as limiting the Agencies’ areas of interest or
commenters’ submissions on the proposals. The Agencies encourage commenters to provide
supporting data and analysis, if available.
What are commenters’ views on the relative pros and cons of a bifurcated
regulatory framework versus a single regulatory framework? Would a bifurcated
approach lead to an increase in industry consolidation? Why or why not? What
are the competitive implications for community and mid-size regional banks?
Would institutions outside of the core group be compelled for competitive reasons
to opt-in to the advanced approaches? Under what circumstances might this
occur and what are the implications? What are the competitive implications of
continuing to operate under a regulatory capital framework that is not risk
sensitive?
If regulatory minimum capital requirements declined under the advanced
approaches, would the dollar amount of capital these banking organizations hold
also be expected to decline? To the extent that advanced approach institutions
have lower capital charges on certain assets, how probable and significant are
concerns that those institutions would realize competitive benefits in terms of
pricing credit, enhanced returns on equity, and potentially higher risk-based
capital ratios? To what extent do similar effects already exist under the current
general risk-based capital rules (e.g., through securitization or other techniques
9
In this regard, alternative approaches would take time to develop, but might present fewer implementation
challenges. Additional work would be necessary to advance the goal of competitive equity among
internationally active banking organizations. If consensus on alternative approaches could not be reached at the
BSC, a departure from the Basel framework also could raise significant international and domestic issues.
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that lower relative capital charges on particular assets for only some
institutions)? If they do exist now, what is the evidence of competitive harm?
Apart from the approaches described in this ANPR, are there other regulatory
capital approaches that are capable of ameliorating competitive concerns while
at the same time achieving the goal of better matching regulatory capital to
economic risks? Are there specific modifications to the proposed approaches or
to the general risk-based capital rules that the Agencies should consider?
II.
Application of the Advanced Approaches in the United States
By its terms, the 1988 Accord applied only to internationally active banks. Under the
New Accord, the scope of application has been broadened also to encompass bank holding
companies that are parents of internationally active “banking groups.”
A. Threshold Criteria for Mandatory Advanced Approach Organizations
The Agencies believe that for large, internationally active U.S. institutions only the
advanced approaches are appropriate. Accordingly, the Agencies intend to identify three groups
of banking organizations: (1) large, internationally active banking organizations that would be
subject to the A-IRB and AMA on a mandatory basis (core banks); (2) organizations not subject
to the advanced approaches on a mandatory basis, but that voluntarily choose to adopt those
approaches (opt-in banks); and all remaining organizations that are not mandatorily subject to
and do not apply the advanced approaches (general banks).
For purposes of identifying core banks, the Agencies are proposing a set of objective
criteria for industry consideration. Specifically, the Agencies are proposing to treat as a core
bank any banking organization that has (1) total commercial bank assets of $250 billion or more,
as reported on year-end regulatory reports (with banking assets of consolidated groups
aggregated at the U.S. bank holding company level); 10 or (2) total on-balance-sheet foreign
exposure of $10 billion or more, as reported on the year-end Country Exposure Report (FFIEC
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009) (with foreign exposure of consolidated groups aggregated at the U.S. bank holding
company level). These threshold criteria are independent; meeting either condition would mean
an institution is a core bank.
Once an institution becomes a core bank it would remain subject to the advanced
approaches on a going forward basis. If, in subsequent years, such an institution were to drop
below both threshold levels it would continue to be a core bank unless it could demonstrate to its
primary Federal supervisor that it has substantially and permanently downsized and should no
longer be a core bank. The Agencies are proposing an annual test for assessing banking
organizations in reference to the threshold levels. However, as a banking organization
approaches either of the threshold levels the Agencies would expect to have ongoing dialogue
with that organization to ensure that appropriate practices are in place or are actively being
developed to prepare the organization for implementation of the advanced approaches.
Institutions that by expansion or merger meet the threshold criteria must qualify for use of the
advanced approaches and would be subject to the same implementation plan requirements and
minimum risk-based capital floors applicable to core and opt-in banks as described below.
Institutions that seek to become opt-in banks would be expected to notify their primary Federal
supervisors well in advance of the date by which they expect to qualify for the advanced
approaches. Based on the aforementioned threshold levels, the Agencies anticipate at this time
that approximately ten U.S. institutions would be core banks.
Application of Advanced Approaches at Individual Bank/Thrift Levels
The Agencies are aware that some institutions might, on a consolidated basis, exceed one
of the threshold levels for mandatory application of the A-IRB and AMA and, yet, might be
10
For banks this means the December Consolidated Report of Condition and Income (Call Report). For thrifts this
means the December Thrift Financial Report.
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comprised of distinct bank and thrift charters whose respective sizes fall well below the
thresholds. In those cases, the Agencies believe that all bank and thrift institutions that are
members of a consolidated group that is itself a core bank or an opt-in bank should calculate and
report their risk-based capital requirements under the advanced approaches. However,
recognizing that separate bank and thrift charters may, to a large extent, be independently
managed and have different systems and portfolios, the Agencies are interested in comment on
the efficacy and burden of a framework that requires the advanced approaches to be implemented
by (or pushed down to) each of the separate subsidiary banks and thrifts that make up the
consolidated group.
U.S. Banking Subsidiaries of Foreign Banking Organizations
Any U.S. bank or thrift that is a subsidiary of a foreign bank would have to comply with
the prevailing U.S. regulatory capital requirements applied to U.S. banks. Thus, if a U.S. bank or
thrift that is owned by a foreign bank meets the U.S. threshold criteria for mandatory application
of the advanced approaches, it would be a core bank. If it does not meet those criteria, it would
have the choice to opt-in to the advanced approaches (and be subject to the same supervisory
framework as other U.S. banking organizations) or to remain a general bank. A top-tier U.S.
bank holding company that is owned by a foreign bank also would be subject to the same criteria
for core bank determination and would be subject to the applicable U.S. bank holding company
capital rules. However, Federal Reserve SR Letter 01-1 (January 5, 2001) would remain in
effect. Thus, subject to the conditions in that SR Letter, a top-tier U.S. bank holding company
that is owned or controlled by a foreign bank that is a qualifying financial holding company
generally would not be required to comply with the Board’s capital adequacy guidelines.
The Agencies are interested in comment on the extent to which alternative
approaches to regulatory capital are implemented across national boundaries
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might create burdensome implementation costs for the U.S. subsidiaries of foreign
banks.
B. Implementation for Advanced Approach Organizations
As noted earlier, U.S. banking organizations that apply the advanced approaches would
be required to comply with supervisory standards prior to use.
The BSC has targeted December 31, 2006 as the effective date for the international
capital rules based on the New Accord. The Agencies are proposing an implementation date of
January 1, 2007. The establishment of a final effective date in the United States, however, would
be contingent on the issuance for public comment of a Notice of Proposed Rulemaking, and
subsequent finalization of any changes in capital regulations the Agencies ultimately decide to
adopt.
Because of the need to pre-qualify for the advanced approaches, banking organizations
would need to take a number of steps upon the finalization of any changes to the capital
regulations. These steps would include developing detailed written implementation plans for
A-IRB and AMA and keeping their primary supervisors advised of these implementation plans
and schedules. Implementation plans would need to address all supervisory standards for A-IRB
and AMA, include objectively measurable milestones, and demonstrate that adequate resources
would be realistically budgeted and made available. An institution’s board of directors would
need to approve its implementation plans.
The Agencies expect core banks to make every effort to meet the supervisory standards
as soon as practicable. In this regard, it is possible that some core banks would not qualify to use
the advanced approaches in time to meet the effective date that is ultimately established. For
those banking organizations, the implementation plan would need to identify when the
supervisory standards would be met and when the institution would be ready for implementation.
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The Agencies note that developing an appropriate infrastructure to support the advanced
approaches for regulatory capital that fully complies with supervisory conditions and
expectations and the associated supervisory guidance will be challenging. The Agencies believe,
however, that institutions would need to be fully prepared before moving to the advanced
approaches.
Use of the advanced approaches would require the primary Federal supervisor’s approval.
Core banks unable to qualify for the advanced approaches in time to meet the effective date
would remain subject to the Agencies’ general risk-based capital rules existing at that time.
The Agencies would consider the effort and progress made to meet the qualifying standards and
would consider whether, under the circumstances, supervisory action should be taken against or
penalties imposed on individual core banks that have not adhered to the schedule outlined in the
implementation plan they submitted to their primary Federal supervisor.
Opt-in banks meeting the supervisory standards could seek to qualify for the advanced
approaches in time to meet the ultimate final effective date or any time thereafter. Institutions
contemplating opting-in to the advanced approaches would need to provide notice to, and submit
an implementation plan and schedule to be approved by, their primary Federal supervisor. As is
true of core banks, opt-in banks would need to allow ample time for developing and executing
implementation plans.
An institution’s primary Federal supervisor would have responsibility for determining its
readiness for an advanced approach and would be ultimately responsible, after consultation with
other relevant supervisors, for determining whether the institution satisfies the supervisory
expectations for the advanced approaches. The Agencies recognize that a consistent and
transparent process to oversee implementation of the advanced approaches would be crucial.
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The Agencies would intend to develop interagency validation standards and procedures to help
ensure consistency. The Agencies would consult with each other on significant issues raised
during the validation process and ongoing implementation.
C. Other Considerations
General Banks
The Agencies expect that the vast majority of U.S. institutions would be neither core
banks nor opt-in banks. Most institutions would remain subject to the general risk-based capital
rules. However, as has been the case since the 1988 Accord was initially implemented in the
United States, the Agencies will continue to make necessary modifications to the general riskbased capital rules as deemed appropriate. In the event changes are warranted the Agencies
could implement through notice and comment procedures necessary revisions prior to the
proposed effective date of the advanced approaches in 2007.
The Agencies seek comment on whether changes should be made to the existing
general risk-based capital rules to enhance the risk-sensitivity or to reflect
changes in the business lines or activities of banking organizations without
imposing undue regulatory burden or complication. In particular, the Agencies
seek comment on whether any changes to the general risk-based capital rules are
necessary or warranted to address any competitive equity concerns associated
with the bifurcated framework.
Majority-Owned or Controlled Subsidiaries
The New Accord generally applies to internationally active banking organizations on a
fully consolidated basis. Thus, consistent with the Agencies’ general risk-based capital rules,
subsidiaries that are consolidated under U.S. generally accepted accounting principles (GAAP)
typically should be consolidated for regulatory capital calculation purposes under the advanced
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approaches as well.11 With regard to investments in consolidated insurance underwriting
subsidiaries, the New Accord notes that deconsolidation of assets and deduction of capital is an
appropriate approach. The Federal Reserve is actively considering several approaches with
regard to the capital treatment for investments by bank holding companies in insurance
underwriting subsidiaries. For example, the Federal Reserve is currently assessing the merits
and weaknesses of an approach that would consolidate an insurance underwriting subsidiary’s
assets at the holding company level and permit excess capital of the subsidiary to be included in
the consolidated regulatory capital of the holding company. A deduction would be required for
capital that is not readily available at the holding company level for general use throughout the
organization.
The Federal Reserve specifically seeks comment on the appropriate regulatory
capital treatment for investments by bank holding companies in insurance
underwriting subsidiaries as well as other nonbank subsidiaries that are subject
to minimum regulatory capital requirements.
Transitional Arrangements
Core and opt-in banks would be required to calculate their capital ratios using the A-IRB
and AMA methodologies, as well as the general risk-based capital rules, for one year prior to
using the advanced approaches on a stand-alone basis. In order to begin this parallel-run year,
however, the institution would have to demonstrate to its supervisor that it meets the supervisory
standards and criteria. Therefore, banking organizations planning to meet the January 1, 2007
target effective date for implementation of the advanced approaches would have to receive
approval from their primary Federal supervisor before year-end 2005. Banking organizations
11
One notable exception exists at the bank level where there is an investment in a financial subsidiary as defined in
the Gramm-Leach-Bliley Act of 1999. For such a subsidiary, assets would continue to be deconsolidated from
the bank’s on-balance-sheet assets and capital at the subsidiary level would be deducted from the bank’s capital.
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that later adopt the advanced approaches also would have a one-year dual calculation period
prior to moving to stand-alone usage of the advanced approaches.
An institution would be subject to a minimum risk-based capital floor for two years
following moving to the advanced approaches on a stand-alone basis. Specifically, in the first
year of stand-alone usage of the advanced approaches, an institution’s calculated risk-weighted
assets could not be less than 90 percent of risk-weighted assets calculated under the general riskbased capital rules. In the following year, an institution’s minimum calculated risk-weighted
assets could not be less than 80 percent of risk-weighted assets calculated under the general riskbased capital rules.12 Importantly, the minimum capital requirement and PCA thresholds would
not be changed.
As a consequence, banking organizations would need to conduct two sets of capital
calculations for at least three years. The pre-implementation calculation of A-IRB and AMA
capital would not need to be made public, but the banking organization would be required to
disclose risk-based capital ratios calculated under both approaches during the two-year postimplementation period. The Agencies would not propose to eliminate the floors after the twoyear transition period for any institution applying the advanced approaches until fully satisfied
that the institution’s systems are sound and accurately assess risk and that resulting capital levels
are prudent.
12
The Agencies note that the text above differs from the floor text in the New Accord, which is based on 90 percent
of the minimum capital requirement under the 1988 Accord, rather than on risk-weighted assets. The Agencies
expect that the final language of the New Accord would need to be consistent with this approach. The following
example reflects how the floor in the first year would by applied by a U.S. banking organization. If the banking
organization’s general risk-based capital calculation produced risk-weighted assets of $100 billion in its first
year of implementation of the advanced approaches, then its risk weighted assets in that year could not be less
than $90 billion. If the advanced approach calculation produced risk-weighted assets of $75 billion (a decrease
of one quarter compared to the general risk-based capital rules), it would not calculate risk-based capital ratios
on the basis of that $75 billion; rather, its risk-weighted assets would be $90 billion. Consequently, its minimum
total risk-based capital charge would be $7.2 billion, and it would need $9 billion to satisfy PCA well-capitalized
criteria.
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These transitional arrangements and the floors established above relate only to risk-based
capital ratios and do not affect the continued applicability to all advanced banking organizations
of the leverage ratio and associated PCA regulations for banks and thrifts. Furthermore, during
the implementation period and before removal of the floors the Agencies intend to closely
monitor the effect that the advanced approaches would have on capital levels at the individual
institution and industry-wide levels. Once the results of this monitoring process are assessed, the
Agencies may consider modifications to the advanced approaches to ensure that capital levels
remain prudent.
Given the general principle that the advanced approaches are expected to be
implemented at the same time across all material portfolios, business lines, and
geographic regions, to what degree should the Agencies be concerned that, for
example, data may not be available for key portfolios, business lines, or regions? Is
there a need for further transitional arrangements? Please be specific, including
suggested durations for such transitions.
Do the projected dates provide an adequate timeframe for core banks to be ready to
implement the advanced approaches? What other options should the Agencies
consider?
The Agencies seek comment on appropriate thresholds for determining whether a
portfolio, business line, or geographic exposure would be material. Considerations
should include relative asset size, percentages of capital, and associated levels of risk
for a given portfolio, business line, or geographic region.
III. Advanced Internal Ratings-Based Approach (A-IRB)
This section describes the proposed A-IRB framework for the measurement of capital
requirements for credit risk. Under this framework, banking organizations that meet the A-IRB
infrastructure requirements and supervisory standards would incorporate internal estimates of
risk inputs into supervisor-provided capital formulas for the various debt and equity portfolios to
calculate the capital requirements for each portfolio. The discussion below provides background
on the conceptual basis of the A-IRB approach and then describes the specific details of the
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capital formulas for two of the main exposure categories, wholesale and retail. Separate sections
follow that describe the A-IRB treatments of loan loss reserves, partial charge-offs, and loans
purchased at a discount, the A-IRB treatment of purchased receivables, the A-IRB approach to
equity exposures, and the A-IRB treatment of securitization exposures. The A-IRB supervisory
criteria and credit risk mitigation techniques also are discussed in separate sections.
A. Conceptual Overview
The A-IRB framework has as its conceptual foundation the belief that any range of
possible losses on a portfolio of credit exposures can be represented by a probability density
function (PDF) of possible losses over a one-year time horizon. If known, the parameters of a
PDF can be used to specify a particular level of capital that will lower the probability of the
institution’s insolvency due to adverse credit risk outcomes to a stated confidence level. With a
known or estimated PDF, the probability of insolvency can be measured or estimated directly,
based on the level of reserves and capital available to an institution.
The A-IRB framework builds off this concept and reflects an effort to develop a common
set of risk-sensitive formulas for the calculation of capital for credit risk. To a large extent, this
framework resembles more systematic quantitative approaches to the measurement of credit risk
that many banking organizations have been developing. The approaches being developed by
banking organizations generally rely on a statistical or probability-based assessment of credit risk
and use inputs broadly similar to those required under the A-IRB approach. Like the value-atrisk (VaR) model that forms the basis for the market risk capital rules, the output of these
statistical approaches to credit risk is typically an estimate of loss threshold on a credit exposure
or pool of credit exposures that is highly unlikely to be exceeded by actual credit-related losses
on the exposures or pool.
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Many banking organizations now use such a credit VaR amount as the basis for an
internal assessment of the economic capital necessary to cover credit risk. In this context, it is
common for banking organizations’ internal credit risk models to consider a one-year loss
horizon, and to focus on a high loss threshold confidence level (that is, a loss threshold that has a
small probability of being exceeded), such as the 99.95th percentile. This is because banking
organizations typically seek an estimate of economic capital for credit risk whose probability of
being exceeded is broadly consistent with the institution’s external credit rating and its
associated default probability. For example, the one-year historical probability of default for
AA-rated firms is less than 5 basis points (0.05 percent).
There is a great deal of variation across banking organizations in the specifics of their
credit risk measurement approaches. It is important to recognize that the A-IRB approach is not
intended to allow banking organizations to use all aspects of their own models to estimate
regulatory capital for credit risk. The A-IRB approach has been developed as a single, common
methodology that all advanced approach banking organizations would use, and consists of a set
of formulas (or functions) and a single set of assumptions regarding critical parameters for the
formulas. The A-IRB approach draws on the same conceptual underpinnings as the credit VaR
approaches that banking organizations have developed individually, but likely differs in many
specifics from the approach used by any individual institution.
The specific A-IRB formulas require the banking organization first to estimate certain
risk inputs, which the organization may do using a variety of techniques. The formulas
themselves, into which the estimated risk inputs are inserted, are broadly consistent with the
most common statistical approaches for measuring credit risk, but also are more straightforward
to calculate than those typically employed by banking organizations (which often require
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computer simulations). In particular, an important property of the A-IRB formulas is portfolio
invariance. That is, the A-IRB capital requirement for a particular exposure generally does not
depend on the other exposures held by the banking organization; as with the general risk-based
capital rules, the total credit risk capital requirement for a banking organization is simply the sum
of the credit risk capital requirements on individual exposures or pools of exposures.13
As with the existing credit VaR models, the output of the A-IRB formulas is an estimate
of the amount of credit losses over a one-year period that would only be exceeded a small
percentage of the time. In the case of the A-IRB formulas, this nominal confidence level is set to
99.9 percent. This means that within the context of the A-IRB modeling assumptions a banking
organization’s overall credit portfolio can be thought of as an estimate of the 99.9th percentile of
potential losses on that portfolio over a one-year period. In practice, however, this 99.9 percent
nominal target likely overstates the actual level of confidence because the A-IRB framework
does not explicitly address portfolio concentration issues or the possibility of errors in estimating
PDs, LGDs, or EADs. The choice of the 99.9th percentile reflects a desire on the part of the
Agencies to align the regulatory capital standard with the default probabilities typically
associated with maintaining low investment grade ratings (that is, BBB) even in periods of
economic adversity and to ensure neither a substantial increase or decrease in overall required
capital levels among A-IRB banking organizations compared with the capital levels that would
be required under the general risk-based capital rules. It also recognizes that the risk-based
capital rules count a broader range of instruments as eligible capital (for example, subordinated
debt) than internal economic capital estimates are typically compared with.
13
The theoretical underpinnings for obtaining portfolio-invariant capital charges within credit VaR models are
provided in the paper “A Risk-Factor Model Foundation for Ratings-Based Bank Capital Rules,” by Michael
Gordy, forthcoming in the Journal of Financial Intermediation. The A-IRB formulas are derived as an
application of these results to a single-factor CreditMetrics-style model. For mathematical details on this model,
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Expected Losses versus Unexpected Losses
The diagram below shows a hypothetical loss distribution for a portfolio of credit
exposures over a one-year horizon. The loss distribution is represented by the curve, and is
drawn in such a way that it depicts a higher proportion of losses falling below the mean value
than falling above the mean. The average value of credit losses is referred to as expected loss
(EL). The losses that exceed the expected level are labeled unexpected loss (UL). An
overarching policy question concerns whether the proposed design of the capital requirements
should reflect an expectation that institutions would allocate capital to cover both EL and a
substantial portion of the range of possible UL outcomes, or only the UL portion of the range of
possible losses (that is, from the EL point out to the 99.9th percentile).
The Agencies recognize that some institutions, in their comment letters on earlier BSC
proposals and in discussion with supervisory staffs, have highlighted the view that regulatory
capital should not be allocated for EL. They emphasize that EL is normally incorporated into the
interest rate and spreads charged on specific products, such that EL is covered by net interest
margin and provisioning. The implication is that supervisors would review provisioning policies
and the adequacy of reserves as part of a supervisory review, much as they do today, and would
require additional reserves and/or regulatory capital for EL in cases where reserves were deemed
insufficient. However, the Agencies are concerned that the accounting definition of general
reserves differs significantly across countries, and that banking practices with respect to the
recognition of impairment also are very different. Thus, the Agencies are proposing to include
EL in the calibration of the risk weight functions.
see M. Gordy, “A Comparative Anatomy of Credit Risk Models.” Journal of Banking and Finance, January
2000, or H.U. Koyluogu and A. Hickman, “Reconcilable Differences.” Risk, October 1998.
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The Agencies also note that the current regulatory definition of capital includes a portion
of general reserves. That is, general reserves up to 1.25 percent of risk-weighted assets are
included in the Tier 2 portion of total capital. If the risk weight functions were calibrated solely
to UL, it could be argued that the definition of capital would also need to be revisited. In the
United States, such a discussion would require a review of the provisioning practices of
institutions under GAAP and of the distinctions drawn between specific and general provisions.
Probability Density Function of Credit Losses
Probability
Mean
99.9 percentile
Losses
Expected Losses
Unexpected Losses
The framework described in this ANPR calibrates the risk-based capital requirements to
the sum of EL plus UL, which raises significant calibration issues. Those calibration issues
would be treated differently if the calibration were based only on the estimate of UL. That is,
decisions with respect to significant policy variables that are described below hinge crucially on
the initial decision to base the calibration on EL plus UL, rather than UL only. These issues
include, for example, the appropriate mechanism for incorporating any future margin income
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(FMI) that is associated with particular business lines, as well as the appropriate method for
incorporating general and specific reserves into the risk-based ratios.
A final overarching assumption of the A-IRB framework is the role of asset correlations.
Within the A-IRB capital formulas (as in the credit VaR models of many banking organizations),
asset correlation parameters provide a measure of the extent to which changes in the economic
value of separate exposures are presumed to move together. A higher asset correlation between a
particular asset and other assets in the same portfolio implies a greater likelihood that the asset
will decline in value at the same time as the portfolio as a whole declines in value. Because this
means a greater chance that the asset will be a contributor to high loss scenarios, its capital
requirement under the A-IRB framework also is higher.
Specifically, the A-IRB capital formulas described in detail below are based on the
assumption that correlation in defaults across borrowers is attributable to their common
dependence on one or more systematic risk factors. The basis for this assumption is the
observation that a banking organization’s borrowers are generally susceptible to adverse changes
in the global economy. These systematic factors are distinct from the borrower-specific, or
idiosyncratic, risk factors that determine the probability that a specific loan will be repaid.
Like other risk-factor models, the A-IRB framework assumes that these borrower-specific factors
represent idiosyncratic sources of risk, and thus (unlike the systematic risk-factors) are
diversified in a large lending portfolio.
The A-IRB approach allows for much improved sensitivity to many of the loan-level
determinants of economic capital (such as PD and LGD), but does not explicitly address how an
exposure’s economic capital might vary with the degree of concentration in the overall portfolio
to specific industries or regions, or even to specific borrowers. That is, it neither rewards nor
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penalizes differences across banking organizations in diversification or concentration across
industry, geography and names. To introduce such rewards and penalties in an appropriate
manner would necessarily entail far greater operational complexity for both regulatory and
financial institutions.
In contrast, the portfolio models of credit risk employed by many banking organizations
are quite sensitive to all forms of diversification. That is, the economic capital charge assigned
to a loan within such a model will depend on the portfolio as a whole. In order to apply a
portfolio model to the calibration of A-IRB capital charges, it would be necessary to identify the
assumptions needed so that a portfolio model would yield economic capital charges that do not
depend on portfolio characteristics. Recent advances in the finance literature demonstrate that
economic capital charges are portfolio-invariant if (and only if) two assumptions are imposed.14
First, the portfolio must be infinitely fine-grained. Second, there must be only a single
systematic risk factor.
Infinite granularity, while never literally attained, is satisfied in an approximate sense by
the portfolios of large, internationally active banks. Analysis of data provided by such
institutions shows that taking account of single-name concentrations in such portfolios would
lead to only trivial changes in the total capital requirement. The single risk-factor assumption
would appear, at first glance, more troublesome. As an empirical matter, there undoubtedly are
distinct cyclical factors for different industries and different geographic regions. From a
substantive perspective, however, the relevant question is whether portfolios at large financial
institutions are all diversified across the various sub-sectors of the economy in a reasonably
similar manner. If so, then the portfolio can be modeled as if there were only a single factor,
namely, the credit cycle as a whole.
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The Agencies seek comment on the conceptual basis of the A-IRB approach,
including all of the aspects just described. What are the advantages and
disadvantages of the A-IRB approach relative to alternatives, including those that
would allow greater flexibility to use internal models and those that would be
more cautious in incorporating statistical techniques (such as greater use of
credit ratings by external rating agencies)? The Agencies also encourage
comment on the extent to which the model’s necessary conditions of the
conceptual justification for the A-IRB approach are reasonably met, and if not,
what adjustments or alternative approach would be warranted.
Should the A-IRB capital regime be based on a framework that allocates capital
to EL plus UL, or to UL only? Which approach would more closely align the
regulatory framework to the internal capital allocation techniques currently used
by large institutions? If the framework were recalibrated solely to UL,
modifications to the rest of the A-IRB framework would be required. The
Agencies seek commenters’ views on issues that would arise as a result of such
recalibration.
B. A-IRB Capital Calculations
A common characteristic of the A-IRB capital formulas is that they calculate the actual
dollar value of the minimum capital requirement associated with an exposure (or, in the case of
retail exposures, a pool of exposures). This capital requirement must be converted to an
equivalent amount of risk-weighted assets in order to be inserted into the denominator of a
banking organization’s risk-based capital ratios. Because the minimum risk-based capital ratio
in the United States is 8 percent, the minimum capital requirement on any asset would be equal
to 8 percent of the risk-weighted asset amount associated with that asset. Therefore, in order to
determine the amount of risk-weighted assets to associate with a given minimum capital
requirement, it would be necessary to multiply the dollar capital requirement generated by the
A-IRB formulas by the reciprocal of 8 percent, or 12.5.
The following subsections of the ANPR detail the specific features of the A-IRB capital
formulas for two principal categories of credit exposure: wholesale and retail. Both of these
subsections include a proposed definition of the exposure category, a description of the banking
14
See forthcoming paper by M. Gordy referenced in footnote number 12 above.
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organization-estimated inputs required to complete the capital calculations, a description of the
specific calculations required to determine the A-IRB capital requirement, and tables depicting a
range of representative results.
Wholesale Exposures: Definitions and Inputs
The Agencies propose that a single credit exposure category – wholesale exposures –
would encompass most non-retail credit exposures in the A-IRB framework. The wholesale
category would include the sub-categories of corporate, sovereign, and interbank exposures as
well as all types of specialized lending exposures. Wholesale exposures would include debt
obligations of corporations, partnerships, limited liability companies, proprietorships, and
special-purpose entities (including those created specifically to finance and/or operate physical
assets). Wholesale exposures also would include debt obligations of banks and securities firms
(interbank exposures), and exposures to central governments, central banks, and certain publicsector entities (sovereign exposures). The wholesale exposure category would not include
securitization exposures, or certain small-business exposures that are eligible to be treated as
retail exposures.
The Agencies propose that banking organizations applying the advanced approaches
would use the same A-IRB capital formula to compute capital requirements on all wholesale
exposures with two exceptions. First, wholesale exposures to small- and medium-sized
enterprises (businesses) (SMEs) would use a downward adjustment to the wholesale A-IRB
capital formula typically based on borrower size. Second, the A-IRB capital formula for
HVCRE loans (generally encompassing certain speculative ADC loans) would use a higher asset
correlation assumption than other wholesale exposures.
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The proposed A-IRB capital calculations for wholesale exposures would require banking
organizations to assign four key risk inputs for each individual wholesale exposure: (1)
probability of default (PD); (2) loss given default (LGD); (3) exposure at default (EAD); and (4)
effective remaining maturity (M). In addition, to use the proposed downward adjustment for
wholesale SMEs described in more detail below, banking organizations would be required to
provide an additional input for borrower size (S).
Probability of default
The first principal input to the wholesale A-IRB calculation is the measure of PD. Under
the A-IRB approach, a banking organization would assign an internal rating to each of its
wholesale obligors (or in other words, assign each wholesale exposure to an internal rating grade
applicable to the obligor). The internal rating (rating grade) would have to be produced by a
rating system that meets the A-IRB infrastructure requirements and supervisory standards for
wholesale exposures, which are intended to ensure (among other things) that the rating system
results in a meaningful differentiation of risk among exposures. For each internal rating (or
rating grade), the banking organization must associate a specific one-year PD value. Various
approaches may be used to develop estimates of PDs; however, regardless of the specific
approach, banking organizations would be expected to satisfy the supervisory standards. The
minimum PD that may be assigned to most wholesale exposures is 3 basis points (0.03 percent).
Certain wholesale exposures are exempt from this floor, including exposures to sovereign
governments, their central banks, the BIS, IMF, European Central Bank, and other multilateral
development banks (MDBs) that are high quality MDBs with strong shareholder support.
The Agencies intend to apply standards to the PD quantification process that are
consistent with the broad guidance outlined in the New Accord. More detailed discussion of
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those points is provided in the draft supervisory guidance on IRB approaches for corporate
exposures published elsewhere in today’s Federal Register.
Loss given default
The second principal input to the A-IRB capital formula for wholesale exposures is LGD.
Under the A-IRB approach, banking organizations would estimate an LGD for each wholesale
exposure. An LGD estimate for a wholesale exposure should provide an assessment of the
expected loss in the event of default of the obligor, expressed as a percentage of the institution’s
estimated total exposure at default. The LGD for a defaulted loan would be estimated as the
expected economic loss rate on that exposure taking into account, where appropriate, recoveries,
workout costs, and the time value of money. Banking organizations would estimate LGDs as the
loss severities expected to prevail when default rates are high, unless they have information
indicating that recoveries on a particular class of exposure are unlikely to be affected to an
appreciable extent by cyclical factors. As with estimates of other A-IRB inputs, banking
organizations would be expected to be conservative in assigning LGDs.
Although estimated LGDs should be grounded in historical recovery rates, the A-IRB
approach is structured to allow banking organizations to assess the differential impact of various
factors, including, for example, the presence of collateral or differences in loan terms and
covenants. The Agencies expect to impose limitations on the use of guarantees and credit
derivatives in a banking organization’s LGD estimates. These limitations are discussed in the
separate section on the A-IRB treatment of credit risk mitigation techniques.
Exposure at default
The third principal input to the wholesale A-IRB capital formula is EAD. The Agencies
are proposing that banking organizations would provide their own estimate of EAD for each
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exposure. The EAD for an exposure would be defined as the amount legally owed to the
banking organization (net of any charge-offs) in the event that the borrower defaults on the
exposure. For on-balance-sheet items, banking organizations would estimate EAD as no less
than the current drawn amount. For off-balance-sheet items, except over-the-counter (OTC)
derivative transactions, banking organizations would assign an EAD equal to an estimate of the
long-run default-weighted average EAD for similar facilities and borrowers or, if EADs are
highly cyclical, the EAD expected to prevail when default rates are high. The EAD associated
with OTC derivative transactions would continue to be estimated using the “add-on” approach
contained in the general risk-based capital rules.15 In addition, there would be a specific EAD
calculation for the recognition of collateral in the context of repo-style transactions subject to a
master netting agreement, the features of which are outlined below in the section on the A-IRB
treatment of credit risk mitigation techniques.16
Definition of default and loss
A banking organization would estimate inputs relative to the following definition of
default and loss. A default is considered to have occurred with respect to a particular borrower
when either or both of the following two events has taken place: (1) the banking organization
determines that the borrower is unlikely to pay its obligations to the organization in full, without
recourse to actions by the organization such as the realization of collateral; or (2) the borrower is
more than 90 days past due on principal or interest on any material obligation to the
organization. The Agencies believe that the definition of unlikely to pay is largely consistent
15
Under the add-on approach an institution would determine its EAD for an OTC derivative contract by adding the
current value of the contract (zero if the current value is negative) and an estimate of potential future exposure
(PFE) on the contract. The estimated PFE would be equal to the notional amount of the derivative multiplied by
a supervisor-provided add-on factor that takes into account the type of instrument and its maturity.
16
Repo-style transactions include reverse repurchase agreements and repurchase agreements and securities lending
and borrowing.
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with the practice of U.S. banking organizations in assessing whether a loan is on non-accrual
status.
Maturity
The fourth principal input to the A-IRB capital formula is effective remaining maturity
(M), measured in years. If a wholesale exposure is subject to a determinable cash flow schedule,
the banking organization would calculate M as the weighted-average remaining maturity of the
expected cash flows, using the amounts of the cash flows as the relevant weights. The banking
organization also would be able to use the nominal remaining maturity of the exposure if the
weighted-average remaining maturity of the exposure cannot be calculated. For OTC derivatives
and repo-style transactions subject to master netting agreements, the institution would set M
equal to the weighted-average remaining maturity of the individual transactions, using the
notional amounts of the individual transactions as the relevant weights.
In all cases, M would be set no greater than 5 years and, with few exceptions, M would
be set no lower than one year. The exceptions apply to certain transactions that are not part of a
banking organization’s ongoing financing of a borrower. For wholesale exposures that have an
original maturity of less than three months including repo-style transactions, money market
transactions, trade finance-related transactions, and exposures arising from payment and
settlement processes M may be set as low as one day. For OTC derivatives and repo-style
transactions subject to a master netting agreement, M would be set at no less than five days.
As with the assignment of PD estimates, the Agencies propose to apply supervisory
standards for the estimation of LGD, EAD, and M that are consistent with the broad guidance
contained in the New Accord. More detailed discussion of these issues is provided in the draft
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supervisory guidance on IRB approaches for corporate exposures published elsewhere in today’s
Federal Register.
The Agencies seek comment on the proposed definition of wholesale exposures
and on the proposed inputs to the wholesale A-IRB capital formulas. What are
views on the proposed definitions of default, PD, LGD, EAD, and M? Are there
specific issues with the standards for the quantification of PD, LGD, EAD, or M
on which the Agencies should focus?
Wholesale Exposures: Formulas
The calculation of the A-IRB capital requirement for a particular wholesale exposure
would be accomplished in three steps:
(1)
Calculation of the relevant asset correlation parameter, which would be a function of
PD (as well as firm size (S) for SMEs);
(2)
Calculation of a preliminary capital requirement assuming a maturity of one year,
which would be a function of PD, LGD, EAD, and the asset correlation parameter calculated in
the first step; and
(3)
Application of a maturity adjustment for differences between the actual effective
remaining maturity of the exposure and the one-year maturity assumption in the second step,
where the adjustment would be a function of both PD and M.
These calculations result in the A-IRB capital requirement, expressed in dollars, for a
particular wholesale exposure. As noted earlier, this amount would be converted to a riskweighted assets equivalent by multiplying the amount by 12.5, and the risk-weighted assets
equivalent would be included in the denominator of the risk-based capital ratios.
Asset correlation
The first step in the calculation of the A-IRB capital requirement for a wholesale
exposure is the calculation of the asset correlation parameter, which is denoted by the letter “R”
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in the formulas below. This asset correlation parameter is not a fixed amount; rather, the
parameter varies as an inverse function of PD. For all wholesale exposures except HVCRE
exposures, the asset correlation parameter approaches an upper bound value of 24 percent for
very low PD values and approaches a lower bound value of 12 percent for very high PD values.
This reflects the Agencies’ view that borrowers with lower credit quality (that is, higher PDs) are
likely to be more idiosyncratic in the factors affecting their likelihood of default than borrowers
with higher credit quality (lower PDs). Therefore, the higher PD borrowers are proportionately
less influenced by systematic (sector-wide or economy-wide) factors common to all borrowers.17
An important practical impact of having asset correlation decline with increases in PD is
to reduce the speed with which capital requirements increase as PDs increase, and to increase the
speed with which EL dominates the total capital charge thereby tending to reduce procyclicality
in the application of these capital formulas. The specific formula for determining the asset
correlation parameter for all wholesale exposures except HVCRE exposures is as follows:
R = 0.12 * (1 – EXP(-50 * PD)) + 0.24 * [1 – (1 -EXP(-50 * PD))]
Where:
R denotes asset correlation;
EXP(x) denotes the natural exponential function; and
PD denotes probability of default.
Capital requirement with assumed one-year maturity adjustment
The second step in the calculation of the A-IRB capital requirement for a particular
wholesale exposure is the calculation of the capital requirement that would apply to the exposure
17
See Jose Lopez, “The Empirical Relationship between Average Asset Correlation, Firm Probability of Default,
and Asset Size.” Federal Reserve Bank of San Francisco Working Paper 02-05 (June 2002).
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assuming a one-year effective remaining maturity. The specific formula to calculate this oneyear-maturity capital requirement is as follows:
K1 = EAD * LGD * N[(1 – R)^-0.5 * G(PD) + (R / (1 – R))^0.5 * G(0.999)]
Where:
K1 denotes the one-year-maturity capital requirement;
EAD denotes exposure at default;
LGD denotes loss given default;
N(x) denotes the standard normal cumulative distribution function;
R denotes asset correlation;
G(x) denotes the inverse of the standard normal cumulative distribution function; and18
PD denotes probability of default.
There are several important aspects of this formula. First, it rises in a straight-line
fashion with increases in EAD, meaning that a doubling of the exposure amount would result in
a doubling of the capital requirement. It also rises in a straight-line fashion with increases in
LGD, which similarly implies that a loan with an LGD estimate twice that of an otherwise
identical loan would have twice the capital requirement of the other loan. This also implies that
as LGD or EAD estimates approach zero, the capital requirement would likewise approach zero.
The remainder of the formula is a function of PD, R (asset correlation, which is itself a function
of PD), and the target loss percentile amount of 99.9 percent discussed earlier.
Maturity adjustment
The third stage in the calculation of the A-IRB capital requirement for a particular
wholesale exposure is the application of a maturity adjustment to reflect the exposure’s actual
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effective remaining maturity (M). The A-IRB maturity adjustment multiplies the one-yearmaturity capital requirement (K1) by a factor that depends on both M and PD. The fact that the
A-IRB maturity adjustment depends on PD reflects the Agencies’ view that there is a greater
proportional need for maturity adjustments for high-quality exposures (those with low PDs)
because there is a greater potential for such exposures to deteriorate in credit quality than for
those exposures whose credit quality is lower. The specific formula for applying the maturity
adjustment and generating the A-IRB capital requirement is as follows:
K = K1 * [(M – 2.5) * (1 + b)] / [(-1.5 * (1 + b))], where
b = (0.08451 – 0.05898 * LN(PD))^2
Where:
K denotes the A-IRB capital requirement;
K1 denotes the one-year-maturity capital requirement;
M denotes effective remaining maturity;
LN(x) denotes the natural logarithm; and
PD denotes probability of default.
In this formula, the value “b” effectively determines the slope of the maturity adjustment and is
itself a function of PD. Note that if M is set equal to one, the maturity adjustment also equals
one and K will therefore equal K1.
To provide a more concrete sense of the range of capital requirements under the
wholesale A-IRB framework, the following table presents the A-IRB capital requirements (K)
for a range of values of both PD and M. In this table LGD is assumed to equal 45 percent. For
18
The N(x) and G(x) functions are widely used in statistics and are commonly available in computer spreadsheet
programs. A description of these functions may be found in the Help function of most spreadsheet programs or
in basic statistical textbooks.
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comparison purposes, the general risk-based capital rules assign a capital requirement of 8
percent for most commercial loans.
PD
0.05 percent
0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
20.00 percent
Capital Requirements (in percentage points)
Effective Remaining Maturity (M)
1 month
1 year
3 years
0.50
0.92
1.83
1.00
1.54
2.71
2.17
2.89
4.44
3.57
4.40
6.21
5.41
6.31
8.29
7.65
8.56
10.56
11.91
12.80
14.75
17.67
18.56
20.50
26.01
26.84
28.65
5 years
2.74
3.88
5.99
8.03
10.27
12.56
16.69
22.45
30.47
The impact of the A-IRB capital formulas on minimum risk-based capital requirements
for wholesale exposures would, of course, depend on the actual values of PD, LGD, EAD, and M
that banking organizations would use as inputs to the wholesale formulas. Subject to the caveats
noted earlier, evidence from QIS3 suggested an average reduction in capital requirements for
corporate exposures of about 26 percent for twenty large U.S. banking organizations.
SME adjustment
For loans to SMEs not eligible for retail A-IRB treatment, the proposed calculation of the
A-IRB capital requirement has one additional element – a downward adjustment based on
borrower size (S). This adjustment would effectively lower the A-IRB capital requirement on
wholesale exposures to SMEs with annual sales (or total assets) of less than $50 million. The
Agencies believe the measure of borrower size should be based on annual sales (rather than total
assets), unless the banking organization can demonstrate that it would be more appropriate for
the banking organization to use the total assets of the borrower as its measure of borrower size.
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The borrower size adjustment would be made to the asset correlation parameter (R), as shown in
the following formula:
RSME = R – 0.04 * [1 – (S – 5)/45]
Where
RSME denotes the size-adjusted asset correlation value;
R denotes asset correlation; and
S denotes borrower size (expressed in millions of dollars).
The maximum reduction in the asset correlation parameter based on this formula is
4 percent, and is achieved when borrower size is $5 million. For all borrower sizes below $5
million, borrower size would be set equal to $5 million. The adjustment shrinks to zero as
borrower size approaches $50 million. The broad rationale for this adjustment is the view that
the credit condition of SMEs will be influenced relatively more by idiosyncratic factors than is
the case for larger firms, and, thus, SMEs would be less likely to deteriorate simultaneously with
other exposures. This greater susceptibility to idiosyncratic factors would imply lower asset
correlation. The evidence in favor of this view is mixed, particularly after considering that the
A-IRB framework already incorporates a negative relationship between asset correlation and PD.
The following table illustrates the practical effect of the SME adjustment by depicting the capital
requirements (K) across a range of PDs and borrower sizes. As in the previous table, LGD is
assumed to equal 45 percent. For this table, M is assumed to be equal to three years. Note that
the last column is identical to the three-year maturity column in the preceding table because the
SME adjustment is phased out for borrowers of $50 million or more in size.
Capital Requirements (in percentage points)
PD
$5 million
Borrower Size (S)
$20 million
$35 million
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0.05 percent
0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
20.00 percent
1.44
2.14
3.54
4.97
6.63
8.40
11.70
16.76
24.67
1.57
2.33
3.83
5.37
7.17
9.11
12.73
18.05
26.08
1.70
2.51
4.13
5.79
7.72
9.83
13.74
19.30
27.40
1.83
2.71
4.44
6.21
8.29
10.56
14.75
20.50
28.65
Subject to the caveats mentioned above, evidence from QIS3 suggested an average
reduction in risk-based capital requirements for corporate SME exposure of about 39 percent for
the 20 large U.S. banking organizations that participated in QIS3.
If the Agencies include a SME adjustment, are the $50 million threshold and the
proposed approach to measurement of borrower size appropriate? What
standards should be applied to the borrower size measurement (for example,
frequency of measurement, use of size buckets rather than precise
measurements)?
Does the proposed borrower size adjustment add a meaningful element of risk
sensitivity sufficient to balance the costs associated with its computation? The
Agencies are interested in comments on whether it is necessary to include an SME
adjustment in the A-IRB approach. Data supporting views is encouraged.
Wholesale Exposures: Other Considerations
Specialized lending
The specialized lending (SL) asset class encompasses exposures for which the primary
source of repayment is the income generated by the specific asset(s) being financed, rather than
the financial capacity of a broader commercial enterprise. The SL category encompasses four
broad exposure types:
•
Project finance (PF) exposures finance large, complex, expensive installations that produce
goods or services for sale, such as power plants, chemical processing plants, mines, or
transportation infrastructure, where the source of repayment is primarily the revenues
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generated by sale of the goods or services by the installations.
•
Object finance (OF) exposures finance the acquisition of (typically moveable) physical
assets, such as ships or aircraft, where the source of repayment is primarily the revenues
generated by the assets being financed, often through rental or lease contracts with third
parties.
•
Commodities finance (CF) exposures are structured short-term financings of reserves,
inventories, or receivables of exchange-traded commodities, such as crude oil, metals, or
agricultural commodities, where the source of repayment is the proceeds of the sale of the
commodity.
•
Commercial real estate (CRE) exposures finance the construction or acquisition of real estate
(including land as well as improvements) where the prospects for repayment and recovery
depend primarily on the cash flows generated by the lease, rental, or sale of the real estate.19
The broad CRE category is further divided into two groups: low asset correlation CRE and
HVCRE.20
Most of the issues raised below for comment are described in substantially greater detail,
in the context of CRE exposures, in a white paper entitled “Loss Characteristics of CRE Loan
Portfolios,” released by the Federal Reserve Board on June 10, 2003. Commenters are
19
CRE exposures are typically non-recourse exposures, often to special purpose vehicles, and are distinguishable
from corporate exposures that are collateralized by real estate for which the prospects for repayment and
recovery depend primarily on the financial performance of the broader commercial enterprise that is the obligor.
20
To describe a loan portfolio as having a relatively high asset correlation means that any defaults that occur in that
portfolio are relatively likely to occur at the same time, and for this reason the portfolio is likely to exhibit
greater variability in aggregate default rates. For two portfolios with the same EL, the portfolio with more
highly variable aggregate default rates warrants higher capital to cover UL (“bad-tail events”) with the same
level of confidence. Describing a portfolio as having a relatively high asset correlation does not imply that loans
in that portfolio have relatively high PD, LGD, or EL. In particular, loans in high asset correlation portfolios
may well have very low PDs and LGDs (and therefore ELs); conversely, loans in low asset correlation portfolios
may have very high PDs and LGDs (and ELs). For any two loans from a portfolio with a given asset correlation
(or from two different portfolios with the same asset correlation), the loan with the lower EL should be assigned
a lower risk weight. For any two loans with the same EL, the loan from the portfolio with the lower asset
correlation should incur a lower capital charge, because bad-tail events are less likely to occur in that portfolio.
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encouraged to read the white paper in conjunction with this section.
A defining characteristic of SL exposures (including CRE) is that the risk factors
influencing actual default rates are likely to influence LGDs as well. This is because both the
borrower’s ability to repay an exposure and the banking organization’s recovery on an exposure
in the event of default are likely to depend on the same underlying factors, such as the net cash
flows of the property being financed. This suggests a positive correlation between observed
default frequencies and observed loss rates on defaulted loans, with both declining during
periods of favorable economic conditions and both increasing during unfavorable economic
periods. While cyclicality in LGDs may be significant for a number of lending activities, the
Agencies believe that cyclicality is likely to be the norm for SL portfolios, and that a banking
organization’s procedures for estimating LGD inputs for SL exposures should assess and
quantify this cyclicality in a comprehensive and systematic fashion.
The Agencies invite comment on ways to deal with cyclicality in LGDs. How can
risk sensitivity be achieved without creating undue burden?
For core and opt-in banks that may not be able to provide sufficiently reliable estimates
of PD, LGD, and M for each SL exposure, the New Accord offers a Supervisory Slotting Criteria
(SSC) approach. Under this approach, rather than estimating the loan-level risk parameters,
banking organizations would use slotting criteria to map their internal risk rating grades to one of
five supervisory rating grades: Strong, Good, Satisfactory, Weak, and Default. In addition,
supervisory risk weights would be assigned to each of these supervisory rating grades. To assist
banking organizations in implementing these supervisory rating grades, for reference purposes
the New Accord associates each with an explicit range of external rating grades. If the SSC
approach were allowed in the United States, the Agencies would have to develop slotting criteria
that would take into account factors such as market conditions; financial ratios such as debt
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service coverage or loan-to-value ratios; cash flow predictability; strength of sponsor or
developer; and other factors likely to affect the PD and/or LGD of each loan.
The Agencies invite comment on the merits of the SSC approach in the United
States. The Agencies also invite comment on the specific slotting criteria and
associated risk weights that should be used by organizations to map their internal
risk rating grades to supervisory rating grades if the SSC approach were to be
adopted in the United States.
Under the A-IRB approach, a banking organization would estimate the risk parameters
for each SL exposure and then calculate the A-IRB capital charge for the estimated EAD by
substituting the estimated PD, LGD, and M into one of two risk weight functions. The first risk
weight function is the wholesale risk weight function and applies to all PF, OF, and CF
exposures, as well as to all low asset correlation CRE exposures (including in-place commercial
properties). The second risk weight function applies to all HVCRE exposures. It also is the
same as the wholesale risk weight function, except that it incorporates a higher asset correlation
parameter. The asset correlation equation for HVCRE is as follows:
R = 0.12 x (1-EXP (-50 x PD)) + 0.30 x [EXP (-50 x PD)]
Where
R denotes asset correlation;
EXP denotes the natural exponential function; and
PD denotes probability of default.
The following table presents the A-IRB capital requirement (K) for a range of values of
both PD and M. In this table, EAD is assumed to equal $100 and LGD is assumed to equal 45
percent. This LGD is used for consistency with the similar table for wholesale exposures and
should not be construed as an indication that 45 percent is a typical LGD for HVCRE exposures.
HVCRE Capital Requirements (in percentage points)
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Effective Remaining Maturity
PD
0.05 percent
0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
20.00 percent
1 year
1.24
2.05
3.74
5.52
7.53
9.55
13.12
18.59
26.84
3 years
2.46
3.61
5.76
7.79
9.89
11.79
15.12
20.54
28.65
5 years
3.68
5.16
7.77
10.07
12.25
14.02
17.11
22.49
30.47
All ADC loans would be treated as HVCRE loans, unless the borrower has “substantial
equity” at risk or the property is pre-sold or sufficiently pre-leased. In part, this reflects some
empirical evidence suggesting that most ADC loans have relatively high asset correlations. It
also, however, reflects a longstanding supervisory concern that CRE lending to finance
speculative construction and development is vulnerable to, and may worsen, speculative swings
in CRE markets, especially when there is little borrower equity at risk. Such lending was a
major factor causing the stress experienced by many banks in the early 1990s, not only in the
United States but in other countries as well.
Under the New Accord SL loans financing the construction of one- to four-family
residential properties (single or in subdivisions) are included with other ADC loans in the high
asset correlation category. However, loans financing the construction of pre-sold one- to fourfamily residential properties would be eligible to be treated under the low asset correlation
treatment. In some cases the loans may finance the construction of subdivisions or other groups
of houses, some of which are pre-sold while others are not.
Under the New Accord, each national supervisory authority is directed to recognize and
incorporate into its implementation of the New Accord the high asset correlation determinations
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of other national supervisory authorities for loans made in their respective jurisdictions. Thus,
when the Agencies designate certain CRE properties as HVCRE, foreign banking organizations
making extensions of credit to those properties also would be expected to treat them as HVCRE.
Similarly, when non-U.S. supervisory authorities designate certain CRE as HVCRE, U.S.
banking organizations that extend credit to those properties would be expected to treat them as
HVCRE.
The Agencies invite the submission of empirical evidence regarding the (relative
or absolute) asset correlations characterizing portfolios of land ADC loans, as
well as comments regarding the circumstances under which such loans would
appropriately be categorized as HVCRE.
The Agencies also invite comment on the appropriateness of exempting from the
high asset correlation category ADC loans with substantial equity or that are presold or sufficiently pre-leased. The Agencies invite comment on what standard
should be used in determining whether a property is sufficiently pre-leased when
prevailing occupancy rates are unusually low.
The Agencies invite comment on whether high asset correlation treatment for oneto four-family residential construction loans is appropriate, or whether they
should be included in the low asset correlation category. In cases where loans
finance the construction of a subdivision or other group of houses, some of which
are pre-sold while others are not, the Agencies invite comment regarding how the
“pre-sold” exception should be interpreted.
The Agencies invite comment on the competitive impact of treating defined classes
of CRE differently. What are commenters’ views on an alternative approach
where there is only one risk weight function for all CRE? If a single asset
correlation treatment were considered, what would be the appropriate asset
correlations to employ within a single risk-weight function applied to all CRE
exposures?
Lease financings
Under the wholesale A-IRB framework, some lease financings require special
consideration. A distinction is made for leases that expose the lessor to residual value risk,
namely the risk of the fair value of the assets declining below the banking organization’s
estimate of residual risk at lease inception. If a banking organization has exposure to residual
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value risk, it would assign a 100 percent risk weight to the residual value amount and determine
a risk-weighted asset equivalent for the lease’s remaining net investment (net of residual amount)
using the same methodology as any other wholesale exposure. The sum of these components
would be the risk-weighted asset amount for a particular lease. Where a banking organization
does not have exposure to residual value risk, the lease net investment would be subject to a
capital charge using the same methodology applied to any other wholesale exposure.
This approach would be used regardless of accounting classification as a direct finance,
operating or leveraged lease. For leveraged leases, when the banking organization is the equity
participant it would net the balance of the non-recourse debt against the discounted lease
payment stream prior to applying the risk weight. If the bank is the debt participant, the
exposure would be treated as any other wholesale credit exposure.
The Agencies are seeking comment on the wholesale A-IRB capital formulas and
the resulting capital requirements. Would this approach provide a meaningful
and appropriate increase in risk sensitivity in the sense that the results are
consistent with alternative assessments of the credit risks associated with such
exposures or the capital needed to support them? If not, where are there material
inconsistencies?
Does the proposed A-IRB maturity adjustment appropriately address the risk
differences between loans with differing maturities?
Retail Exposures: Definitions and Inputs
The second major exposure category in the A-IRB framework is the retail exposure
category. This category encompasses the vast majority of credit exposures to individual
consumers. The Agencies also are considering whether certain SME exposures should be
eligible for retail A-IRB treatment. The retail exposure category has three distinct subcategories: (1) residential mortgages (and related exposures); (2) qualifying revolving exposures
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(QREs); and (3) other retail exposures. There are separate A-IRB capital formulas for each of
these three sub-categories to reflect different levels of associated risk.
The Agencies propose that the residential mortgage exposure sub-category be defined to
include loans secured by first or subsequent liens on one- to four-family residential properties,
including term loans and revolving lines of credit secured by home equity. There would be no
upper limit on the size of the exposure that could be included in the residential mortgage
exposure sub-category, but the borrower would have to be an individual and the banking
organization should generally manage the exposure as part of a pool of similar exposures.
Residential mortgage exposures that are individually internally rated and managed similarly to
commercial exposures, rather than managed and internally rated as pools, would be treated under
the wholesale A-IRB framework.
The second sub-category of retail exposures is qualifying revolving exposures (QREs).
The Agencies propose to define QREs as exposures to individuals that are revolving, unsecured,
uncommitted, less than $100,000, and managed as part of a pool of similar exposures. In
practice, QREs will include primarily exposures where customers’ outstanding borrowings are
permitted to fluctuate based on their own decisions to borrow and repay, up to a limit established
by the banking organization. Most credit card exposures to individuals and overdraft lines on
individual checking accounts would be QREs.
The third sub-category of retail exposures, other retail, includes two types of exposures.
First, it encompasses all exposures to individuals for non-business purposes that are generally
managed as part of a pool of similar exposures and that do not meet the conditions for inclusion
in the first two sub-categories of retail exposures. The Agencies are not proposing to establish a
fixed upper limit on the size of exposures to individuals that are eligible for the other retail
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treatment. In addition, the Agencies are proposing that the other retail sub-category include
certain SME exposures that are managed on a pool basis similar to retail exposures. These
exposures could be to a company or to an individual. The Agencies are considering an
individual borrower exposure threshold of $1 million for such exposures. For the purpose of
assessing compliance with the individual borrower exposure threshold, the banking organization
would aggregate all exposures to the individual borrower on a fully consolidated basis. Credit
card accounts with balances between $100,000 and $1 million would be considered other retail
rather than QRE, even if the accounts are extended to or guaranteed by an individual and used
exclusively for small business purposes.
The Agencies are interested in comment on whether the proposed $1 million
threshold provides the appropriate dividing line between those SME exposures
that banking organizations should be allowed to treat on a pooled basis under the
retail A-IRB framework and those SME exposures that should be rated
individually and treated under the wholesale A-IRB framework.
One of the most significant differences between the wholesale and retail A-IRB
categories is that the risk inputs for retail exposures do not have to be assigned at the level of an
individual exposure. The Agencies recognize that banking organizations typically manage retail
exposures on a portfolio or pool basis, where each portfolio or pool contains exposures with
similar risk characteristics. Therefore, a key characteristic of the retail A-IRB framework is that
the risk inputs for retail exposures would be assigned to portfolios or pools of exposures rather
than to individual exposures.
It is important to highlight that within each of the three sub-categories of retail exposures,
the retail A-IRB framework is intended to provide banking organizations with substantial
flexibility to use the retail portfolio segmentation that they believe is most appropriate for their
activities. In determining how to group their retail exposures within each sub-category into
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portfolio segments for the purpose of assigning A-IRB risk inputs, the Agencies believe that
banking organizations should use a segmentation approach that is consistent with their approach
for internal risk assessment purposes and that classifies exposures according to predominant risk
characteristics.
As general principles for segmentation, banking organizations would group exposures in
each of the three retail sub-categories into portfolios or pools according to the sub-category’s
principal risk drivers, and would have to be able to demonstrate that the resultant segmentation
effectively differentiates and rank orders risk and provides reasonably accurate and consistent
quantitative estimates of PD, LGD, and EAD. With the exceptions noted below, the Agencies
are not proposing that institutions must consider any particular risk drivers or employ any
minimum number of portfolios or pools in any of the three retail sub-categories. The only
specific limitations that the Agencies would propose in regard to the portfolio segmentation of
retail exposures are (1) banking organizations generally would not be permitted to combine retail
exposures from multiple countries into the same portfolio segment (because of differences in
national legal systems and bankruptcy regimes), and (2) banking organizations would need to
separately segment delinquent retail exposures.
The inputs to the retail A-IRB capital formulas differ slightly from the inputs to the
wholesale A-IRB capital formulas. Measures of PD, LGD, and EAD remain important elements,
but there is no M input to the retail A-IRB capital formulas. Rather, the retail A-IRB capital
formulas implicitly incorporate average maturity effects in general, such as in the residential
mortgage sub-category.
Aside from the applicable definition of default, the definitions of PD, LGD, and EAD for
retail exposures are generally equivalent to those for wholesale exposures. One additional
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element of potential flexibility for banking organizations in the retail context needs to be
highlighted. The Agencies recognize that certain banking organizations that may qualify for the
advanced approaches segment their retail portfolios for management purposes by EL, rather than
by separately measuring PD and LGD, as required under the A-IRB framework. Therefore, the
Agencies propose that banking organizations be permitted substantial flexibility in translating
measures of EL into the requisite PD and LGD inputs. For non-revolving portfolio segments, EL
generally would equal the product of PD and LGD, so that if a banking organization has an
estimate of EL and either PD or LGD, it would be able to infer an estimate of the other required
input.
In addition, the Agencies are proposing that if one or the other of PD and LGD did not
tend to vary significantly across portfolio segments, the banking organization would be permitted
to apply a general estimate of that input to multiple segments and to use that general estimate,
together with segment-specific estimates of EL, to infer segment-specific estimates of the other
required input. The Agencies note, however, that this proposal offers substantial flexibility to
institutions and may, in fact, be overly flexible (for example, because LGDs on residential
mortgages tend to be quite cyclical). For these loans, the above method of inferring PDs or
LGDs from a long-run average EL would not necessarily result in PD being estimated as a longrun average, and LGD would not necessarily reflect the loss rate expected to prevail when
default rates are high. Banking organizations using an EL approach would have to ensure that
the A-IRB capital requirement under this method is at least as conservative as a PD/LGD method
in order to minimize any potential divergences between capital requirements computed under the
PD/LGD approach versus an EL approach.
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As in the wholesale A-IRB framework, a floor of 3 basis points (0.03 percent) applies to
the PD estimates for all retail exposures (that is, the minimum PD is 3 basis points). In addition,
for residential mortgage exposures other than those guaranteed by a sovereign government, a
floor of 10 percent on the LGD estimate would apply, based on the view that LGDs during
periods of high default rates are unlikely to fall below this level if measured appropriately.
Along with the overall monitoring of the implementation of the advanced approaches and the
determination whether to generally relax the floors established during the initial implementation
phases (that is, the 90 and 80 percent floors), the Agencies intend to review the need to retain PD
and LGD floors for retail exposures following the first two years of implementation of the AIRB framework.
The Agencies are proposing the following data requirements for retail A-IRB. Banking
organizations would have to have a minimum of five years of data history for PD, LGD, and
EAD, and preferably longer periods so as to include a complete economic cycle. Banking
organizations would not have to give equal weight to all historical factors if they can
demonstrate that the more recent data are better predictors of the risk inputs. Also, banking
organizations would have to have a minimum of three years of experience with their
segmentation and risk management systems.
Definition of default and loss
The retail definition of default and loss being proposed by the Agencies differs
significantly from that proposed for the wholesale portfolio. Specifically, the Agencies propose
to use the definitions of loss recognition embodied in the Federal Financial Institutions
Examination Council (FFIEC) Uniform Retail Credit Classification and Account Management
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Policy.21 All residential mortgages and all revolving credits would be charged off, or charged
down to the value of the property, after a maximum of 180 days past due; other credits would be
charged off after a maximum of 120 days past due.
In addition, the Agencies are proposing to define a retail default to include the occurrence
of any one of the three following events if it occurs prior to the respective 120- or 180-day
FFIEC policy trigger: (1) a full or partial charge-off resulting from a significant decline in credit
quality of the exposure; (2) a distressed restructuring or workout involving forbearance and loan
modification; or (3) a notification that the obligor has sought or been placed in bankruptcy.
Finally, for retail exposures (as opposed to wholesale) the definition of default could be applied
to a particular facility, rather than to the obligor. That is, default on one obligation would not
require a banking organization to treat all other obligations of the same obligor as defaulted.
Undrawn lines
The treatment of undrawn lines of credit, in particular those associated with credit cards,
merits specific discussion. Banking organizations would be permitted to incorporate undrawn
retail lines in one of two ways. First, banking organizations could incorporate them into their
EAD estimates directly, by assessing the likelihood that undrawn balances would be drawn at the
time of an event of default. Second, banking organizations could incorporate them into LGD
estimates by assessing the size of potential losses in default (including those arising from both
currently drawn and undrawn balances) as a proportion of the current drawn balance. In the
latter case, it is possible that the relevant LGD estimates would exceed 100 percent. While the
proposed EAD approach for undrawn wholesale and retail lines is the same, the Agencies are
aware that the sheer volume of credit card undrawn lines and the ratio of undrawn lines to
21
The FFIEC Uniform Retail Credit Classification and Account Management Policy was issued on June 12, 2000.
It is available on the FFIEC website at www.FFIEC.gov.
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outstanding balances create issues for undrawn retail lines that differ from undrawn wholesale
lines not only in degree but also in kind.
An additional issue arises in connection with the undrawn lines associated with credit
card accounts whose drawn balances (but not undrawn balances) have been securitized. To the
extent that banking organizations remain exposed to the risk that such undrawn lines will be
drawn, but these undrawn lines are not themselves securitized, then there is a need for
institutions to hold regulatory capital against such undrawn lines. The Agencies propose that a
banking organization would be required to hold capital against the full amount of any undrawn
lines regardless of whether drawn amounts are securitized. This presumes that the institution
itself is exposed to the credit risk associated with future draws.
The Agencies are interested in comments and specific proposals concerning
methods for incorporating undrawn credit card lines that are consistent with the
risk characteristics and loss and default histories of this line of business.
The Agencies are interested in further information on market practices in this
regard, in particular the extent to which banking organizations remain exposed to
risks associated with such accounts. More broadly, the Agencies recognize that
undrawn credit card lines are significant in both of the contexts discussed above,
and are particularly interested in views on the appropriate retail IRB treatment of
such exposures.
Future margin income
In the New Accord, the retail A-IRB treatment of QREs includes a unique additional
input that arises because of the large amount of expected losses typically associated with QREs.
As noted above, the A-IRB approach would require banking organizations to hold regulatory
capital against both EL and UL. Banking organizations may typically seek to cover expected
losses through interest income and fees for all of their business activities and the Agencies
recognize that this practice is a particularly important aspect of the business model for QREs.
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The Agencies are including in this proposal for the QRE sub-category only, that future
margin income (FMI) be permitted to offset a portion of the A-IRB retail capital charge relating
to EL. For this purpose, the Agencies propose to define the amount of eligible FMI for the QRE
sub-category as the amount of income anticipated to be generated by the relevant exposures over
the next twelve months that can reasonably be assumed to be available to cover potential credit
losses on the exposures after covering expected business expenses, and after subtracting a
cushion to account for potential volatility in credit losses (UL). FMI would not be permitted to
include anticipated income from new accounts and would have to incorporate assumptions about
income from existing accounts that are in line with the banking organization’s historical
experience. The amount of the cushion to account for potential volatility in credit losses would
be set equal to two standard deviations of the banking organization’s annualized loss rate on the
exposures. The Agencies would expect banking organizations to be able to support their
estimates of eligible FMI on the basis of historical data and would disallow the use of FMI in the
QRE capital formula if this is not the case. The step needed to recognize eligible FMI is
discussed below.
Permitting a FMI offset to the A-IRB capital requirement for QREs could have a
significant impact on the level of minimum regulatory capital at institutions adopting the
advanced approaches. The Agencies would need to fully assess and analyze the impact of such
an FMI offset on institutions’ risk-based capital ratios prior to final implementation of the A-IRB
approach. Furthermore, the Agencies anticipate the need to issue additional guidance setting out
more specific expectations in this regard.
For the QRE sub-category of retail exposures only, the Agencies are seeking
comment on whether or not to allow banking organizations to offset a portion of
the A-IRB capital requirement relating to expected losses by demonstrating that
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their anticipated FMI for this sub-category is likely to more than sufficiently
cover expected losses over the next year.
The Agencies are seeking comment on the proposed definitions of the retail A-IRB
exposure category and sub-categories. Do the proposed categories provide a
reasonable balance between the need for differential treatment to achieve risksensitivity and the desire to avoid excessive complexity in the retail A-IRB
framework? What are views on the proposed approach to inclusion of smallbusiness exposures in the other retail category?
The Agencies are also seeking views on the proposed approach to defining the
risk inputs for the retail A-IRB framework. Is the proposed degree of flexibility in
their calculation, including the application of specific floors, appropriate? What
are views on the issues associated with undrawn retail lines of credit described
here and on the proposed incorporation of FMI in the QRE capital determination
process?
The Agencies are seeking comment on the minimum time requirements for data
history and experience with segmentation and risk management systems: Are
these time requirements appropriate during the transition period? Describe any
reasons for not being able to meet the time requirements.
Retail Exposures: Formulas
The retail A-IRB capital formulas are very similar to the wholesale A-IRB formulas, and
are based on the same underlying concepts. However, because there is no M adjustment
associated with the retail A-IRB framework, the retail A-IRB capital calculations generally
involve fewer steps than the wholesale A-IRB capital calculations. As with the wholesale A-IRB
framework, the output of the retail A-IRB formulas is a minimum capital requirement, expressed
in dollars, for the relevant set of exposures. The capital requirement would be converted into an
equivalent amount of risk-weighted assets by multiplying the capital requirement by 12.5. The
two key steps in implementing the retail A-IRB capital formulas are (1) assessing the relevant
asset correlation parameter, and (2) calculating the minimum capital requirement for the relevant
pool of exposures.
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Residential mortgages and related exposures
For residential mortgage and related exposures, the retail A-IRB capital formula requires
only one step. This is because the asset correlation parameter for such exposures is fixed at 15
percent, regardless of the PD. The fixed asset correlation parameter reflects the Agencies’ view
that the arguments for linking the asset correlation to PD, as occurs in the wholesale A-IRB
framework and in the other two sub-categories of retail exposures, are not as relevant for
residential mortgage-related exposures, whose performance is significantly influenced by
broader trends in the housing market for borrowers of all credit qualities. The assumed asset
correlation of 15 percent also seeks implicitly to reflect the higher average maturity associated
with residential mortgage exposures and is therefore higher than would likely be the case if a
specific maturity adjustment were also included in the framework. The proposed retail A-IRB
capital formula for residential mortgage and related exposures is as follows:
K = EAD * LGD * N[1.08465 * G(PD) + 0.4201 * G(0.999)]
Where
K denotes the capital requirement;
EAD denotes exposure at default;
LGD denotes loss given default;
N(x) denotes the standard normal cumulative distribution function;
G(x) denotes the inverse of the standard normal cumulative distribution function; and
PD denotes probability of default.
The following table depicts a range of representative capital requirements (K) for
residential mortgage and related exposures based on this formula. The EAD is assumed to be
equal to $100. Three different illustrative LGD assumptions are shown: 15 percent, 35 percent,
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and 55 percent. For comparison purposes, the current capital requirement on most first mortgage
loans is 4 percent and on most home equity loans is 8 percent.
Capital Requirements (in percentage points)
PD
0.05 percent
0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
20.00 percent
LGD
35 percent
0.41
0.70
1.41
2.36
3.86
6.17
10.97
16.22
22.75
15 percent
0.17
0.30
0.61
1.01
1.65
2.64
4.70
6.95
9.75
55 percent
0.64
1.10
2.22
3.70
6.06
9.70
17.24
25.49
35.75
Subject to the caveats noted earlier, evidence from QIS3 suggested that advanced
approach banking organizations would experience a reduction in capital requirements for
mortgage exposures of about 56 percent.
Private mortgage insurance
The Agencies wish to highlight one issue associated with the A-IRB capital requirements
for the residential mortgage sub-category relating to the treatment of private mortgage insurance
(PMI). Most PMI arrangements effectively provide partial compensation to the banking
organization in the event of a mortgage default. Accordingly, the Agencies consider that it may
be appropriate for banking organizations to recognize such effects in the LGD estimates for
individual portfolio segments, consistent with the historical loss experience on those segments
during periods of high default rates. Such an approach would avoid requiring banking
organizations to quantify specifically the effect of PMI on a loan-by-loan basis; rather, they
could estimate the effect of PMI on an average basis for each segment. This approach
effectively ignores the risk that the mortgage insurers themselves could default.
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The Agencies also seek comment on the competitive implications of allowing PMI
recognition for banking organizations using the A-IRB approach but not allowing
such recognition for general banks. In addition, the Agencies are interested in
data on the relationship between PMI and LGD to help assess whether it may be
appropriate to exclude residential mortgages covered by PMI from the proposed
10 percent LGD floor. The Agencies request comment on whether or the extent to
which it might be appropriate to recognize PMI in LGD estimates.
More broadly, the Agencies are interested in information regarding the risks of
each major type of residential mortgage exposure, including prime first
mortgages, sub-prime mortgages, home equity term loans, and home equity lines
of credit. The Agencies are aware of various views on the resulting capital
requirements for several of these product areas, and wish to ensure that all
appropriate evidence and views are considered in evaluating the A-IRB treatment
of these important exposures.
The risk-based capital requirements for credit risk of prime mortgages could well
be less than one percent of their face value under this proposal. The Agencies are
interested in evidence on the capital required by private market participants to
hold mortgages outside of the federally insured institution and GSE environment.
The Agencies also are interested in views on whether the reductions in mortgage
capital requirements contemplated here would unduly extend the federal safety
net and risk contributing to a credit-induced bubble in housing prices. In
addition, the Agencies are also interested in views on whether there has been any
shortage of mortgage credit under general risk-based capital rules that would be
alleviated by the proposed changes.
Qualifying revolving exposures
The second sub-category of retail exposures is QREs. The calculation of capital
requirements for QREs would require three steps: (1) calculation of the relevant asset correlation,
(2) calculation of the minimum capital requirement assuming no offset for eligible FMI, and (3)
application of the offset for eligible FMI. These steps would be performed for each QRE
portfolio segment individually.
As in the case of wholesale exposures, it is assumed that the asset correlation for QREs
declines as PD rises. This reflects the view that pools of borrowers with lower credit quality
(high PD) are less likely to experience simultaneous defaults than pools of higher credit quality
(low PD) borrowers, because with high PD borrowers defaults are more likely to result from
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borrower-specific or idiosyncratic factors. In the case of QREs, the asset correlation approaches
an upper bound value of 11 percent for very low PD values and approaches a lower bound value
of 2 percent for very high PD values. The specific formula for determining the asset correlation
parameter for QREs is as follows:
R = 0.02 * (1 – EXP(-50 * PD)) + 0.11 * [1 – (1 - EXP(-50 * PD))]
Where
R denotes correlation;
EXP denotes the natural exponential function; and
PD denotes probability of default.
The second step in the A-IRB capital calculation for QREs would be the calculation of
the capital requirement assuming no FMI offset. The specific formula to calculate this amount is
as follows:
KNo FMI = EAD * LGD * N[(1 – R)^-0.5 * G(PD) + (R / (1 – R))^0.5 * G(0.999)]
Where
KNoFMI denotes capital requirement assuming no FMI offset;
EAD denotes exposure at default;
LGD denotes loss given default;
N(x) denotes the standard normal cumulative distribution function;
R denotes asset correlation;
G(x) denotes the inverse of the standard normal cumulative distribution function; and
PD denotes probability of default.
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Future margin income adjustment
The result of this calculation effectively includes both an EL and a UL component. As
already discussed, for QREs only, the Agencies are considering the possibility of allowing
institutions to offset a portion of the EL portion of the capital requirement using eligible FMI, as
defined above. Up to 75 percent of the EL portion of the capital requirement could potentially be
offset in this fashion. The specific calculation for determining the capital requirement (K) after
application of the potential offset for eligible FMI is as follows.
K = KNo FMI – eligible FMI offset
Where
K denotes the capital requirement after application of an offset for eligible FMI;
KnoFMI denotes the capital requirement assuming no FMI offset;
Eligible FMI offset equals:
0.75 * EL if estimated FMI equals or exceeds the expected 12-month loss amount
plus two standard deviations of the annualized loss rate, or
zero otherwise;
EL denotes expected loss (EL = EAD * PD * LGD);
FMI denotes future margin income;
EAD denotes exposure at default;
PD denotes probability of default; and
LGD denotes loss given default.
If eligible FMI did not exceed the required minimum, then recognition of eligible FMI
would be disallowed.
The Agencies are interested in views on whether partial recognition of FMI
should be permitted in cases where the amount of eligible FMI fails to meet the
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required minimum. The Agencies are also interested in views on the level of
portfolio segmentation at which it would be appropriate to perform the FMI
calculation. Would a requirement that FMI eligibility calculations be performed
separately for each portfolio segment effectively allow FMI to offset EL capital
requirements for QRE exposures?
The following table depicts a range of representative capital requirements (K) for QREs
based on these formulas. In each case, it is assumed that the maximum offset for eligible FMI
has been applied. The LGD is assumed to equal 90 percent, consistent with recovery rates for
credit card portfolios. The table shows capital requirements with recognition of FMI and without
recognition of FMI but using the same formula in other respects. As PDs increase, the
proportion of total required capital held against EL after deducting the 75 percent offset rises at
an increasing rate and the proportion held against UL declines at an increasing rate. Offsets from
EL, as considered in this ANPR, would therefore have a proportionally greater impact on
reducing required capital charges as default probabilities increase. For comparison purposes, the
current capital requirement on drawn credit card exposures is 8 percent and is zero for undrawn
credit lines.
Capital Requirement (in percentage points)
PD
0.05
0.10
0.25
0.50
1.00
2.00
5.00
10.0
20.0
With FMI
Capital 8%
0.68
1.17
2.24
3.44
4.87
6.21
7.89
11.12
17.23
Without FMI
Capital 8%
0.72
1.23
2.41
3.78
5.55
7.56
11.27
17.87
30.73
Subject to the same qualifications mentioned earlier, the QIS3 results estimated an
increase in capital requirements for QRE of about 16 percent.
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Other retail
The third and final sub-category of retail A-IRB exposures is other retail. This subcategory encompasses a wide variety of different exposures including auto loans, student loans,
consumer installment loans, and some SME loans. Two steps would be required to calculate the
A-IRB capital requirement for other retail exposures: (1) calculating the relevant asset
correlation parameter, and (2) calculating the capital requirement. Both of these steps would be
done separately for each portfolio segment included within the other retail sub-category.
As for wholesale exposures and QREs, it would be assumed that the asset correlation for
other retail exposures declines as PD rises. In the case of other retail exposures, the asset
correlation parameter approaches an upper bound value of 17 percent for very low PD values and
approaches a lower bound value of 2 percent for very high PD values. The specific formula for
determining the asset correlation for other retail exposures is as follows:
R = 0.02 * (1 – EXP(-35 * PD)) + 0.17 * [1 – (1 - EXP(-35 * PD))]
Where
R denotes asset correlation;
EXP denotes the natural exponential function; and
PD denotes probability of default.
The second step in the A-IRB capital calculation for other retail exposures would be the
calculation of the capital requirement (K). The specific formula to calculate this amount is as
follows:
K = EAD * LGD * N[(1 – R)^-0.5 * G(PD) + (R / (1 – R))^0.5 * G(0.999)]
Where
K denotes the capital requirement;
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EAD denotes exposure at default;
LGD denotes loss given default;
PD denotes probability of default;
N(x) denotes the standard normal cumulative distribution function;
G(x) denotes the inverse of the standard normal cumulative distribution function; and
R denotes asset correlation.
The following table depicts a range of representative capital requirements (K) for other
retail exposures based on this formula. Three different LGD assumptions are shown: 25 percent,
50 percent, and 75 percent, in order to depict a range of potential outcomes depending on the
characteristics of the underlying retail exposure. For comparison purposes, the current capital
requirement on most of the exposures likely to be included in the other retail sub-category is 8
percent.
Capital Requirements (in percentage points)
PD
0.05 percent
0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
20.00 percent
LGD
50 percent
0.66
1.11
2.13
3.28
4.70
6.15
7.87
10.48
17.10
25 percent
0.33
0.56
1.06
1.64
2.35
3.08
3.94
5.24
8.55
75 percent
0.99
1.67
3.19
4.92
7.05
9.23
11.81
15.73
25.64
Subject to the qualifications described earlier, QIS3 estimated a 25 percent reduction in
risk-based capital requirements for the other retail category.
The Agencies are seeking comment on the retail A-IRB capital formulas and the
resulting capital requirements, including the specific issues mentioned. Are there
particular retail product lines or retail activities for which the resulting A-IRB
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capital requirements would not be appropriate, either because of a misalignment
with underlying risks or because of other potential consequences?
A-IRB: Other Considerations
As described earlier, the A-IRB capital requirement includes components to cover both
EL and UL. Because banking organizations have other resources to cover expected losses, the
Agencies proposes to recognize certain of these measures as potential offsets to the A-IRB
capital requirement, subject to the limitations set forth below. The use of eligible FMI for QREs
is one such potential mechanism that has already been discussed.
Loan loss reserves
A second important mechanism involves the allowance for loan and lease losses (ALLL),
also referred to as general loan loss reserves. Under the general risk-based capital rules, an
amount of the ALLL is eligible for inclusion as an element of Tier 2 capital, up to a limit equal
to 1.25 percent of gross risk-weighted assets. Loan loss reserves above this limit are deducted
from risk-weighted assets, on a dollar-for-dollar basis. The New Accord proposes to retain the
1.25 percent limit on the eligibility of loan loss reserves as an element of Tier 2 capital.
However, the proposal also contains, and the Agencies are proposing for comment, a feature that
would allow the amount of the ALLL (net of associated deferred tax) above this 1.25 percent
limit to be used to offset the EL portion of A-IRB capital requirements in certain circumstances.
The offset would be limited to that amount of EL that exceeds the 1.25 percent limit.
For example, if the 1.25 percent limit equals $100, the ALLL equals $125, and the EL portion of
the A-IRB capital requirement equals $110, then $10 of the capital requirement may be directly
offset ($110 - $100). The additional amount of the ALLL not included in Tier 2 capital and not
included as a direct offset against the A-IRB capital requirement ($125 - $110 = $15 in the
example) would continue to be deducted from risk-weighted assets.
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It is important to recognize that this treatment would likely result in a significantly more
favorable treatment of such excess ALLL amounts than simply deducting them from riskweighted assets. Under the proposal, banking organizations would be allowed to multiply the
eligible excess ALLL by a factor of 12.5 because the minimum total capital requirement is 8
percent of risk-weighted assets. In effect, this treatment is 12.5 times more favorable than the
general risk-based capital rules, which allow only a deduction against risk-weighted assets on a
dollar-for-dollar basis. In addition, it is important to note that a dollar-for-dollar offset against
the A-IRB capital requirement is also more favorable than the inclusion of ALLL below the 1.25
percent limit in Tier 2 capital, since the latter has no impact on Tier 1 capital ratios, while the
former does.
The Agencies recognize the existence of various issues in regard to the proposed
treatment of ALLL amounts in excess of the 1.25 percent limit and are interested
in views on these subjects, as well as related issues concerning the incorporation
of expected losses in the A-IRB framework and the treatment of the ALLL
generally. Specifically, the Agencies invite comment on the domestic competitive
impact of the potential difference in the treatment of reserves described.
Another issue the Agencies wish to highlight is the inclusion within the New Accord of
the ability for banking organizations to make use of “general specific” provisions as a direct
offset against EL capital requirements. Such provisions are not specific to particular exposures
but are specific to particular categories of exposures and are not allowed as an element of Tier 2
capital. While several other countries make use of such provisions, the Agencies do not believe
existing elements of the ALLL in the United States qualify for such treatment.
The Agencies seek views on this issue, including whether the proposed U.S.
treatment has significant competitive implications. Feedback also is sought on
whether there is an inconsistency in the treatment of general specific provisions
(all of which may be used as an offset against the EL portion of the A-IRB capital
requirement) in comparison to the treatment of the ALLL (for which only those
amounts of general reserves exceeding the 1.25 percent limit may be used to offset
the EL capital charge).
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Charge-offs
Another potential offset to the EL portion of the A-IRB capital requirements is the use of
partial charge-offs, where a portion of an individual exposure is written off. Given the A-IRB
definition of default, a partial charge-off would cause an exposure to be classified as a defaulted
exposure (that is, PD=100%), in which case the A-IRB capital formulas ensure that the resulting
capital requirement on the defaulted exposure is equal to EAD * LGD, where EAD is defined as
the gross exposure amount prior to the partial charge-off. All of this capital requirement can be
considered to be covering EL.
The New Accord proposes that for such partially charged off exposures, the banking
organization be allowed to use the amount of the partial charge-off to offset the EL component of
that asset’s capital charge on a dollar-for-dollar basis. In addition, to the extent that the partial
charge-off on a defaulted exposure exceeds the EL capital charge on that exposure, the amount
of this surplus could be used to offset the EL capital charges on other defaulted assets in the
same portfolio (for example, corporates, banks, residential mortgages, etc.), but not for any other
purpose.
An implication of the New Accord is that if a defaulted loan’s charge-off were at least
equal to its expected loss, no additional capital requirement would be incurred on that exposure.
For example, consider a $100 exposure having an LGD of 40 percent, implying an expected loss
of $40, equal to the IRB capital charge. If the charge off were equal to $40, under the New
Accord approach, there would be no additional capital required against the resultant $60 net
position. The Agencies do not believe this is a prudent or acceptable outcome, since this position
is not riskless and a banking organization could be forced to recognize additional charge-offs if
the recoveries turn out to be less than expected.
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To preclude this possibility, the Agencies propose that, for defaulted exposures, the
A-IRB capital charge (inclusive of any EL offsets for charge-offs) be calculated as
the sum of (a) EAD*LGD less any charge-offs and (b) 8 percent of the carrying value of the loan
(i.e., the gross exposure amount (EAD) less any charge-offs)
Also, the charged off amounts in excess of the EAD*LGD product would not be
permitted to offset the EL capital requirements for other exposures. In effect, the proposed AIRB capital charge on a defaulted exposure adds a buffer for defaulted assets and results in a
floor equal to 8 percent against the remaining book value if the banking organization has taken a
charge-off equal to or greater than the EAD * LGD. Importantly, this treatment would not apply
to a defaulted exposure that has been restructured and where the obligor has not yet defaulted on
the restructured credit. Upon any restructuring, whether associated with a default or otherwise,
the A-IRB capital charge would be based on the EAD, PD, LGD, and M applicable to the
exposure after it has been restructured. The existence of any partial charge-offs associated with
the pre-restructured credit would affect the A-IRB capital charge on the restructured exposure
only through its impact on the post-restructured exposure’s EAD, PD, and/or LGD.
Purchased Receivables
This section describes the A-IRB treatment for wholesale and retail credit exposures
acquired from another institution (purchased receivables). The purchase of such exposures may
expose the acquiring banking organisation to potential losses from two sources: credit losses
attributable to defaults by the underlying receivables obligors, and losses attributable to dilution
of the underlying receivables.22 The total A-IRB capital requirement for purchased credit
22
Dilution refers to the possibility that the contractual amounts payable by the receivables obligors may be reduced
through future cash or non-cash credits to the accounts of these obligors. Examples include offsets or
allowances arising from returns of goods sold, disputes regarding product quality, possible debts of the
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exposures would be the sum of (a) a capital charge for credit risk, and (b) a separate capital
charge for dilution risk, when dilution is a material factor.
Capital charge for credit risk
The New Accord’s proposed treatment of purchased loans would treat a purchase
discount as equivalent to a partial charge-off, and for this reason it could imply a zero capital
charge against certain exposures. In general, a zero capital charge would emerge whenever the
difference between a loan’s face value and purchase price (the purchase discount) exceeded its
LGD, as might be the case with a secondary market purchase of deeply distressed debt. Again,
the Agencies believe that a zero capital charge in such a circumstance is unwarranted because the
position is not riskless.
The Agencies propose that for a credit exposure that is purchased or acquired from
another party, the A-IRB capital charge would be calculated as if the exposure was a direct loan
to the underlying obligor in the amount of the loan's carrying value to the purchasing bank (that
is, its amortized purchase price) with other attributes of the loan agreement (for example,
maturity, collateral, covenants) and, hence, LGD, remaining unchanged. This treatment would
apply regardless of whether the carrying value to the purchasing bank was less than, equal to, or
greater than the underlying instrument’s face value. Thus, if a loan having a principal amount
equal to $100 and associated PD and LGD of 10 percent and 40 percent was purchased for $80,
the capital charge against the purchased loan would be calculated as if that loan had an EAD
equal to $80, PD equal to 10 percent, and LGD equal to 40 percent.
In general, the same treatment would apply to pools of purchased receivables. However,
under the conditions detailed below, an alternative 'top-down' approach (similar to that used for
originator/seller to a receivables obligor, and any payment or promotional discounts offered by the
originator/seller (e.g., a credit for cash payments within 30 days).
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retail exposures) may be applied to pools of purchased receivables if the purchasing banking
organization can only estimate inputs to the capital function (PD, LGD, EAD, and M) on a pool
or aggregate basis.
Top-down method for pools of purchased receivables
Under the top-down approach, required capital would be determined using the
appropriate A-IRB capital formula (that is, for wholesale exposures, the wholesale capital
function, and for retail exposures, the appropriate retail capital function) in combination with
estimates of PD, LGD, EAD and M developed for pools of receivables. In estimating the pool
parameters, the banking organization first would determine EL for the purchased receivables
pool, expressed (in decimal form) at an annual rate relative to the amount currently owed to the
banking organization by the obligors in the receivables pool. The estimated EL would not take
into account any assumptions of recourse or guarantees from the seller or other parties. If the
banking organization can decompose EL into PD and LGD components, then it would do so and
use those components as inputs into the capital function. If the institution cannot decompose EL
then it would use the following split: PD would equal the estimated EL, and LGD would be 100
percent. Under the top-down approach, EAD would equal the carrying amount of the receivables
and for wholesale exposures, M would equal the exposure-weighted average effective maturity
of the receivables in the pool.23
Treatment of undrawn receivables purchase commitments
Capital charges against any undrawn portions of receivables purchase facilities ('undrawn
purchase commitments') also would be calculated using the top-down methodology. The EL
(and/or PD and LGD) parameters would be determined on the basis of the current pool of
23
If a banking organization can estimate the exposure-weighted average size of the pool it also would use the firmsize adjustment (S) in the wholesale framework.
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eligible receivables using the pool-level estimation methods described above. For undrawn
commitments under revolving purchase facilities, the New Accord specifies that the EAD would
be set at 75 percent of the undrawn line. This treatment reflects a concern that relevant historical
data for estimating such EADs reliably is not available at many banking organisations. For other
undrawn purchase commitments, EAD would be estimated by the bank providing the facility and
would be subject to the same operational standards that are applicable to undrawn wholesale
credit lines. The level of M associated with undrawn purchase commitments would be the
average effective maturity of receivables eligible for purchase from that seller, so long as the
facility contains effective arrangements for protecting the banking organisation against an
unanticipated deterioration. In the absence of such protections, the M for an undrawn
commitment would be calculated as the sum of (a) the longest-dated potential receivable under
the purchase agreement, and (b) the remaining maturity of the facility.
The Agencies seek comment on the proposed methods for calculating credit risk
capital charges for purchased exposures. Are the proposals reasonable and
practicable?
For committed revolving purchase facilities, is the assumption of a fixed 75
percent conversion factor for undrawn advances reasonable? Do banks have the
ability (including relevant data) to develop their own estimate of EADs for such
facilities? Should banks be permitted to employ their own estimated EADs,
subject to supervisory approval?
A banking organization may only use the top-down approach with approval of its primary
Federal supervisor. In addition, the purchased receivables would have to have been purchased
from unrelated, third party sellers and the organisation may not have originated the credit
exposures either directly or indirectly. The receivables must have been generated on an arm’s
length basis between the seller and the obligor (intercompany accounts receivable and
receivables subject to contra-accounts between firms that buy and sell to each other would not
qualify). Also, the receivables may not have a remaining maturity of greater than one year,
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unless they are fully secured. The agencies propose that the bottom-up method would have to be
used for receivables to any single obligor, or to any group of related obligors, that aggregate to
more than $1 million.
Capital Charge for Dilution Risk
When dilution is a material risk factor,24 purchased receivables would be subject to a
separate capital charge for that risk. The capital charge may be calculated at the level of
individual receivables and then aggregated, or, for a pool of receivables, at the level of the pool
as a whole. The capital charge for dilution risk would be calculated using the wholesale A-IRB
formula and the following parameters: EAD would be equal to the gross amount of receivable(s)
balance(s); LGD would be 100 percent; M would be the (exposure weighted-average) effective
maturity of the exposure(s); and PD would be the expected dilution loss rate, defined as total
expected dilution losses over the remaining term of the receivable(s) divided by EAD.25
Expected dilution losses would be computed on a stand-alone basis; that is, under the assumption
of no recourse or other support from the seller or third party guarantors.
The following table illustrates the dilution risk capital charges (per dollar of EAD)
implied by this approach for a hypothetical pool of purchased receivables having a remaining
maturity of one year or less. As can be seen, the proposal implies capital charges for dilution
risk that are many multiples of expected dilution losses.
Capital Requirements (in percentage points)
Expected
Dilution Loss
Rate
0.05 percent
24
25
Dilution Risk Capital
Charge
(per dollar of EAD,
percent)
2.05
If dilution risk is immaterial there would be no additional capital charge.
If the remaining term exceeds one year, the expected dilution loss rate would be specified at an annual rate.
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0.10 percent
0.25 percent
0.50 percent
1.00 percent
2.00 percent
5.00 percent
10.00 percent
3.42
6.41
9.77
14.03
19.03
28.45
41.24
The Agencies seek comment on the proposed methods for calculating dilution risk
capital requirements. Does this methodology produce capital charges for dilution
risk that seem reasonable in light of available historical evidence? Is the
corporate A-IRB capital formula appropriate for computing capital charges for
dilution risk?
In particular, is it reasonable to attribute the same asset correlations to dilution
risk as are used in quantifying the credit risks of corporate exposures within the
A-IRB framework? Are there alternative method(s) for determining capital
charges for dilution risk that would be superior to that set forth above?
Minimum requirements
The Agencies propose to apply standards for the estimation of risk parameters and
expected dilution losses and for the control and risk management systems associated with
purchased receivables programs that are consistent with the general guidance contained in the
New Accord. These standards will aim to ensure that risk parameter and expected dilution loss
estimates are reliable and consistent over time, and reflect all relevant information that is
available to the acquiring bank. The minimum operational requirements are intended to ensure
that the acquiring bank has a valid legal claim to cash proceeds generated by the exposures pool,
that the pool and cash proceeds are closely monitored and controlled, and that systems are in
place to identify and address seller, servicer, and other potential risks. A more detailed
discussion of these will be provided when the Agencies release draft examination guidance
dealing with purchased receivables programs.
The Agencies seek comment on the appropriate eligibility requirements for using
the top-down method. Are the proposed eligibility requirements, including the $1
million limit for any single obligor, reasonable and sufficient?
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The Agencies seek comment on the appropriate requirements for estimating
expected dilution losses. Is the guidance set forth in the New Accord reasonable
and sufficient?
Risk mitigation
For purposes of reducing the capital charges for credit risk or dilution risk with respect to
purchased receivables, purchase discounts, guarantees, and other risk mitigants may be
recognized through the same framework used elsewhere in the A-IRB approach.
Credit Risk Mitigation Techniques
The New Accord takes account of the risk-mitigating effects of both financial and
nonfinancial collateral, as well as guarantees, including credit derivatives. For these risk
mitigants to be recognized for regulatory capital purposes, the banking organization must have in
place operational procedures and risk management processes that ensure that all documentation
used in collateralizing or guaranteeing a transaction is binding on all parties and legally
enforceable in all relevant jurisdictions. The banking organization must have conducted
sufficient legal review to verify this conclusion, must have a well-founded legal basis for the
conclusion, and must reconduct such a review as necessary to ensure continuing enforceability.
Adjusting LGD for the effects of collateral
A banking organization would be able to take into account the risk-mitigating effect of
collateral in its internal estimates of LGD, provided the organization has established internal
requirements for collateral management, operational procedures, legal certainty, and risk
management processes that ensure that:
1) the legal mechanism under which the collateral is pledged or transferred ensures that
the banking organization has the right to liquidate or take legal possession of the
collateral in a timely manner in the event of the default, insolvency, or bankruptcy (or
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other defined credit event) of the obligor and, where applicable, the custodian holding
the collateral;
2) the banking organization has taken all steps necessary to fulfill legal requirements to
secure the organization’s interest in the collateral so that it has and maintains an
enforceable security interest;
3) the banking organization has clear and robust procedures for the timely liquidation of
collateral to ensure observation of any legal conditions required for declaring the
default of the borrower and prompt liquidation of the collateral in the event of default;
4) the banking organization has established procedures and practices for (i)
conservatively estimating, on a regular ongoing basis, the market value of the
collateral, taking into account factors that could affect that value (for example, the
liquidity of the market for the collateral and obsolescence or deterioration of the
collateral), and (ii) where applicable, for periodically verifying the collateral (for
example, through physical inspection of collateral such as inventory and equipment);
and
5) the banking organization has in place systems for requesting and receiving promptly
additional collateral for transactions whose terms require maintenance of collateral
values at specified thresholds.
In reflecting collateral in the LGD estimate, the banking organization would need to
consider the extent of any dependence between the risk of the borrower and that of the collateral
or collateral provider. The banking organization’s assessment of LGD would have to address in
a conservative way any significant degrees of dependence, as well as any currency mismatch
between the underlying obligation and the collateral. The LGD estimates would have to be
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grounded in historical recovery rates on the collateral and could not be based solely upon the
collateral’s estimated market value.
Repo-style transactions subject to master netting agreements
Repo-style transactions include reverse repurchase agreements and repurchase
agreements and securities lending and borrowing transactions, including those executed on an
indemnified agency basis.26 Many of these transactions are conducted under a bilateral master
netting agreement or equivalent arrangement. The effects of netting arrangements generally
would be recognized where the banking organization takes into account the risk-mitigating effect
of collateral through an adjustment to EAD. To qualify for the EAD adjustment treatment, the
repo-style transaction would have to be marked-to-market daily and be subject to a daily margin
maintenance requirement. Further, the repo-style transaction would have to be documented
under a qualifying master netting agreement that would have to:
1) provide the non-defaulting party the right to terminate and close out promptly all
transactions under the agreement upon an event of default, including in the event of
insolvency or bankruptcy of the counterparty;
2) provide for the netting of gains and losses on transactions (including the value of any
collateral) terminated and closed out under the agreement so that a single net amount
is owed by one party to the other;
3) allow for the prompt liquidation or setoff of collateral upon the occurrence of an
event of default; and
26
Some banking organizations, particularly those that are custodians, lend, as agent, their customers’ securities on a
collateralized basis. Typically, the agent banking organization indemnifies the customer against risk of loss in
the event the borrowing counterparty defaults. Where such indemnities are extended, the agent banking
organization has the same risks it would have if it had entered into the transaction as principal.
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4) be, together with the rights arising from the provisions required in 1) to 3) above,
legally enforceable in each relevant jurisdiction upon the occurrence of an event of
default and regardless of the counterparty’s insolvency or bankruptcy.
Where a banking organization’s repo-style transactions do not meet these requirements, it
would not be able to use the EAD adjustment method. Rather, for each individual repo-style
transaction it would estimate an LGD that takes into account the collateral received. It would
use the notional amount of the transaction for EAD; it would not take into account netting effects
for purposes of determining either EAD or LGD.
The method for determining EAD for repo-style transactions, described below, is
essentially the determination of an unsecured loan equivalent exposure amount to the
counterparty. Thus, no collateral effects for these transactions would be recognized through
LGD; rather, the applicable LGD would be the one the banking organization would estimate for
an unsecured exposure to the counterparty.
To determine EAD, the banking organization would add together its current exposure to
the counterparty under the master netting arrangement and a measure for PFE to the counterparty
under the master netting arrangement. The current exposure would be the sum of the market
values of all securities and cash lent, sold subject to repurchase, or pledged as collateral to the
counterparty under the master netting agreement, less the sum of the market values of all
securities and cash lent, sold subject to repurchase, or pledged as collateral by the counterparty.
The PFE calculation would be based on the market price volatilities of the securities delivered to,
and the securities received from, the counterparty, as well as any foreign exchange rate
volatilities associated with any cash or securities delivered or received.
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Banking organizations would use a VaR-type measure for determining PFE for repo-style
transactions subject to master netting agreements. Banking organizations would be required to
use a 99th percentile, one-tailed confidence interval for a five-day holding period using a
minimum one-year historical observation period of price data. Banking organizations would
have to update their data sets no less frequently than once every three months and reassess them
whenever market prices are subject to material changes. The illiquidity of lower-quality
instruments would have to be taken into account through an upward adjustment in the holding
period where the five-day holding period would be inappropriate given the instrument’s
liquidity. No particular model would be prescribed for the VaR-based measure, but the model
would have to capture all material risks for included transactions.
Banking organizations using a VaR-based approach to measuring PFE would be
permitted to take into account correlations in the price volatilities among instruments delivered
to the counterparty and among instruments received from the counterparty, as well as between
the two sets of instruments. The VaR-based approach for calculating PFE for repo-style
transactions would be available to all banking organizations that received supervisory approval
for an internal market risk model under the market risk capital rules. Other banking
organizations could apply separately for supervisory approval to use their internal VaR models
for calculation of PFE for repo-style transactions.
A banking organization would use the following formula to determine EAD for each
counterparty with which it has a master netting agreement for repo-style transactions.
EAD = max {0, [(Σ E - ΣC) + (VaR output from internal market risk model x multiplier)]}
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Where:
E denotes the current value of the exposure (that is, all securities and cash delivered to
the counterparty); and
C denotes the current value of the collateral received (that is, all securities and cash
received from the counterparty).
The multiplier in the above formula would be determined based on the results of the
banking organization’s backtesting of the VaR output. To backtest the output, the banking
organization would be required to identify on an annual basis twenty counterparties that include
the ten largest as determined by the banking organization’s own exposure measurement approach
and ten others selected at random. For each day and for each of the twenty counterparties, the
banking organization would compare the previous day’s VaR estimate for the counterparty
portfolio to the change in the current exposure of the previous day’s portfolio. This change
represents the difference between the net value of the previous day’s portfolio using today’s
market prices and the net value of that portfolio using the previous day’s market prices. Where
this difference exceeds the previous day’s VaR estimate, an exception would have occurred.
At the end of each quarter, the banking organization would identify the number of
exceptions it has observed for its twenty counterparties over the most recent 250 business days,
that is, the number of exceptions in the most recent 5000 observations. Depending on the
number of exceptions, the output of the VaR model would be scaled up using a multiplier as
provided in the table below.
Zone
Green Zone
Yellow Zone
Number of Exceptions
0-99
100-119
120-139
140-159
160-179
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None (=1)
2.0
2.2
2.4
2.6
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180-199
200 or more
Red Zone
2.8
3.0
The Agencies seek comments on the methods set forth above for determining
EAD, as well as on the proposed backtesting regime and possible alternatives
banking organizations might find more consistent with their internal risk
management processes for these transactions. The Agencies also request
comment on whether banking organizations should be permitted to use the
standard supervisory haircuts or own estimates haircuts methodologies that are
proposed in the New Accord.
Guarantees and credit derivatives
The Agencies are proposing that banking organizations reflect the credit risk mitigating
effects of guarantees and credit derivatives through adjusting the PD or the LGD estimate (but
not both) of the underlying obligation that is protected. The banking organization would be
required to assign the borrower and guarantor to an internal rating in accordance with the
minimum requirements set out for unguaranteed (unhedged) exposures, both prior to the
adjustments and on an ongoing basis. The organization also would be required to monitor
regularly the guarantor’s condition and ability and willingness to honor its obligation. For
guarantees on retail exposures, these requirements would also apply to the assignment of an
exposure to a pool and the estimation of the PD of the pool.
For purposes of reflecting the effect of guarantees in regulatory capital requirements, the
Agencies are proposing that a banking organization have clearly specified criteria for adjusting
internal ratings or LGD estimates -- or, in the case of retail exposures, for allocating exposures to
pools to reflect use of guarantees and credit derivatives -- that take account of all relevant
information. The adjustment criteria would have to require a banking organization to (i) meet all
minimum requirements for an unhedged exposure when assigning borrower or facility ratings to
guaranteed/hedged exposures; (ii) be plausible and intuitive; (iii) consider the guarantor’s ability
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and willingness to perform under the guarantee; (iv) consider the extent to which the guarantor’s
ability and willingness to perform and the borrower’s ability to repay may be correlated (that is,
the degree of wrong-way risk); and (v) consider the payout structure of the credit protection and
conservatively assess its effect on the level and timing of recoveries. The banking organization
also would be required to consider any residual risk to the borrower that may remain -- for
example, a currency mismatch between the credit protection and the underlying exposure.
Banking organizations would be required to make adjustments to alter PD or LGD
estimates in a consistent way for a given type of guarantee or credit derivative. In all cases, the
adjusted risk weight for the hedged obligation could not be less than the risk weight associated
with a comparable direct exposure on the protection provider. As a practical matter, this
guarantor risk weight floor on the risk weight of the hedged obligation would require a banking
organization first to determine the risk weight on the hedged obligation using the adjustment it
has made to the PD or LGD estimate to reflect the hedge. The banking organization would then
compare that risk weight to the risk weight assigned to a direct obligation of the guarantor. The
higher of the two risk weights would then be used to determine the risk-weighted asset amount of
the hedged obligation.
Notwithstanding the guarantor risk weight floor, the proposed approach gives institutions
a great deal of flexibility in their methodology for recognizing the risk-reducing effects of
guarantees and credit derivatives. At the same time, the approach does not differentiate between
various types of guarantee structures, which may have widely varying characteristics, that a
banking organization may use. For example, a company to company guarantee, such as a
company’s guarantee of an affiliate or a supplier, is fundamentally different from a guarantee
obtained from an unrelated third party that is in the business of extending financial guarantees.
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Examples of the latter type of guarantee include standby letters of credit, financial guarantee
insurance, and credit derivatives. These products tend to be standardized across institutions and,
thus, arguably should be recognized for capital purposes in a consistent fashion across
institutions. The problem of inconsistent treatment could be exacerbated in the case of
protection in the form of credit derivatives, which are tradable and which further can be
distinguished by their characteristic of allowing a banking organization to have a recovery claim
on two parties, the obligor and the counterparty, rather than just one.
Industry comment is sought on whether a more uniform method of adjusting PD
or LGD estimates should be adopted for various types of guarantees to minimize
inconsistencies in treatment across institutions and, if so, views on what methods
would best reflect industry practices. In this regard, the Agencies would be
particularly interested in information on how banking organizations are currently
treating various forms of guarantees within their economic capital allocation
systems and the methods used to adjust PD, LGD, EAD, and any combination
thereof.
Double default effects
The Agencies are proposing that neither the banking organization’s criteria nor rating
process for guaranteed/hedged exposures be allowed to take into account so-called “double
default” effects, that is, joint probability of default of the borrower and guarantor. As a result of
not being able to recognize double default probabilities, the adjusted risk weight for the hedged
obligation could not be less than the risk weight associated with a direct exposure on the
protection provider. The Agencies are seeking comment on the proposed nonrecognition of
double default effects. On June 10, 2003, the Federal Reserve released a white paper entitled,
Treatment of Double Default and Double Recovery Effects for Hedged Exposures Under Pillar I
of the Proposed New Basel Capital Accord, discussing this issue. Commenters are encouraged
to take into account the white paper in formulating their responses to the ANPR.
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The Agencies also are interested in obtaining commenters’ views on alternative methods
for giving recognition to double default effects in a manner that is operationally feasible and
consistent with safety and soundness. With regard to the latter, commenters are requested to
bear in mind the concerns outlined in the double default white paper, particularly in connection
with concentrations, wrong-way risk (especially in stress periods), and the potential for
regulatory capital arbitrage. In this regard, information is solicited on how banking
organizations consider double default effects on credit protection arrangements in their economic
capital calculations and for which types of credit protection arrangements they consider these
effects.
Requirements for recognized guarantees and credit derivatives
The Agencies are not proposing any restrictions on the types of eligible guarantors or
credit derivative providers. Rather, a banking organization would be required to have clearly
specified criteria for those guarantors they will accept as eligible for regulatory capital purposes.
It is proposed that guarantees and credit derivatives recognized for regulatory capital purposes:
(1) be required to represent a direct claim on the protection provider; (2) explicitly reference
specific exposures or classes thereof; (3) be evidenced in writing through a contract that is
irrevocable by the guarantor; (4) not have a clause that would (i) allow the protection provider
unilaterally to cancel the credit protection (other than in the event of nonpayment or other default
by the protection buying banking organization) or (ii) increase the effective cost of credit
protection as the credit quality of the hedged exposure deteriorates; (5) be in force until the
underlying obligation is satisfied in full (to the amount and tenor of the guarantee); and (6) be
legally enforceable against the guarantor in a jurisdiction where the guarantor has assets to attach
and enforce a judgement.
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The Agencies view the risk mitigating benefits of conditional guarantees -- that is,
guarantees that prescribe certain conditions under which the guarantor would not be obliged to
perform -- as particularly difficult to quantify. The Agencies are proposing that as a general
matter such guarantees would not be recognized under the A-IRB approach. In certain
circumstances, however, conditional guarantees could be recognized where the banking
organization can demonstrate that its assignment criteria fully reflect the reduction in credit risk
mitigation arising from the conditionality and that the guarantee provides a meaningful degree of
credit protection.
Additional requirements for recognized credit derivatives
The Agencies are proposing that credit derivatives, whether in the form of credit default
swaps or total return swaps, recognized for A-IRB risk-based capital purposes meet additional
criteria. The credit events specified by the contracting parties would be required to include at a
minimum: (i) failure to pay amounts due under the terms of the underlying obligation; (ii)
bankruptcy, insolvency, or inability of the obligor to pay its debt; and (iii) restructuring of the
underlying obligation that involves forgiveness or postponement of principal, interest, or fees
that results in a credit loss.
With regard to restructuring events, the Agencies note that the New Accord suggests that
a banking organization may not need to include restructuring credit events when it has complete
control over the decision of whether or not there will be a restructuring of the underlying
obligation. This would occur, for example, where the hedged obligation requires unanimous
consent of the creditors for a restructuring. The Agencies have concerns that this approach could
have the incidental effect of dictating terms in underlying obligations in ways that over time
could diverge from creditors’ business needs. The Agencies also question whether such clauses
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actually eliminate restructuring risk on the underlying obligation, particularly as many credit
derivatives hedge only a small portion of a banking organization’s exposure to the underlying
obligation.
The Agencies invite comment on this issue, as well as consideration of an
alternative approach whereby the notional amount of a credit derivative that does
not include restructuring as a credit event would be discounted. Comment is
sought on the appropriate level of discount and whether the level of discount
should vary on the basis of, for example, whether the underlying obligor has
publicly outstanding rated debt or whether the underlying is an entity whose
obligations have a relatively high likelihood of restructuring relative to default
(for example, a sovereign or PSE). Another alternative that commenters may
wish to discuss is elimination of the restructuring requirement for credit
derivatives with a maturity that is considerably longer -- for example, two years -than that of the hedged obligation.
Consistent with the New Accord, the Agencies are proposing not to recognize credit
protection on total return swaps where the banking organization records net payments received
on the swap as net income, but does not record offsetting deterioration in the value of the hedged
obligation either through reduction in fair value or by an addition to reserves. The Agencies are
considering imposing similar non-recognition on credit default swaps where mark-to-market
gains in value are recognized in income and, thus, in Tier 1 capital, but no offsetting
deterioration in the hedged obligation is recorded. (This situation generally would not arise
where both the hedged obligation and the credit default swap are recorded in the banking book
because under U.S. GAAP increases in the swap’s value are recorded in the Other
Comprehensive Income account, which is not included in regulatory capital.)
Comment is sought on this matter, as well as on the possible alternative treatment
of recognizing the hedge in these two cases for regulatory capital purposes but
requiring that mark-to-market gains on the credit derivative that have been taken
into income be deducted from Tier 1 capital.
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Mismatches in credit derivatives between reference and underlying obligations
The Agencies are proposing to recognize credit derivative hedges for A-IRB capital
purposes only where the reference obligation on which the protection is based is the same as the
underlying obligation except where: 1) the reference obligation ranks pari passu with or is more
junior than the underlying obligation, and 2) the underlying obligation and reference obligation
share the same obligor and legally enforceable cross-default or cross-acceleration clauses are in
place.
Treatment of maturity mismatch
The Agencies are proposing to recognize on a discounted basis guarantees and credit
derivatives that have a shorter maturity than the hedged obligation. A hedge with less than oneyear residual maturity that does not have a matching maturity to the underlying obligation,
however, would not be recognized. The formula for discounting the amount of a maturitymismatched hedge that is recognized is proposed as follows:
Pa = P * t/T
Where:
Pa denotes the value of the credit protection adjusted for maturity mismatch;
P denotes the amount of the credit protection;
t denotes the lesser of T and the residual maturity of the hedge arrangement, expressed in
years; and
T denotes the lesser of 5 and the residual maturity of the underlying obligation, expressed
in years.
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The Agencies have concerns that the proposed formulation does not appropriately
reflect distinctions between bullet and amortizing underlying obligations.
Comment is sought on the best way of making such a distinction, as well as more
generally on alternative methods for dealing with the reduced credit risk
coverage that results from a maturity mismatch.
Treatment of counterparty risk for credit derivative contracts
The Agencies are proposing that the EAD for derivative contracts included in either the
banking book or trading book be determined in accordance with the rules for calculating the
credit equivalent amount for such contracts set forth under the general risk-based capital rules.
The Agencies are proposing to include in the types of derivative contracts covered under these
rules credit derivative contracts recorded in the trading book. Accordingly, where a banking
organization buys or sells a credit derivative through its trading book, a counterparty credit risk
capital charge would be imposed based on the replacement cost plus the following add-on factors
for PFE:
Total Return or Credit
Default Swap
Qualifying Reference
Obligation*
Non-Qualifying Reference
Obligation*
Protection Buyer
Protection Seller
5%
5%**
10%
10%**
* The definition of qualifying would be the same as for the “qualifying” category for the treatment of specific risk
for covered debt positions under the market risk capital rules
** The protection seller of a credit default swap would only be subject to the add-on factor where the contract is
subject to close-out upon the insolvency of the protection buyer while the underlying obligor is still solvent.
The Agencies also are considering applying a counterparty credit risk charge on all credit
derivatives that are marked-to-market, including those recorded in the banking book. Such a
treatment would promote consistency with other OTC derivatives, which are assessed the same
counterparty credit risk charge regardless of where they are booked.
Further, the Agencies note that, if credit derivatives booked in the banking book are not
assessed a counterparty credit charge, banking organizations would be required to exclude these
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derivatives from the net current exposure of their other derivative exposures to a counterparty for
purposes of determining regulatory capital requirements. On balance, the Agencies believe a
better approach would be to align the net derivative exposure used for capital purposes with that
used for internal risk management purposes to manage counterparty risk exposure and
collateralization thereof. This approach would suggest imposing a counterparty risk charge on
all credit derivative exposures that are marked to market, regardless of where they are booked.
The Agencies are seeking industry views on the PFE add-ons proposed above and
their applicability. Comment is also sought on whether different add-ons should
apply for different remaining maturity buckets for credit derivatives and, if so,
views on the appropriate percentage amounts for the add-ons in each bucket.
Equity Exposures
Banking organizations using an A-IRB approach for any credit exposure would be
required to use an internal models market-based approach to calculate regulatory capital charges
for equity exposures. Minimum quantitative and qualitative requirements for using an internal
model would have to be met on an ongoing basis. A banking organization that is transitioning
into an internal models approach to equity exposures or that fails to demonstrate compliance with
the minimum operational requirements for using an internal models approach to equity exposures
would be required to develop a plan for compliance, obtain approval of the plan from its primary
Federal supervisor, and implement the plan in a timely fashion. In addition, a banking
organization’s primary Federal supervisor would have the authority to impose additional
operational requirements on a case-by-case basis. Until it is fully compliant with all applicable
requirements, the banking organization would apply a minimum 300 percent risk weight to all
publicly traded equity investments (that is, equity investments that are traded on a nationally
recognized securities exchange) and a minimum 400 percent risk weight to all other equity
investments.
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Positions covered
All equity exposures held in the banking book, along with any equity exposures in the
trading book that are not currently subject to a market risk capital charge, would be subject to the
A-IRB approach for equity exposures. In general, equity exposures are distinguished from other
types of exposures based on the economic substance of the exposure. Equity exposures would
include both direct and indirect ownership interests, whether voting or non-voting, in the assets
or income of a commercial enterprise or financial institution that are not consolidated or
deducted for regulatory capital purposes. Holdings in funds containing both equity investments
and non-equity investments would be treated either as a single investment based on the majority
of the fund’s holdings or, where possible, as separate and distinct investments in the fund’s
component holdings based on a “look-through approach” (that is, based on the individual
component holdings).
An instrument generally would be considered to be an equity exposure if it (1) would
qualify as Tier 1 capital under the general risk-based capital rules if issued by a banking
organization; (2) is irredeemable in the sense that the return of invested funds can be achieved
only by the sale of the investment or sale of the rights to the investment or in the event of the
liquidation of the issuer; (3) conveys a residual claim on the assets or income of the issuer; and
(4) does not embody an obligation on the part of the issuer.
An instrument that embodies an obligation of the issuer is considered an equity
exposure if the instrument meets any of the following conditions: (1) the issuer may defer
indefinitely the settlement of the obligation; (2) the obligation requires, or permits at the issuer’s
discretion, settlement by the issuance of a fixed number of the issuer’s equity interests; (3) the
obligation requires, or permits at the issuer’s discretion, settlement by the issuance of a variable
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number of the issuer’s equity interests, and all things being equal, any change in the value of the
obligation is attributable to, comparable to, and in the same direction as, the change in value of a
fixed number of the issuer’s equity shares; or (4) the holder has the option to require that the
obligation be settled by issuance of the issuer’s equity interests, unless the banking
organization’s primary Federal supervisor has opined in writing that the instrument should be
treated as a debt position.
Debt obligations and other securities, derivatives, or other instruments structured with
the intent of conveying the economic substance of equity ownership would be considered equity
exposures for purposes of the A-IRB capital requirements. For example, options and warrants on
equities and short positions in equity securities would be characterized as equity exposures. If a
debt instrument is convertible into equity at the option of the holder, it would be deemed equity
upon conversion. If such debt is convertible at the option of the issuer or automatically by the
terms of the instrument, it would be equity from inception. In addition, instruments with a return
directly linked to equities would be characterized as equity investments under most
circumstances. A banking organization’s primary Federal supervisor would have the discretion
to allow a debt characterization of such an equity-linked instrument, however, if the instrument is
directly hedged by an equity holding such that the net position does not involve material equity
risk to the holder. Equity instruments that are structured with the intent of conveying the
economic substance of debt holdings or securitization exposures would not be considered an
equity exposure. For example, some issuances of term preferred stock may be more
appropriately characterized as debt.
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In all cases, the banking organization’s primary Federal supervisor would have the
discretion to recharacterize debt holdings as equity exposures or equity holdings as debt or
securitization exposures for regulatory capital purposes.
The Agencies encourage comment on whether the definition of an equity exposure
is sufficiently clear to allow banking organizations to make an appropriate
determination as to the characterization of their assets.
Materiality
As noted above, a banking organization that is required or elects to use the A-IRB
approach for one credit portfolio would also use the A-IRB approach for all of its holdings,
including equity investments. However, if the aggregate equity holdings of a banking
organization are not material in amount, the organization would not be required to use the A-IRB
approach to equity exposures. For this purpose, a banking organization’s equity exposures
generally would be considered material if their aggregate carrying value, including holdings
subject to exclusions and transitional provisions (as described below), exceeds ten percent of the
organization’s Tier 1 and Tier 2 capital on average during the prior calendar year. To address
concentration concerns, however, the materiality threshold would be lowered to five percent of
the banking organization’s Tier 1 and Tier 2 capital if the organization’s equity portfolio consists
of less than ten individual holdings. Banking organizations would risk weight at 100 percent
equity exposures exempted from the A-IRB equity treatment under a materiality threshold.
Comment is sought on whether the materiality thresholds set forth above are appropriate.
Exclusions from the equity capital charge
Zero and low risk weight investments
The New Accord provides that national supervisors may exclude from the A-IRB
capital charge those equity exposures to entities whose debt obligations qualify for a zero risk
weight under the New Accord’s standardized approach for credit risk. Entities whose debt
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obligations qualify for a zero risk weight generally include (i) sovereigns rated AAA to AA-; (ii)
the BIS; (iii) the IMF; (iv) the European Central Bank; (v) the European Community; and (vi)
high-quality multilateral development banks (MDBs) with strong shareholder support.27 The
Agencies intend to exclude from the A-IRB equity capital charge equity investments in these
entities. Instead, these investments would be risk weighted at zero percent under the A-IRB
approach.
In addition, the Agencies are proposing to exempt from the A-IRB equity capital charge
investments in non-central government public-sector entities (PSEs) that are not traded publicly
and generally are held as a condition of membership. Examples of such holdings include stock
of a Federal Home Loan Bank or a Federal Reserve Bank. These investments would be riskweighted as they would be under the general risk-based capital rules -- 20 percent or zero
percent, respectively, in the example.
Comment is sought on whether other types of equity investments in PSEs should
be exempted from the capital charge on equity exposures, and if so, the
appropriate criteria for determining which PSEs would be exempted.
Nationally legislated programs
Under the New Accord, national supervisors may exclude from the A-IRB capital charge
on equity exposures certain equity exposures made under legislated programs that involve
government oversight and restrictions on the types or amounts of investments that may be made
(legislated program equity exposures). Under the New Accord, a banking organization would be
able to exclude from the A-IRB capital charge on equity exposures legislated program equity
exposures in an amount up to ten percent of a banking organization’s Tier 1 plus Tier 2 capital.
27
These are, at present, the World Bank group comprised of the International Bank for Reconstruction and
Development (IBRD) and the International Finance Corporation (IFC), the Asian Development Bank (ADB), the
African Development Bank (AfDB), the European Bank for Reconstruction and Development (EBRD), the
Inter-American Development Bank (IADB), the European Investment Bank (EIB), the Islamic Development
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The Agencies propose that equity investments by a banking organization in a small
business investment company (SBIC) under section 302(b) of the Small Business Investment Act
of 1958 would be legislated program equity exposures eligible for the exclusion from the A-IRB
equity capital charge in an amount up to ten percent of the banking organization’s Tier 1 plus
Tier 2 capital. A banking organization would be required to risk weight at 100 percent any
amounts of legislated program equity exposures that qualify for this exclusion from the A-IRB
equity capital charge.
The Agencies seek comment on what conditions might be appropriate for this
partial exclusion from the A-IRB equity capital charge. Such conditions could
include limitations on the size and types of businesses in which the banking
organization invests, geographical limitations, or maximum limitations on the size
of individual investments.
U.S. banking organizations also make investments in community and economic
development entities that promote the public welfare under 12 U.S.C. 24 (eleventh). These
investments receive favorable tax treatment and investment subsidies that make their risk and
return characteristics markedly different (and more favorable to investors) than equity
investments in general. Recognizing this more favorable risk-return structure and the importance
of these investments to promoting important public welfare goals, the Agencies are proposing the
exclusion of all CEDE investments from the A-IRB equity capital charge. Unlike the exclusion
for SBIC exposures, the exclusion of CEDE investments would not be subject to a percentage of
capital limit. All CEDE equity exposures would receive a 100 percent risk weight.
The Agencies seek comment on whether any conditions relating to the exclusion of
CEDE investments from the A-IRB equity capital charge would be appropriate.
These conditions could serve to limit the exclusion to investments in CEDEs that
meet specific public welfare goals or to limit the amount of CEDE investments
that would qualify for the exclusion from the A-IRB equity capital charge. The
Bank, the Nordic Investment Bank (NIB), the Caribbean Development Bank (CDB), and the Council of Europe
Development Bank (CEDB).
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Agencies also seek comment on whether any other classes of legislated program
equity exposures should be excluded from the A-IRB equity capital charge.
Grandfathered investments
Equity investments held as of the date of adoption of the final capital rule governing
equity holdings would be exempt from the A-IRB equity capital charge for a period of ten years
from that date. A banking organization would be required to risk weight these holdings during
the ten-year period at 100 percent. The investments that would be considered grandfathered
would be equal to the number of shares held as of the date of the final rule, plus any shares that
the holder acquires directly as a result of owning those shares, provided that any additional
shares do not increase the holder’s proportional ownership share in the company.
For example, if a banking organization owned 100 shares of a company on the date of
adoption of the final rule, and the issuer thereafter declared a pro rata stock dividend of five
percent, the entire post-dividend holdings of 105 shares would be exempt from the A-IRB equity
capital charge for a period of ten years from the date of the adoption of the final A-IRB capital
rule. However, if additional shares are acquired such that the holder’s proportional share of
ownership increases, the additional shares are not grandfathered. Thus, if a banking organization
owned 100 shares of a company on the date of adoption of the final rule and subsequently
acquired an additional 50 shares, the original 100 shares would be exempt from the A-IRB equity
capital charge for the ten-year period from the date of adoption of the final rule, but the
additional 50 shares would be immediately subject to the A-IRB equity capital charge.
Description of quantitative principles
The primary focus of the A-IRB approach to equity exposures is to assess capital based
on an internal estimate of loss under extreme market conditions, on an institution’s portfolio of
equity holdings or, in simpler forms, its individual equity investments. The methodology or
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methodologies used to compute the banking organization’s estimated loss should be those used
by the institution for internal risk management purposes. The model should be fully integrated
into the banking organization’s risk management infrastructure.
A banking organization’s use of internal models would be subject to supervisory approval
and ongoing review by the institution’s primary Federal supervisor. Given the unique nature of
equity portfolios and differences in modeling techniques, the supervisory model review process
would be, in many respects, institution-specific. The sophistication and nature of the modeling
technique used for a particular type of equity exposure should correspond to the banking
organization’s exposure, concentration in individual equity issues of that type, and the particular
risk of the holding (including any optionality). Institutions would have to use an internal model
that is appropriate for the risk characteristics and complexity of their equity portfolios. The
model would have to be able to capture adequately all of the material risks embodied in equity
returns, including both general market risk and idiosyncratic (that is, specific) risk of the
institution’s equity portfolio.
In their evaluations of institutions’ internal models, the Agencies would consider, among
other factors, (a) the nature of equity holdings, including the number and type of equities (for
example, public, private, long, short); (b) the risk characteristics and makeup of institutions’
portfolio holdings, including the extent to which publicly available price information is
obtainable on the exposures; and (c) the level and degree of concentration. Institutions with
equity portfolios containing holdings with values that are highly nonlinear in nature (for
example, equity derivatives or convertibles) would have to employ an internal model designed to
appropriately capture the risks associated with these instruments.
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The Agencies recognize that the type and sophistication of internal modeling systems will
vary across institutions due to differences in the nature and complexity of business lines in
general and equity exposures in particular. Although the Agencies intend to use a VaR
methodology as a benchmark for the internal model approach, the Agencies recognize that some
institutions employ models for internal risk management and capital allocation purposes that,
given the nature of their equity holdings, can be more risk-sensitive than some VaR models. For
example, some institutions employ rigorous historical scenario analysis and other techniques in
assessing the risk of their equity portfolios. It is not the Agencies’ intention to dictate the form
or operational details of banking organizations’ risk measurement and management practices for
their equity exposures. Accordingly, the Agencies do not expect to prescribe any particular type
of model for computing A-IRB capital charges for equity exposures.
For purposes of evaluating the A-IRB equity capital charges produced by a banking
organization’s selected methodology, the Agencies would expect to use as a benchmark a VaR
methodology using a 99.0 percent (one-tailed) confidence level of estimated maximum loss over
a quarterly time horizon using a long-term sample period. Moreover, A-IRB equity capital
charges would have to produce risk weights for equity exposures that are at least equal to a 200
percent risk weight for publicly traded equity exposures, and a 300 percent risk weight for all
other equity exposures.
VaR-based internal models must use a historical observation period that includes a
sufficient amount of data points to ensure statistically reliable and robust loss estimates relevant
to the long-term risk profile of the institution’s specific holdings. The data used to represent
return distributions should reflect the longest sample period for which data are available and
should meaningfully represent the risk profile of the banking organization’s specific equity
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holdings. The data sample should be long-term in nature and, at a minimum, should encompass
at least one complete equity market cycle relevant to the institution’s holdings, including both
increases and decreases in relevant equity values over a long-term data period. The data used
should be sufficient to provide conservative, statistically reliable, and robust loss estimates that
are not based purely on subjective or judgmental considerations.
The parameters and assumptions used in a VaR model must be subject to a rigorous and
comprehensive regime of stress-testing. Banking organizations utilizing VaR models would be
required to subject their internal model and estimation procedures, including volatility
computations, to either hypothetical or historical scenarios that reflect worst-case losses given
underlying positions in both public and private equities. At a minimum, banking organizations
that use a VaR model would be required to employ stress tests to provide information about the
effect of tail events beyond the level of confidence assumed in the internal models approach.
Banking organizations using non-VaR internal models that are based on stress tests or
scenario analyses would have to estimate losses under worst-case modeled scenarios. These
scenarios would have to reflect the composition of the organization’s equity portfolio and should
produce capital charges at least as large as those that would be required to be held against a
representative market index under a VaR approach. For example, for a portfolio consisting
primarily of publicly held equity securities that are actively traded, capital charges produced
using historical scenario analyses would have to be greater than or equal to capital charges
produced by a baseline VaR approach for a major index that is representative of the institution’s
holdings.
The measure of an equity exposure on which A-IRB capital requirements would be based
would be the value of the equity presented in the financial statements. For investments held at
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fair value, the exposure amount would be equal to the fair value presented in the balance sheet.
For investments held at the lower of cost or market value, the exposure amount would be equal
to the cost or market value presented in the balance sheet.
The loss estimate derived from the internal model would constitute the A-IRB capital
charge to be assessed against the equity exposure. The A-IRB equity capital charge would be
incorporated into an institution’s risk-based capital ratio through the calculation of risk-weighted
equivalent assets. To convert the A-IRB equity capital charge into risk-weighted equivalent
assets, a banking organization would multiply the capital charge by a factor of 12.5.
Consistent with the general risk-based capital rules, 45 percent of the positive change in
value held in the tax-adjusted separate component of equity – that is, 45 percent of revaluation
gains on available-for-sale (AFS) equity securities – would be includable in Tier 2 capital under
the A-IRB framework.
Comment is specifically sought on whether the measure of an equity exposure
under AFS accounting continues to be appropriate or whether a different rule for
the inclusion of revaluation gains should be adopted.
C. Supervisory Assessment of A-IRB Framework
A banking organization would have to satisfy all the A-IRB infrastructure requirements
and supervisory standards before it would be able to use the A-IRB approach for calculating
capital requirements for credit risk. This section describes key elements of the framework on
which the Agencies propose to base the A-IRB qualifying requirements for U.S. banking
organizations. The Agencies intend to provide more detailed implementation guidance in regard
to these issues for wholesale and retail exposures, as well as for equity and securitization
exposures. As noted earlier, draft guidance for corporate exposures that identifies associated
supervisory standards was published elsewhere in today’s Federal Register
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Overview of Supervisory Framework
Many of the supervisory standards are focused on requirements for a banking
organization’s internal risk rating system. Emphasis is placed on a banking organization’s ability
to rank order and quantify risk in a consistent, reliable and valid manner. In sum, a banking
organization’s internal risk rating system would have to provide for a meaningful differentiation
of the riskiness of borrowers, as well as the risks inherent in individual transactions. To ensure
the reliability of these estimates, internal risk rating systems would need to be subject to review
by independent control units. Data sources and estimation methods used by banking
organizations would need to be sufficiently robust to support the production of consistent
quantitative assessments of risk over time. Finally, to ensure that ratings are not derived solely
for regulatory capital purposes, internal risk rating systems and quantification methods would
need to form an integral part of the management of the institution, as outlined below.
It is important to emphasize that the Agencies believe that meeting the A-IRB
infrastructure requirements and supervisory standards will require significant efforts by banking
organizations. The A-IRB supervisory standards will effectively “raise the bar” in regard to
sound credit risk management practices.
Rating system design
The design of an internal risk rating system is key to its effectiveness. By definition, a
rating system comprises all of the processes that support the assessment of credit risk, the
assignment of internal risk ratings, and the quantification of default and loss estimates. Banking
organizations would be able to rely on one or more systems for assessing their credit risk
exposures. When this is the case, the banking organization would have to demonstrate that each
system used for A-IRB capital purposes complies with the supervisory standards.
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The Agencies believe that banking organizations’ internal rating systems should
accurately and consistently differentiate degrees of risk. For wholesale exposures, banking
organizations would need to have a two-dimensional rating system that separately assesses the
risk of borrower default, as well as transaction-specific factors that focus on the amount that
would likely be collected in the event of default. Such factors may include whether an exposure
is collateralized, its seniority, and the product type. In contrast to the individual evaluation
required for wholesale exposures, retail exposures would be assessed on a pool basis. Banking
organizations would need to group their retail exposures into portfolio segments based on the
risk characteristics that they consider relevant -- for example borrower characteristics such as
credit scores or transaction characteristics such as product or collateral type. Delinquent or
defaulted exposures would need to be separated from those that are current.
Banking organizations would be required to define clearly their wholesale rating
categories and retail portfolio segments. The clarity and transparency of the ratings criteria are
critical to ensuring that ratings are assigned in a consistent and reliable manner. The Agencies
believe it is important for banking organizations to document the operating procedures for their
internal risk rating system in writing. For example, the documentation should describe which
parties within the organization would have the authority to approve exceptions. Further, the
documentation would have to clearly specify the frequency of review, as well as describe the
oversight to be provided by management of the ratings process.
Banking organizations using the A-IRB approach would need to be able to generate
sound measurements of the key risk inputs to the A-IRB capital formulas. Banking
organizations would be able to rely on data based either on internal experience or generated by
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an external source, as long as the banking organization can demonstrate the relevance of external
data to its own experience.
In assigning a rating to an obligor, a banking organization must assess the risk of default,
taking into account possible adverse events that might increase the obligor’s likelihood of
default. The A-IRB supervisory standards in the supervisory guidance provide banking
organizations with a degree of flexibility in determining precisely how to reflect adverse events
in obligor ratings. However, banking organizations are required to clearly articulate the
approach chosen, and to articulate the implications for capital planning and for capital adequacy
during times of systematic economic stress. The Agencies recognize that banking organizations’
internal risk rating systems may include a range of statistical models or other methods to assign
borrower or facility ratings or to estimate key inputs. The burden of proof would remain on the
banking organization as to whether a specific model or procedure satisfies the supervisory
standards.
Risk rating system operations
The risk rating system would have to form an integral part of the loan approval process
wherein ratings are assigned to all borrowers, guarantors or facilities depending upon whether
the extension of credit is wholesale or retail in nature. Any deviations from policies that govern
the assignment of ratings must be clearly documented and monitored.
Data maintenance is another key aspect of risk rating system operations. Banking
organizations would be expected to collect and store data on key borrower and facility
characteristics. The data would have to be sufficiently detailed to allow for future
reconsideration of the way in which obligors and facilities have been allocated to grades.
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Furthermore, banking organizations would have to collect, retain and disclose data on aspects of
their internal ratings as described under the disclosure section of this proposal.
Banking organizations would be required to have in place sound stress testing processes
for use in the assessment of capital adequacy. Stress testing would have to involve identifying
possible events or future changes in economic conditions that could have unfavorable effects on
a banking organization’s credit exposures. Specifically, institutions would need to assess the
effect of certain specific conditions on their A-IRB regulatory capital requirements. The choice
of test to be employed would remain with the individual banking organization provided the
method selected is meaningful and reasonably conservative.
Corporate governance and oversight
The Agencies view the involvement of the board of directors and management as critical
to the successful implementation of the A-IRB approach. The board of directors and
management would be responsible for maintaining effective internal controls over the banking
organization’s information systems and processes for assessing adequacy of regulatory capital
and determining regulatory capital charges consistent with this ANPR. All significant aspects of
the rating and estimation processes must be approved by the banking organization’s board of
directors or a designated committee thereof and senior management. These parties would need
to be fully aware of whether the system complies with the supervisory standards, makes use of
the necessary data, and produces reliable quantitative estimates. Ongoing management reports
would have to accurately capture the performance of the rating system.
Oversight would also need to involve independent credit risk control units responsible for
ensuring the performance of the rating system, the accuracy of the ratings and parameter
estimates, and overall compliance with supervisory standards and capital regulations. The
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Agencies believe it is critical that such units remain functionally independent from the personnel
and management responsible for originating credit exposures. Among other responsibilities, the
control units should be charged with testing and monitoring the appropriateness of the rating
scale, verifying the consistent use of ratings for a given exposure type across the organization,
and reviewing and documenting any changes to be made to the system.
Use of internal ratings
To qualify to use the A-IRB framework, a banking organization’s rating systems would
have to form an integral part of its day-to-day credit risk management process. The Agencies
expect that banking organizations would rely on their internal risk rating systems when making
decisions about whether to extend credit as well as in their ongoing monitoring of credit
exposures. For example, ratings information would have to be incorporated into other key
processes, such as reserving determinations and when allocating economic capital internally.
Risk quantification
Ratings quantification is the process of assigning values to the key risk components of the
A-IRB approach: PD, LGD, EAD and M. With the exception of M, the risk components are
unobservable and must be estimated. The estimates would have to be consistent with sound
practice and supervisory standards. Banking organizations’ rating system review and internal
audit functions would need to serve as control mechanisms that ensure the process of rating
assignments and quantification are functioning according to policy and that non-compliance or
weaknesses are identified.
Validation of internal estimates
An equally important element would be a robust system for validating the accuracy and
consistency of a banking organization’s rating system, as well as the estimation of risk
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components. The standards in the supervisory guidance require that banking organizations use a
broad range of validation tools, including evaluation of developmental evidence, ongoing
monitoring of rating and quantification processes, benchmarking against alternative approaches,
and comparison of outcomes with estimates. Details of the validation process would have to be
consistent with the operation of the banking organization’s rating system and data would have to
be maintained and updated to support oversight and validation work. Banking organizations
would have to have well-articulated standards for situations where deviations of realized values
from expectations become significant enough to call the validity of the estimates into question.
Rating systems with appropriate data and oversight feedback mechanisms should create an
environment that promotes integrity and improvements in the rating system over time.
U.S. Supervisory Review
The primary Federal supervisor would be responsible for evaluating an institution’s
initial and ongoing compliance with the infrastructure requirements and supervisory standards
for approval to use the A-IRB approach for regulatory capital purposes. As noted, the Agencies
will be developing and issuing specific implementation guidance describing the supervisory
criteria for wholesale, retail, equity and securitization exposures. The Agencies will issue the
draft implementation guidance for each portfolio for public comment to ensure that there is an
opportunity for banking organizations and others to provide feedback on the Agencies’
expectations in regard to A-IRB systems.
The Agencies seek comment on the extent to which an appropriate balance has
been struck between flexibility and comparability for the A-IRB requirements. If
this balance is not appropriate, what are the specific areas of imbalance, and
what is the potential impact of the identified imbalance? Are there alternatives
that would provide greater flexibility, while meeting the overall objective of
producing accurate and consistent ratings?
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The Agencies also seek comment on the supervisory standards contained in the
draft guidance. Do the standards cover all of the key elements of an A-IRB
framework? Are there specific practices that appear to meet the objectives of
accurate and consistent ratings but that would be ruled out by the supervisory
standards related to controls and oversight? Are there particular elements from
the corporate guidance that should be modified or reconsidered as the Agencies
draft guidance for other types of credit?
In addition, the Agencies seek comment on the extent to which these proposed
requirements are consistent with the ongoing improvements banking
organizations are making in credit-risk management processes.
IV.
Securitization
A. General Framework
This section describes the calculation of A-IRB capital requirements for securitization
exposures. A securitization exposure is any on- or off-balance-sheet position created by
aggregating and then tranching the risks of a pool of assets, commitments, or other instruments
(underlying exposures) into multiple financial interests where, typically, the pooled risks are not
shared pro-rata. The pool may include one or more underlying exposures. Examples include all
exposures arising from traditional and synthetic securitizations, as well as partial guarantee
arrangements where credit losses are not divided proportionately among the parties (often
referred to as tranched cover). Asset- and mortgage-backed securities (including those privately
issued and those issued by GSEs such as Fannie Mae and Freddie Mac), credit enhancements,
liquidity facilities, and credit derivatives that meet the conditions noted above would be
considered securitization exposures.
With ongoing advances in financial engineering, the Agencies recognize that
securitization exposures having similar risks can take different legal forms. For this reason, both
the designation of positions as securitization exposures and the calculation of A-IRB capital
requirements for securitization exposures would be guided by the economic substance of a given
transaction, rather than by its legal form.
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Operational Criteria
Banking organizations would have to satisfy certain operational criteria to be eligible to
use the A-IRB approach to securitization exposures. Moreover, all banking organizations that
use the A-IRB approach for the underlying exposures that have been securitized would have to
apply the A-IRB treatment for securitization exposures. Minimum operational criteria would
apply to traditional and synthetic securitizations, including permissible types of clean-up calls.28
The Agencies propose to establish supervisory criteria for determining when, for risk-based
capital purposes, a banking organization may treat exposures that it has originated directly or
indirectly as having been securitized and, hence, not subject to the same capital charge as if the
banking organization continued to hold the assets. The Agencies anticipate these supervisory
criteria will be substantially equivalent to the criteria contained in the New Accord (paragraphs
516-520). Broadly, these criteria are intended to ensure that securitization transactions transfer
significant credit risk to third parties and, in the case of traditional securitizations, that each
transaction qualifies as a true sale under applicable accounting standards.
The supervisory criteria also would describe the types of clean-up calls that may be
incorporated within transactions qualifying for the A-IRB securitization treatment. Specifically,
any clean-up call would have to meet the following conditions: (a) its exercise is at the discretion
of the originating banking organization; (b) it does not serve as a credit enhancement; and (c) it
is only exercisable when 10 percent or less of the original underlying portfolio or reference
portfolio value remains. If a clean-up call does not meet all of these criteria, the originating
banking organization would have to treat the underlying exposures as if they had not been
securitized.
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The Agencies seek comment on the proposed operational requirements for
securitizations. Are the proposed criteria for risk transference and clean-up calls
consistent with existing market practices?
Differences Between General A-IRB Approach and the A-IRB Approach for Securitization
Exposures
In contrast to the proposed A-IRB framework for traditional loans and commitments, the
A-IRB securitization framework does not rely on a banking organization’s own internal
assessments of the PD and LGD of a securitization exposure. For pools of multiple assets, such
assessments require implicit or explicit estimates of correlations among the losses on those
assets. Such correlations are extremely difficult to estimate and validate in an objective manner
and on a going-forward basis. For this reason, the A-IRB framework generally would not permit
a banking organization to use its internal risk assessments when such assessments depend,
implicitly or explicitly, on estimates of correlation effects. The A-IRB treatment of
securitization exposures would rely principally on two sources of information, when available:
(i) an assessment of the securitization exposure’s credit risk made by an external rating agency
and (ii) the A-IRB capital charge that would have been assessed against the underlying exposures
had the exposures not been securitized (denoted “KIRB”), along with other information about the
transaction.
B. Determining Capital Requirements
General Considerations
Because the information available to a banking organization about a securitization
exposure often reflects the organization’s role in a securitization transaction, the Agencies are
proposing that the method of calculating the A-IRB capital requirement for a securitization
28
In general terms, a clean-up call is an option that permits an originating banking organization to call the
securitization exposures (for example, asset- or mortgage-backed securities) before all of the underlying
exposures have been repaid.
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exposure may depend on whether a banking organization is an originator or a third-party investor
in the securitization transaction. In general, a banking organization would be considered an
originator of a securitization if the organization directly or indirectly originated the underlying
exposures or serves as the sponsor of an asset-backed commercial paper (ABCP) conduit or
similar program.29 If a banking organization is not deemed an originator of a securitization
transaction, then it would be considered an investor in the securitization.
There are several methods for determining the A-IRB capital requirement for a
securitization exposure: the Ratings-Based Approach (RBA), the Alternative RBA, the
Supervisory Formula Approach (SFA), the Look-Through Approach, deduction from Tier 1
capital, and deduction from total capital. When a banking organization would apply one of these
methods to determine the A-IRB capital requirement for a particular securitization exposure is
summarized in the table below.
29
A banking organization is generally considered a sponsor of an ABCP conduit or similar program if, in fact or in
substance, it manages or advises the conduit program, places securities into the market for the program, or
provides liquidity support or credit enhancements to the program.
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Steps for Determining A-IRB
Capital Requirements for Securitization Exposures
For an investing banking organization:
1. Deduct from total capital any credit-enhancing interest-only strips
2. When an external or inferred rating exists, apply the RBA
3. When an external or inferred rating does not exist, then do the following:
a. Subject to supervisory review and approval, if the investing banking organization can
determine KIRB, then calculate required capital as would an originating banking
organization using the steps described in 2.a. below
b. Otherwise, deduct the securitization exposure from total capital
For an originating banking organization*
1. Deduct from Tier 1 capital any increase in capital resulting from the securitization
transaction and deduct from total capital any credit-enhancing interest-only strips (net of
deductions from Tier 1 capital due to increases in capital)
2. When an A-IRB approach exists for the underlying exposures then do the following:
a. If KIRB can be determined:
i. For a securitization exposure (or portion thereof) that is below KIRB, deduct the
exposure from total capital
ii. For a securitization exposure (or portion thereof) that is above KIRB:
1. Apply the RBA whenever an external or inferred rating is available
2. Otherwise, apply the SFA
b. If KIRB cannot be determined:
i. Apply the Look-Through Approach if the exposure is an eligible liquidity facility,
subject to supervisory approval
ii. Otherwise, deduct the exposure from total capital
3. When an A-IRB approach does not exist for the underlying exposures then do the following:
a. Apply the Look-Through Approach if the exposure is an eligible liquidity facility, subject
to supervisory approval
b. Otherwise, apply the Alternative RBA
*In addition to the capital treatments delineated, an originating banking organization’s total A-IRB capital
charge with regard to any single securitization transaction is subject to a maximum or ceiling, as
described later in this section.
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Deductions of gain on sale or other accounting elements that result in increases in equity capital
Any increase in equity capital resulting from a securitization transaction (for example, a
gain resulting from FAS 140 accounting treatment of the sale of assets) would be deducted from
Tier 1 capital. Such deductions are intended to offset any gain on sale or other accounting
treatments (“gain on sale”) that result in an increase in an originating banking organization’s
shareholder’s equity and Tier 1 capital. Over time, as banking organizations, from an accounting
perspective, realize the increase in equity that was booked at origination of a securitization
transaction through actual receipt of cash flows, the amount of the required deduction would be
reduced accordingly.
Banking organizations would have to deduct from total capital any on-balance sheet
credit-enhancing interest-only strips (net of any increase in the shareholder’s equity deducted
from Tier 1 capital) as described in the previous paragraph. 30 Credit-enhancing interest-only
strips are defined in the general risk-based capital rules and cover items, such as excess spread,
that represent subordinated cash flows of future margin income.
Maximum capital requirement
Where an A-IRB approach exists for the underlying exposures, an originating banking
organization's total A-IRB capital charge for exposures associated with a given securitization
transaction would be subject to a maximum or ceiling. This maximum A-IRB capital charge
would equal the aggregate A-IRB capital charge on the underlying exposures multiplied by the
size of the underlying exposure pool (KIRB), plus any required deductions, as described in the
preceding paragraphs. The aim of this treatment is to ensure that an institution’s effective A-IRB
capital charge generally would not be greater after securitization than before, while also
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addressing the Agencies’ safety and soundness concerns with respect to credit-enhancing
interest-only strips and other capitalized assets.31
The proposed maximum A-IRB capital requirement effectively would reverse the general
risk-based capital rules for securitization exposures referred to as residual interests. Under the
general risk-based capital rules, banking organizations are required to hold a dollar in capital for
every dollar in residual interest exposure, regardless of the capital requirement on the underlying
assets. One of the reasons the Agencies adopted the “dollar-for-dollar” capital treatment for
residual interests is that in many instances the relative size of the exposure retained by the
originating banking organization reveals additional market information about the quality of the
underlying exposures and deal structure that may not have been captured in the capital
requirement on the underlying exposures, had those exposures remained on the banking
organization’s balance sheet. The Agencies will continue to review the proposal for safety and
soundness considerations and may consider retaining the current dollar-for-dollar capital
treatment for residual interests, especially in those instances where an originator retains first loss
and other deeply subordinated interests in amounts that significantly exceed KIRB plus required
deductions.
Comments are invited on the circumstances under which the retention of the
treatment in the general risk-based capital rules for residual interests for banking
organizations using the A-IRB approach to securitization would be appropriate.
Should the Agencies require originators to hold dollar-for-dollar capital against
all retained securitization exposures, even if this treatment would result in an
aggregate amount of capital required of the originator that exceeded KIRB plus
any applicable deductions? Please provide the underlying rationale.
30
Deductions other than of increases in equity capital are to be taken 50 percent from Tier 1 capital and 50 percent
from Tier 2 capital.
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Investors
Third-party investors generally do not have access to detailed, ongoing information about
the credit quality of the underlying exposures in a securitization. In such cases, investors often
rely upon credit assessments made by external rating agencies. For securitization exposures held
by an investing banking organization, and where an A-IRB treatment for the underlying
exposures exists, the institution would use the Ratings-Based Approach (RBA) described below
if the securitization exposure is externally rated or if an inferred rating is available as defined in
the RBA discussion below. When neither an external nor an inferred rating is available, an
investing banking organization would compute the A-IRB capital charge using the methodology
described below for originating institutions (subject to supervisory review and approval).
Otherwise, the securitization exposure would be deducted 50 percent from Tier 1 and 50 percent
from Tier 2 capital. The Agencies anticipate that investing banking organizations would apply
the RBA in the vast majority of situations.
Originators
This section presumes that an A-IRB approach exists for the underlying exposures. If no
A-IRB treatment exists for the underlying exposures, then an originating banking organization
(originator) would use the Alternative RBA discussed below. For eligible liquidity facilities
(defined below in the Look Through Approach) provided to ABCP programs where a banking
organization lacks the information necessary to calculate KIRB, the Look-Through Approach
described below would be applied on a temporary basis and subject to supervisory approval.
In contrast to third-party investors, banking organizations that originate securitizations
are presumed to have much greater access to information about the current credit quality of the
underlying exposures. In general, when an originator retains a securitization exposure, the
31
The maximum capital requirement also applies to investing banks that receive approval to use the SFA.
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securitization framework would require the institution to calculate, on an ongoing basis, the
underlying exposure pool's A-IRB capital requirement had the underlying exposures not been
securitized (the "pool's A-IRB capital charge"), which would be based on the notional dollar
amount of underlying exposures (the "size of the pool"). The pool's A-IRB capital charge would
be calculated using the “top-down” or “bottom-up” method applicable to the type(s) of
underlying exposure(s).32 The pool’s A-IRB capital charge divided by the size of the pool would
be denoted KIRB. An originator also would be expected to know: (a) its retained securitization
exposure's nominal size relative to the size of the pool (the exposure's "thickness," denoted T);
and (b) the notional amount of all more junior securitization exposures relative to the size of the
pool (the exposure's "credit enhancement level," denoted L). The retained securitization
exposure's A-IRB capital requirement depends on the relationship between KIRB, T, and L. If
an originator cannot determine KIRB, any retained securitization exposure would be deducted
from capital.
Positions below KIRB
An originating banking organization would deduct from capital any retained
securitization exposure (or part thereof) that absorbs losses at or below the level of KIRB (that
is, an exposure for which L+T ≤ KIRB).33 This means that an originating banking organization
would be given no risk-based capital relief unless it sheds at least some exposures below KIRB.
Deduction from capital would be required regardless of the securitization exposure’s external
rating. This deduction treatment is in contrast to the A-IRB capital treatment for investors, who
32
For the purpose of determining the A-IRB capital requirement for a securitization exposure, the top-down method
could be used regardless of the maturity of the underlying exposures, provided the other eligibility criteria for
employing the top-down approach are satisfied.
33
If an originator holds a securitization exposure that straddles KIRB, the exposure must be decomposed into two
separate positions – one that is above KIRB and another that is at or below KIRB.
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would be able to look to the external (or inferred) rating of a securitization exposure regardless
of whether the exposure was below KIRB.
While this disparate treatment of originators and investors may be viewed as inconsistent
with the principle of equal capital for equal risk, the Agencies believe it is appropriate in order to
provide incentives for originating banks to shed highly subordinated securitization exposures.
Such exposures contain the greatest credit risks. Moreover, these risks are difficult to evaluate,
and risk quantifications tend to be highly sensitive to modeling assumptions that are difficult to
validate objectively. The proposal to prevent an originator from using the RBA for securitization
exposures below KIRB reflects, in part, a concern by the Agencies that the market discipline
underpinning an external credit rating may be less effective when the rating applies to a retained,
non-traded securitization exposure and is sought by an originator solely for regulatory capital
purposes.
The Agencies note that the specific securitization exposures retained by an originator that
are subject to deduction treatment could change over time in response to variations in the credit
quality of the underlying exposures. For example, if the pool’s A-IRB capital charge were to
increase after the inception of a securitization, additional portions of securitization exposures
held by an originator may fall below KIRB and, thus, become subject to deduction. Therefore,
when an originator retains a first-loss securitization exposure well in excess of KIRB, the
originator’s A-IRB capital requirement on the exposure could climb rapidly in the event of any
marked deterioration of the underlying exposures. In general, an originator could minimize
variability in future capital charges by minimizing the size of any retained first-loss
securitization exposures.
The Agencies seek comment on the proposed treatment of securitization exposures
held by originators. In particular, the Agencies seek comment on whether
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originating banking organizations should be permitted to calculate A-IRB capital
charges for securitizations exposures below the KIRB threshold based on an
external or inferred rating, when available.
Positions above KIRB
When an originating banking organization retains a securitization exposure, or part
thereof, that absorbs losses above the KIRB amount (that is, an exposure for which L + T >
KIRB) and the banking organization has not already met the maximum capital requirement for
securitization exposures described previously, the A-IRB capital requirement for the exposure
would be calculated as follows. For securitization exposures having an external or inferred
rating, the organization would calculate it’s A-IRB capital requirement using the RBA.
However, if neither an external rating nor an inferred rating is available, an originator would be
able to use the SFA, subject to supervisory review and approval. Otherwise, the organization
would deduct the securitization exposure from total capital.
The Agencies seek comment on whether deduction should be required for all nonrated positions above KIRB. What are the advantages and disadvantages of the
SFA approach versus the deduction approach?
Capital Calculation Approaches
The ratings-based approach (RBA)
The RBA builds upon the widespread acceptance of external ratings by third-party
investors as objective assessments of a securitization exposure’s stand-alone credit risk. Certain
minimum requirements would have to be satisfied in order for a banking organization to rely on
an external credit rating. To be recognized for regulatory capital purposes, the external credit
rating on a securitization exposure must be public and take into account and reflect the entire
amount of credit risk exposure the banking organization has with regard to all payments owed to
it under the exposure. In particular, if a banking organization is owed both principal and interest
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on a securitization exposure, the external rating on the exposure must fully reflect the credit risk
associated with both payment streams. The Agencies propose to establish criteria to ensure the
integrity of external ratings processes and banking organizations' use of these ratings under the
RBA. These criteria are expected to be consistent with the proposed guidance provided in the
New Accord (paragraph 525).
In certain circumstances, an “inferred rating” may be used for risk weighting a non-rated
securitization exposure. Similar to the general risk-based capital rules, to qualify for use of an
inferred rating, a non-rated securitization exposure would have to be senior in all respects to the
next subordinate, rated position within the same securitization transaction. Further, the junior
rated tranche would have to have an equivalent or longer remaining maturity than the non-rated
exposure. Where these conditions are met, the non-rated exposure would be treated as if it had
the same rating (an “inferred rating”) as that of the rated junior tranche. External and inferred
ratings would be treated equivalently.
Under the RBA, the capital charge per dollar of a securitization exposure would depend
on: (i) the external rating (or inferred rating), (ii) whether the rating reflects a long-term or shortterm assessment of the exposure’s credit risk, and (iii) a measure of the effective number -- or
granularity -- of the underlying exposures, (N).34 For a securitization exposure rated AA or
AAA, the RBA capital charge also would depend on a measure of that exposure’s relative
seniority in the overall transaction (Q).35
Tables 1 and 2 below present the risk weights that would result from the RBA when a
securitization exposure’s external rating (or inferred rating) represents a long-term or short-term
34
N is defined more formally in the discussion below of the Supervisory Formula Approach.
Q is defined as the total size of all securitization exposures rated at least AA- that are pari passu or junior to the
exposure of interest, measured relative to the size of the pool and expressed as a decimal. Thus, for a securitization
transaction having an AAA-rated tranche in the amount of 70 percent of the pool, an AA-rated tranche of 10 percent,
35
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credit rating, respectively. In both tables, the risk weights in column 2 would apply to AA-and
AAA-rated securitization exposures when the effective number of exposures (N) is 100 or more,
and the exposure’s relative seniority (Q) is greater than or equal to 0.1 + 25/N. If the underlying
exposures are retail exposures, N would be treated as infinite and the minimum qualifying value
of Q would be 0.10. The Agencies anticipate that these risk weights would apply to AA- and
AAA-rated tranches of most retail securitizations. Column 4 would apply only to securitizations
involving pools of non-retail exposures for which N is less than 6, while column 3 would apply
in all other situations.
Within each table, risk weights increase as external rating grades decline. Under the Base
Case (column 3), for example, the risk weights range from 12 percent for AAA-rated exposures
to 650 percent for exposures rated BB-. This pattern of risk weights is broadly consistent with
analyses employing standard credit risk models and a range of assumptions regarding correlation
effects and the types of exposures being securitized.36 These analyses imply that, compared with
a corporate bond having a given level of stand-alone credit risk (for example, as measured by its
expected loss rate), a securitization tranche having the same level of stand-alone risk -- but
backed by a reasonably granular and diversified pool -- will tend to exhibit more systematic
risk.37 This effect is most pronounced for below-investment grade tranches, and is the primary
reason why the RBA risk weights increase rapidly as ratings deteriorate over this range -- much
more rapidly than for similarly rated corporate bonds. Similarly, the risk weights expected to
apply to most securitization exposures backed by highly granular pools (column 2) decline
steeply as ratings improve above single-A -- again, more so than might be the case for similarly
a BBB-rated tranche of 10 percent, and a non-rated tranche of 10 percent, the values of Q associated with these three
positions would be 0.80, 0.10 , 0, and 0, respectively.
36
See Vladislav Peretyatkin and William Perraudin, "Capital for Asset-Backed Securities," Bank of England,
February 2003.
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rated corporate bonds -- while the decline is less pronounced for the Base Case and for tranches
backed by non-granular pools (column 4).
For securitization exposures rated below BB-, the proposed A-IRB treatment -- deduction
from capital -- would be somewhat more conservative than suggested by credit risk modeling
analyses. However, the Agencies believe this more conservative treatment would be appropriate
in light of modeling uncertainties and the tendency for securitization exposures in this range, at
least at the inception of the securitization transaction, to be non-traded positions retained by an
originator because they cannot be sold at a reasonable price.
37
See, for example, Michael Pykhtin and Ashish Dev, "Credit Risk in Asset Securitizations: Analytical Model,"
Risk (May 2002) S16-S20.
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Table 1: ABS risk weights based on long-term credit assessments
External
Rating
(Illustrative)
Thick Tranches
Backed by
Highly Granular
Pools
AAA
AA
A
BBB+
BBB
BBBBB+
BB
BBBelow BB-
7%
10%
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Base Case
12%
15%
20%
50%
75%
100%
250%
425%
650%
Deduction
Tranches
Backed by
Non-granular
Pools
20%
25%
35%
50%
75%
100%
250%
425%
650%
Deduction
Table 2: ABS risk weights based on short-term credit assessments
External Rating
(Illustrative)
Thick Tranches
Backed by
Highly Granular
Pools
A-1/P-1
A-2/P-2
A-3/P-3
All other ratings
7%
N/A
N/A
N/A
Base Case
12%
20%
75%
Deduction
Tranches
Backed by
Non-granular
Pools
20%
35%
75%
Deduction
The Agencies seek comment on the proposed treatment of securitization exposures
under the RBA. For rated securitization exposures, is it appropriate to
differentiate risk weights based on tranche thickness and pool granularity?
For non-retail securitizations, will investors generally have sufficient information
to calculate the effective number of underlying exposures (N)?
What are views on the thresholds, based on N and Q, for determining when the
different risk weights apply in the RBA?
Are there concerns regarding the reliability of external ratings and their use in
determining regulatory capital? How might the Agencies address any such
potential concerns?
Unlike the A-IRB framework for wholesale exposures, there is no maturity
adjustment within the proposed RBA. Is this reasonable in light of the criteria to
assign external ratings?
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The supervisory formula approach (SFA)
As noted above, when an explicit A-IRB approach exists for the underlying exposures,
originating and investing banking organizations would be able to apply the SFA to non-rated
exposures above the KIRB threshold, subject to supervisory approval and review. The Agencies
anticipate that, in addition to its application to liquidity facilities and to other traditional and
synthetic securitization exposures, the SFA would be used when calculating A-IRB capital
requirements for tranched guarantees (for example, a loan for which a guarantor assumes a firstloss position that is less than the full amount of the loan).
Under the SFA, the A-IRB capital charge for a securitization tranche would depend on
six institution-supplied inputs:38 the notional amount of underlying exposures that have been
securitized (E), the A-IRB capital charge had the underlying exposures not been securitized
(KIRB); the tranche’s credit enhancement level (L); the tranche's thickness (T); the pool’s
effective number of exposures (N); and the pool’s exposure-weighted average loss-given-default
(LGD). In general, the estimates of N and LGD would be developed as a by-product of the
process used to determine KIRB.
The SFA capital charge for a given securitization tranche would be calculated as the
notional amount of exposures that have been securitized (E), multiplied by the greater of: (i)
0.0056 * T or (ii) the following expression: 39
38
When the banking organization holds only a proportional interest in the tranche, that position’s A-IRB capital
charge equals the prorated share of the capital charge for the entire tranche.
39
Because securitization exposures at or below KIRB must be deducted from regulatory capital, the SFA applies
only to exposures above KIRB. When a tranche straddles KIRB, for the purpose of applying the SFA the
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(1)
K [ L + T ] − K [ L ] + { 0 .05 ⋅ ( d ⋅ K IRB ⋅ e − 20 ⋅( L − K IRB ) / K IRB ) ⋅ (1 − e − 20 T / K IRB )} ,
where,40
h
= (1 − K IRB / LGD ) N
c
= K IRB /(1 − h )
v
=
f
g
a
b
d
( LGD − K IRB ) K IRB + 0 .25 (1 − LGD ) K IRB
N
2
v + K IRB
(1 − K IRB ) K IRB − v
=
− c 2 +
(1 − h ) ⋅1000
1− h
(1 − c ) c
=
−1
f
= g ⋅c
= g ⋅ (1 − c )
= 1 − (1 − h ) ⋅ (1 − Beta [ K IRB ; a , b ])
K [ x ] = (1 − h ) ⋅ ( x ⋅ (1 − Beta [ x ; a , b ]) + c ⋅ Beta [ x ; a + 1, b ] ).
Although visually daunting, the above supervisory formula is easily programmable within
standard spreadsheet packages, and its various components have intuitive interpretations.
Part (i), noted above, of the supervisory formula approach effectively imposes a 56 basis
point minimum or floor A-IRB capital charge per dollar of tranche exposure. While
acknowledging that such a floor is not risk-sensitive, the Agencies believe that some minimum
prudential capital charge is nevertheless appropriate. The floor has been proposed at 56 basis
points partly on the basis of empirical analyses suggesting that, across a broad range of modeling
assumptions and exposure types, this level provides a reasonable lower bound on the capital
charges implied by standard credit risk models for tranches meeting the standards for an external
tranche should be decomposed into a position at or below KIRB and another above KIRB. The former would be
deducted from capital, while the latter would be the position to which the SFA is actually applied.
40
In these expressions, Beta[X; a, b] refers to the cumulative beta distribution with parameters a and b evaluated at
X. The cumulative beta distribution function is available in Excel as the function BETADIST.
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rating of AAA.41 This floor also is consistent with the lowest capital charge available under the
RBA.
Part (ii) of the supervisory formula approach also is a blend of credit risk modeling
results and supervisory judgment. The function denoted K[x] represents a pure model-based
estimate of the pool's aggregate systematic or non-diversifiable credit risk that is attributable to a
first-loss position covering pool losses up to and including x. Since the tranche of interest
(defined in terms of a credit enhancement level L, and thickness T) covers losses between L and
L+T, its total systematic risk can be represented as K[L+T] - K[L], which are the first two terms
in (1). The term in braces within (1) represents a supervisory add-on to the pure model-based
result. This add-on is intended primarily to avoid potential behavioral distortions associated with
what would otherwise be a discontinuity in capital charges for relatively thin mezzanine tranches
lying just below and just above KIRB: all tranches below KIRB would be deducted from capital,
whereas a very thin tranche just above KIRB would incur a pure model-based capital charge that
could vary between zero and one, depending upon the number of effective underlying exposures
in the pool, N. The add-on would apply primarily to positions just above KIRB, and its
quantitative effect would diminish rapidly as the distance from KIRB widens.
Most of the complexity of the supervisory formula is a consequence of attempting to
make K[x] as consistent as possible with the parameters and assumptions of the A-IRB
framework that would apply to the underlying exposures if held directly by a banking
organization.42 The specification of K[x] assumes that KIRB is an accurate measure of the pool's
total systematic credit risk, and that a securitization merely redistributes this systematic risk
41
See Vladislav Peretyatkin and William Perraudin, "Capital for Asset-Backed Securities," Bank of England,
February 2003.
42
The conceptual basis for specification of K[x] above is developed in Michael B. Gordy and David Jones,
"Random Tranches," Risk (March 2003) 78-83.
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among its various tranches. In this way, K[x] embodies precisely the same asset correlations as
are assumed elsewhere within the A-IRB framework. In addition, this specification embodies
the well-known result that a pool's total systematic risk (that is, KIRB) tends to be redistributed
toward more senior tranches as the effective number of underlying exposures in the pool (N)
declines.43 The importance of pool granularity depends on the pool's average loss-rate-givendefault, as increases in LGD also tend to shift systematic risk toward senior tranches when N is
small. For highly granular pools, such as securitization of retail exposures, LGD would have no
influence on the SFA capital charge.
The Agencies propose to establish criteria for determining E, KIRB, L, T, N, and LGD
that are consistent with those suggested in the New Accord. A summary of these requirements is
presented below.
E. This input would be measured (in dollars) as the A-IRB estimate of the exposures in
the underlying pool of securitized exposures, as if they were held directly by the banking
organization, rather than securitized. This amount would reflect only those underlying exposures
that have actually been securitized to date. Thus, for example, E would exclude undrawn lines
associated with revolving credit facilities (for example, credit card accounts).
KIRB. This input would be measured (in decimal form) as the ratio of (a) the pool's AIRB capital requirement to (b) the notional or loan equivalent amount of underlying exposures in
the pool (E). The pool's A-IRB capital requirement would be calculated in accordance with the
applicable A-IRB standard for the type of underlying exposure. This calculation would
incorporate the effect of any credit risk mitigant that is applied to the underlying exposures
(either individually or to the entire pool), and hence benefits all of the securitization exposures.
Consistent with the measurement of E, the estimate of KIRB would reflect only the underlying
43
See Michael Pykhtin and Ashish Dev, "Coarse-grained CDOs", Risk (January 2003) 113-116.
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exposures that have been securitized. For example, KIRB generally would exclude the A-IRB
capital charges against the undrawn portions of revolving credit facilities.
Credit enhancement level (L). This input would be measured (in decimal form) as the
ratio of: (a) the notional amount of all securitization exposures subordinate to the tranche of
interest to (b) the notional or loan equivalent amount of underlying exposures in the pool (E). L
would incorporate any funded reserve account (for example, spread account or
overcollateralization) that provides credit enhancement to the tranche of interest. Creditenhancing interest-only strips would not be included in the calculation of L.
Thickness (T). This input would be measured (in decimal form) as the ratio of (a) the
nominal amount of the tranche of interest to (b) the notional or loan equivalent amount of
underlying exposures in the pool (E).
Effective number of exposures (N). This input would be calculated as
N =
(∑ EADi ) 2
i
∑ EAD
2
i
i
where EADi represents the exposure-at-default associated with the i-th underlying exposure in
the pool. Multiple exposures to the same obligor would be consolidated (that is, treated as a
single exposure). If the pool contains any underlying exposures that are themselves
securitization exposures (for example, one or more asset-backed securities), each of these would
be treated as a single exposure for the purpose of measuring N.44
44
Within the supervisory formula, the probability distribution of credit losses associated with the underlying pool of
exposures is approximated by treating the pool as if it consisted of N homogeneous exposures, each having an AIRB capital charge of KIRB/N. The proposed treatment of N implies, for example, that a pool containing one
ABS tranche backed by 1 million effective loans behaves more like a single loan having an A-IRB capital charge
of KIRB than a pool of 1 million loans, each having an A-IRB capital charge of KIRB/1,000,000.
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Exposure-weighted average LGD. This input would be calculated (in decimal form) as
∑ LGD ⋅ EAD
LGD =
∑ EAD
i
i
i
i
i
where LGDi represents the average LGD associated with all underlying exposures to the i-th
obligor. In the case of re-securitization (a securitization of securitization exposures), an LGD of
100 percent would be assumed for any underlying exposure that was itself a securitization
exposure.45
Simplified method for computing N and LGD. Under the conditions provided below,
banking organizations would be able to employ simplified methods for calculating N and the
exposure-weighted average LGD. When the underlying exposures are retail exposures, the SFA
may be implemented by setting h = 0 and v = 0, subject to supervisory approval and review.
When the share of the pool associated with the largest exposure, C1, is no more than 0.03 (or 3
percent of the pool), the banking organization would be able to set LGD = 0.50 and N equal to:
−1
C − C1
N = C1 Cm + m
max{1 − m C1 , 0 }
m −1
, provided that the banking
organization can measure Cm, which denotes the share of the pool corresponding to the largest
“m” exposures (for example, a 15 percent share corresponds to a value of 0.15).46 Alternatively,
when only C1 is available and this amount is no more than 0.03, then the banking organization
would be able to set LGD = 0.50 and N = 1/ C1.
45
As noted above, the A-IRB securitization framework does not permit banking organizations to use their own
internal estimates of LGDs (and PDs) for securitization exposures because such quantification requires implicit or
explicit estimates of loss correlations among the underlying exposures. Recall that LGDs should be measured as the
loss rates expected to prevail when default rates are high. While setting LGDs equal to 100 percent is reasonable for
certain types of ABSs, such as highly subordinated or thin tranches, this level of LGD may be conservative for other
types of ABSs. However, the Agencies believe that the complexity and burden associated with a more refined
treatment of LGDs would outweigh any improvement in the overall risk sensitivity of A-IRB capital charges for
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The Agencies seek comment on the proposed SFA. How might it be simplified
without sacrificing significant risk sensitivity? How useful are the alternative
simplified computation methodologies for N and LGD?
The Look-Through Approach for eligible liquidity facilities
ABCP conduits and similar programs sponsored by U.S. banking organizations are major
sources of funding for financial and non-financial companies. Liquidity facilities supporting
these programs are considered to be securitization exposures of the banking organizations
providing the liquidity, and generally would be treated under the rules proposed for originators.
As a general matter, the Agencies expect that banking organizations using the A-IRB approach
would apply the SFA when determining the A-IRB capital requirement for liquidity facilities
provided to ABCP conduits and similar programs. However, if it would not be practical for a
banking organization to calculate KIRB using a top-down or a bottom-up approach, the banking
organization may be allowed to use the Look-Through Approach, described below, for
determining the A-IRB capital requirement, subject to supervisory approval and for a temporary
period of time to be determined in consultation with the organization’s primary Federal
supervisor.
Because the Look-Through Approach has limited risk sensitivity, the Agencies propose
that its applicability be restricted to liquidity facilities that are structured to minimize the extent
to which the facilities provide credit support to the conduit. The Look-Through Approach would
only be available to liquidity facilities that meet the following criteria:
(a) the facility documentation clearly identifies and limits the circumstances under which it may
be drawn. In particular, the facility must not be able to cover losses already sustained by the
pool of underlying exposures (for example, to acquire assets from the pool at above fair
originators, owing to the combined effects of (a) the dollar-for-dollar A-IRB capital charge on positions below
KIRB, and (b) the maximum or cap on an originator's total A-IRB capital charge, equal to KIRB.
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value) or be structured such that draw-down is certain (as indicated by regular or continuous
draws);
(b) the facility is subject to an asset quality test that precludes it from being drawn to cover
underlying exposures that are in default;
(c) the facility cannot be drawn after all applicable (specific and program-wide) credit
enhancements from which the liquidity facility would benefit have been exhausted;
(d) repayment of any draws on the facility (that is, assets acquired under a purchase agreement
of loans made under a lending agreement) may not represent a subordinated obligation of the
pool or be subject to deferral or waiver; and
(e) reduction in the maximum drawn amount or early termination of the facility occurs, if the
quality of the pool falls below investment grade.
Under the Look-Through Approach, the liquidity facility's A-IRB capital charge would
be computed as the product of: (a) 8 percent, (b) the maximum potential drawdown under the
facility, (c) the applicable credit conversion factor (CCF), and (d) the applicable risk weight.
The CCF would be set at 50 percent if the liquidity facility's original maturity is one year or less,
and at 100 percent if the original maturity is more than one year. The Agencies propose that the
risk weight be set equal to the risk weight applicable under the general risk-based capital rules
for banking organizations not using the A-IRB approach (that is, to the underlying assets or
obligors after consideration of collateral or guarantees or, if applicable, external ratings).
The Agencies seek comment on the proposed treatment of eligible liquidity
facilities, including the qualifying criteria for such facilities. Does the proposed
Look-Through Approach -- to be available as a temporary measure -satisfactorily address concerns that, in some cases, it may be impractical for
providers of liquidity facilities to apply either the “bottom-up” or “top-down”
approach for calculating KIRB? It would be helpful to understand the degree to
which any potential obstacles are likely to persist.
46
The level of m is to be set by each banking organization.
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Feedback also is sought on whether liquidity providers should be permitted to
calculate A-IRB capital charges based on their internal risk ratings for such
facilities in combination with the appropriate RBA risk weight. What are the
advantages and disadvantages of such an approach, and how might the Agencies
address concerns that the supervisory validation of such internal ratings would be
difficult and burdensome? Under such an approach, would the lack of any
maturity adjustment with the RBA be problematic for assigning reasonable risk
weights to liquidity facilities backed by relatively short-term receivables, such as
trade credit?
Other Considerations
Capital treatment absent an A-IRB approach – The Alternative RBA
For originating banking organizations when there is not a specific A-IRB treatment for an
underlying exposure or group of underlying exposures, the Agencies propose that a securitization
exposure's capital charge be based exclusively on the exposure’s external or inferred credit rating
using the Alternative RBA.47 Under the Alternative RBA, a risk weight of 20 percent is applied
to exposures rated AAA to AA-, 50 percent to exposures rated A+ to A-, and 100 percent to
exposures rated BBB+ to BBB-. Securitization exposures having ratings below investment
grade, or that are non-rated, would be deducted from risk-based capital on a dollar-for-dollar
basis.
Should the A-IRB capital treatment for securitization exposures that do not have a
specific A-IRB treatment be the same for investors and originators? If so, which
treatment should be applied – that used for investors (the RBA) or originators
(the Alternative RBA)? The rationale for the response would be helpful.
Structures with early amortization provisions
Many securitizations of revolving credit facilities (for example, credit card accounts)
contain provisions that call for the securitization to be wound down if the excess spread falls
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beyond a certain threshold.48 This decrease in excess spread can, in some cases, be caused by
deterioration in the credit quality of the underlying exposures. An early amortization event can
increase a banking organization’s capital needs if any new draws on the revolving facilities
would need to be financed by the banking organization itself using on-balance-sheet sources of
funding. The payment allocations used to distribute principal and finance charge collections
during the amortization phase of these structures also can expose a banking organization to
greater risk of loss than in other securitization structures. To account for the risks that early
amortization structures pose to originating banking organizations, the capital treatment described
below would apply to securitizations of revolving credit facilities containing such features.
In addition to the A-IRB capital charge an originating banking organization would incur
on the securitization exposures it retains, an originator would be required to hold capital against
all or a portion of the investors’ interest in a securitization when (i) the organization sells
exposures into a securitization that contains an early amortization feature, and (ii) the underlying
exposures sold are of a revolving nature. The A-IRB capital charge attributed to the originator
that is associated with the investors’ interest is calculated as the product of: (a) the A-IRB capital
charge that would be imposed if the entire investors’ interest were held by the originating
banking organization, and (b) an applicable CCF.
In general, the CCF would depend on whether the early amortization feature repays
investors through a controlled or non-controlled mechanism, and whether the underlying
exposures represent uncommitted revolving retail facilities that are unconditionally cancellable
47
The Alternative RBA does not apply to eligible liquidity facilities, which may use the Look-Through Approach as
described above. Additionally, the securitization exposures subject to the Alternative RBA are not limited by the
maximum capital requirement discussed above.
48
Excess spread is defined as gross finance charge collections and other income received by the trust or special
purpose entity (SPE) minus certificate interest, servicing fees, charge-offs, and other senior trust or SPE
expenses.
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without prior notice (for example, credit card receivables) or other credit lines (for example,
revolving corporate facilities).
An early amortization provision would be considered controlled if, throughout the
duration of the securitization transaction, including the amortization period, there is a pro rata
sharing of interest, principal, expenses, losses, and recoveries based on the balances of
receivables outstanding at the beginning of each month. Further, the pace of repayment may not
be any more rapid than would be allowed through straight-line amortization over a period
sufficient for 90 percent of the total debt outstanding at the beginning of the early amortization
period to have been repaid or recognized as in default. In addition to these criteria, banking
organizations with structures containing controlled early amortization features would also have
to have appropriate plans in place to ensure that there is sufficient capital and liquidity available
in the event of an early amortization. When these conditions are not met, the early amortization
provision would be treated as non-controlled.
Determination of CCFs for controlled early amortization structures
The following method for determining CCFs applies to a securitization of revolving
credit facilities containing a controlled early amortization mechanism. When the pool of
underlying exposures includes uncommitted retail credit lines (for example, credit card
receivables), an originator would first compare the securitization's three-month average excess
spread against the following two reference levels:
A. The point at which the banking organization would be required to trap excess
spread under the terms of the securitization; and
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B. The excess spread level at which an early amortization would be triggered.
In cases where a transaction does not require excess spread to be trapped, the first trapping point
would be deemed to be 4.5 percentage points greater than the excess spread level at which an
early amortization is triggered.
The banking organization would divide the distance between the two points described
above into four equal segments. For example if the spread trapping point is 4.5 percent and the
early amortization trigger is zero percent, then 4.5 percent would be divided into four equal
segments of 112.5 basis points each. The following conversion factors, based on illustrative
segments, would apply to the investors’ interest.
Controlled Early Amortization of Uncommitted Retail Credit Lines
3-month average excess spread
450 basis points (bp) or more
Less than 450 bp to 337.5 bp
Less than 337.5 bp to 225 bp
Less than 225 bp to 112.5 bp
Less than 112.5 bp
Credit Conversion Factor (CCF)
0%
1%
2%
20%
40%
All other securitizations of revolving facilities (that is, those containing underlying
exposures that are committed or non-retail) having controlled early amortization features would
be subject to a CCF of 90 percent.
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Determination of CCFs for non-controlled early amortization structures
The process for determining CCFs when a securitization of revolving credit facilities
contains a non-controlled early amortization mechanism would be basically the same as that
described above for controlled early amortization structures, except that different CCFs would
apply to the various excess spread segments. For non-controlled structures, the following
conversion factors, based on illustrative segments, would apply:
Non-Controlled Early Amortization of Uncommitted Retail Credit Lines
3-month average excess spread
450 basis points (bp) or more
Less than 450 bp to 337.5 bp
Less than 337.5 bp to 225 bp
Less than 225 bp to 112.5 bp
Less than 112.5 bp
Credit Conversion Factor (CCF)
0%
5%
10%
50%
100%
All other securitizations of revolving credit facilities (that is, those containing underlying
exposures that are committed or non-retail) having non-controlled early amortization
mechanisms would be subject to a CCF of 100 percent. In other words, no risk transference
would be recognized for these structures; an originator’s A-IRB capital charge would be the
same as if the underlying exposures had not been securitized.
The Agencies seek comment on the proposed treatment of securitization of
revolving credit facilities containing early amortization mechanisms. Does the
proposal satisfactorily address the potential risks such transactions pose to
originators?
Comments are invited on the interplay between the A-IRB capital charge for
securitization structures containing early amortization features and that for
undrawn lines that have not been securitized. Are there common elements that the
Agencies should consider? Specific examples would be helpful.
Are proposed differences in CCFs for controlled and non-controlled amortization
mechanisms appropriate? Are there other factors that the Agencies should consider?
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Market-disruption eligible liquidity facilities
A banking organization would be able to apply a 20 percent CCF to an eligible liquidity
facility that can be drawn only in the event of a general market disruption (that is, where a capital
market instrument cannot be issued at any price), provided that any advance under the facility
represents a senior secured claim on the assets in the pool. A banking organization using this
treatment would recognize 20 percent of the A-IRB capital charge required for the facility
through use of the SFA. If the market disruption eligible liquidity facility is externally rated, a
banking organization would be able to rely on the external rating under the RBA for determining
the A-IRB capital requirement provided the organization assigns a 100 percent CCF rather than a
20 percent CCF to the facility.
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Overlapping credit enhancements or liquidity facilities
In some ABCP or similar programs, a banking organization may provide multiple
facilities that may be drawn under varying circumstances. The Agencies do not intend that a
banking organization incur duplicative capital requirements against these multiple exposures as
long as, in the aggregate, multiple advances are not permitted against the same collateral.
Rather, a banking organization would be required to hold capital only once for the exposure
covered by the overlapping facilities (whether they are general liquidity facilities, eligible
liquidity facilities, or the facilities serve as credit enhancements). Where the overlapping
facilities are subject to different conversion factors, the banking organization would attribute the
overlapping part to the facility with the highest conversion factor. However, if different banking
organizations provide overlapping facilities, each institution would hold capital against the entire
maximum amount of its facility. That is, there may be some duplication of capital charges for
overlapping facilities provided by multiple banking organizations.
Servicer cash advances
Subject to supervisory approval, servicer cash advances that are recoverable would
receive a zero percent CCF. This treatment would apply when servicers, as part of their
contracts, may advance cash to the pool to ensure an uninterrupted flow of payments to
investors, provided the servicer is entitled to full reimbursement and this right is senior to other
claims on cash flows from the pool of underlying exposures.
When providing servicer cash advances, are banking organizations obligated to
advance funds up to a specified recoverable amount? If so, does the practice
differ by asset type? Please provide a rationale for the response given.
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Credit risk mitigation
For securitization exposures covered by collateral or guarantees, the credit risk mitigation
rules discussed earlier would apply. For example, a banking organization may reduce the A-IRB
capital charge when a credit risk mitigant covers first losses or losses on a proportional basis.
For all other cases, a banking organization would assume that the credit risk mitigant covers the
most senior portion of the securitization exposure (that is, that the most junior portion of the
securitization exposure is uncovered).
V.
AMA Framework for Operational Risk
This section describes features of the proposed AMA framework for measuring the
regulatory capital requirement for operational risk. Under this framework, a banking
organization meeting the AMA supervisory standards would use its internal operational risk
measurement system to calculate its regulatory capital requirement for operational risk. The
discussion below provides background information on operational risk and the conceptual
underpinnings of the AMA, followed by a discussion of the AMA supervisory criteria.49
The Agencies’ general risk-based capital rules do not currently include an explicit capital
charge for operational risk, which is defined as the risk of loss resulting from inadequate or
failed processes, people, and systems or from external events. When developing the general
risk-based capital rules, the Agencies recognized that institutions were exposed to non-credit
related risks, including operational risk. Consequently, the Agencies built a “buffer” into the
general risk-based capital rules to implicitly cover other risks such as operational risk. With the
introduction of the A-IRB framework for credit risk in this ANPR, which results in a more risksensitive treatment of credit risk, there is no longer an implicit capital buffer for other risks.
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The Agencies recognize that operational risk is a key risk in financial institutions, and
evidence indicates that a number of factors are driving increases in operational risk. These
include the recent experience of a number of high-profile, high-severity losses across the banking
industry highlighting operational risk as a major source of unexpected losses. Because the
regulatory capital buffer for operational risk would be removed under the proposal, the Agencies
are now seeking comment on a risk-sensitive capital framework for the largest, most complex
institutions that would include an explicit risk-based capital requirement for operational risk.
The Agencies propose to require banking organizations using the A-IRB approach for credit risk
also to use the AMA to compute capital charges for operational risk.
The Agencies are proposing the AMA to address operational risk for regulatory
capital purposes. The Agencies are interested, however, in possible alternatives.
Are there alternative concepts or approaches that might be equally or more
effective in addressing operational risk? If so, please provide some discussion on
possible alternatives.
A. AMA Capital Calculation
The AMA capital requirement would be based on the measure of operational risk exposure
generated by a banking organization’s internal operational risk measurement system. In
calculating the operational risk exposure, an AMA-qualified institution would be expected to
estimate the aggregate operational risk loss that it faces over a one-year period at a soundness
standard consistent with a 99.9 percent confidence level. The institution’s AMA capital
requirement for operational risk would be the sum of EL and UL, unless the institution can
demonstrate that an EL offset would meet the supervisory criteria for operational risk. The
institution would have to use a combination of internal loss event data, relevant external loss
event data, business environment and internal control factors, and scenario analysis in calculating
49
For a more detailed discussion of the concepts set forth in this ANPR and definitions of relevant terms, see the
accompanying interagency “Supervisory Guidance on Operational Risk Advanced Measurement Approaches for
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its operational risk exposure. The institution also would be allowed to recognize the effect of
risk dependency (for example, correlation) and, to a limited extent, the effect of insurance as a
risk mitigant.
As with the proposed A-IRB capital requirement for credit risk, the operational risk
exposure would be converted to an equivalent amount of risk-weighted assets for the calculation
of an institution’s risk-based capital ratios. An AMA-qualified institution would multiply the
operational risk exposure generated by its analytical framework by a factor of 12.5 to convert the
exposure to a risk-weighted assets equivalent. The resulting figure would be added to the
comparable figures for credit and market risk in calculating the institution’s risk-based capital
denominator.
Does the broad structure that the Agencies have outlined incorporate all the key
elements that should be factored into the operational risk framework for
regulatory capital? If not, what other issues should be addressed? Are any
elements included not directly relevant for operational risk measurement or
management? The Agencies have not included indirect losses (for example,
opportunity costs) in the definition of operational risk against which institutions
would have to hold capital; because such losses can be substantial, should they be
included in the definition of operational risk?
Overview of the Supervisory Criteria
Use of the AMA would be subject to supervisory approval. A banking organization
would have to demonstrate that it has satisfied all supervisory standards before it would be able
to use the AMA for risk-based capital purposes. The supervisory standards are briefly described
below. Because an institution would have significant flexibility to develop its own methodology
for calculating its risk-based capital requirement for operational risk, it would be necessary for
supervisors to ensure that the institution’s methodology is fundamentally sound. In addition,
because different institutions may adopt different methodologies for assessing operational risk,
Regulatory Capital” (supervisory guidance) published elsewhere in today’s Federal Register.
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the requirement to satisfy supervisory standards offers some assurance to institutions and their
supervisors that all AMA-qualified institutions would be subject to a common set of standards.
While the supervisory standards are rigorous, institutions would have substantial
flexibility in terms of how they satisfy the standards in practice. This flexibility is intended to
encourage an institution to adopt a system that is responsive to its unique risk profile, foster
improved risk management, and allow for future innovation. The Agencies recognize that
operational risk measurement is evolving rapidly and wish to encourage continued evolution and
innovation. Nevertheless, the Agencies also acknowledge that this flexibility would make crossinstitution comparisons more difficult than if a single supervisory approach were to be mandated
for all institutions. The supervisory standards outlined below are intended to allow flexibility
while also being sufficiently objective to ensure consistent supervisory assessment and
enforcement of standards across institutions.
The Agencies seek comment on the extent to which an appropriate balance has
been struck between flexibility and comparability for the operational risk
requirement. If this balance is not appropriate, what are the specific areas of
imbalance and what is the potential impact of the identified imbalance?
The Agencies are considering additional measures to facilitate consistency in
both the supervisory assessment of AMA frameworks and the enforcement of AMA
standards across institutions. Specifically, the Agencies are considering
enhancements to existing interagency operational and managerial standards to
directly address operational risk and to articulate supervisory expectations for
AMA frameworks. The Agencies seek comment on the need for and effectiveness
of these additional measures.
The Agencies also seek comment on the supervisory standards. Do the standards
cover the key elements of an operational risk framework?
An institution’s operational risk framework would have to include an independent
operational risk management function, line of business oversight, and independent testing and
verification. Both the institution’s board of directors and management would have to have
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responsibilities in establishing and overseeing this framework. The institution would have to
have clear policies and procedures in place for identifying, measuring, monitoring, and
controlling operational risk.
An institution would have to establish an analytical framework that incorporates internal
operational loss event data, relevant external loss event data, assessments of the business
environment and internal control factors, and scenario analysis. The institution would have to
have standards in place to capture all of these elements. The combination of these elements
would determine the institution’s quantification of operational risk and related regulatory capital
requirement.
The supervisory standards for the AMA have both quantitative and qualitative elements.
Effective operational risk quantification is critical to the objective of a risk-sensitive capital
requirement. Consequently, a number of the supervisory standards are aimed at ensuring the
integrity of the process by which an institution arrives at its estimated operational risk exposure.
It is not sufficient, however, to focus solely on operational risk measurement. If the
Agencies are to rely on institutions to determine their risk-based capital requirements for
operational risk, there would have to be assurances that institutions have in place sound
operational risk management infrastructures. In addition, risk management elements would be
critical inputs into the quantification of operational risk exposure, that is, operational risk
quantification would have to take into account such risk management elements as the quality of
an institution’s internal controls. Likewise, the AMA capital requirement derived from an
institution’s quantification methodology would need to offer incentives for an institution to
improve its operational risk management practices. Ultimately, the Agencies believe that better
operational risk management will enhance operational risk measurement, and vice versa.
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Corporate governance
An institution’s operational risk framework would have to include an independent firmwide operational risk management function, line of business management oversight, and
independent testing and verification functions. While no specific management structure would
be mandated, all three components would have to be evident.
The institution’s board of directors would have to oversee the development of the firmwide operational risk framework, as well as major changes to the framework. Management roles
and accountability would have to be clearly established. The board and management would have
to ensure that appropriate resources have been allocated to support the operational risk
framework.
The independent firm-wide operational risk management function would be responsible
for overseeing the operational risk framework at the firm level to ensure the development and
consistent application of operational risk policies, processes, and procedures throughout the
institution. This function would have to be independent from line of business management and
the testing and verification functions. The firm-wide operational risk management function
would have to ensure appropriate reporting of operational risk exposures and loss data to the
board and management.
Lines of business would be responsible for the day-to-day management of operational
risk within each business unit. Line of business management would have to ensure that internal
controls and practices within their lines of business are consistent with firm-wide policies and
procedures that support the management and measurement of the institution’s operational risk.
The Agencies are introducing the concept of an operational risk management
function, while emphasizing the importance of the roles played by the board,
management, lines of business, and audit. Are the responsibilities delineated for
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each of these functions sufficiently clear and would they result in a satisfactory
process for managing the operational risk framework?
Operational risk management elements
An institution would have to have policies and procedures that clearly describe the major
elements of its operational risk framework, including identifying, measuring, monitoring, and
controlling operational risk. Management reports would need to be developed to address both
firm-wide and line of business results. These reports would summarize operational risk
exposure, operational loss experience, and relevant assessments of business environment and
internal control factors, and would have to be produced at least quarterly. Operational risk
reports, which summarize relevant firm-wide operational risk information, would also have to be
provided periodically to senior management and the board. An institution’s internal control
system and practice would have to be adequate in view of the complexity and scope of its
operations. In addition, an institution would be expected to meet or exceed minimum
supervisory standards as set forth in the Agencies’ supervisory policy statements and other
guidance.
B. Elements of an AMA Framework
An institution would have to demonstrate that it has adequate internal loss event data,
relevant external loss event data, assessments of business environments and internal control
factors, and scenario analysis to support its operational risk management and quantification
framework. These inputs would need to be consistent with the regulatory definition of
operational risk. The institution would have to have clear standards for the collection and
modification of operational risk inputs.
There are a number of standards that banking organizations would have to meet with
respect to internal operational loss data. Institutions would have to have at least five years of
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internal operational risk loss data captured across all material business lines, events, product
types, and geographic locations.50 An institution would have to establish thresholds above which
all internal operational losses would be captured. The New Accord introduces seven loss event
type classifications; the Agencies are proposing that an institution would not be required to
internally manage its operational risk according to these specific loss event type classifications,
but nevertheless would have to be able to map its internal loss data to these loss event categories.
The institution would have to provide consistent treatment for the timing of reporting an
operational loss in its internal data systems. As highlighted earlier in this ANPR, credit losses
caused or exacerbated by operational risk events would be treated as credit losses for regulatory
capital purposes; these would include fraud-related credit losses.
An institution would have to establish and adhere to policies and procedures that provide
for the use of relevant external loss data in the operational risk framework. External data would
be particularly relevant where an institution’s internal loss history is not sufficient to generate an
estimate of major unexpected losses. Management would have to systematically review external
data to ensure an understanding of industry experience. The Agencies seek comment on the use
of external data and its optimal function in the operational risk framework.
While internal and external data provide an important historic picture of an institution’s
operational risk profile, it is important that institutions take a forward-looking view as well.
Consequently, an institution would have to incorporate assessments of the business environment
and internal control factors (for example, audit scores, risk and control assessments, risk
indicators, etc.) into its AMA capital assessment. In addition, an institution would have to
periodically compare its assessment of these factors with actual operational loss experience.
50
With supervisory approval, a shorter initial observation period may be acceptable for institutions that are newly
authorized to use an AMA methodology.
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Another element of the AMA framework is scenario analysis. Scenario analysis is a
systematic process of obtaining expert opinions from business managers and risk management
experts to derive reasoned assessments of the likelihood and impact of plausible operational
losses consistent with the regulatory soundness standard. While scenario analysis may rely, to a
large extent, on internal or, especially, external data (for example, where an institution looks to
industry experience to generate plausible loss scenarios), it is particularly useful where internal
and external data do not generate a sufficient assessment of the institution’s operational risk
profile.
An institution would be required to have a comprehensive analytical framework that
provides an estimate of the aggregate operational loss that it faces over a one-year period at a
soundness standard consistent with a 99.9 percent confidence level. The institution would have
to document the rationale for all assumptions underpinning its chosen analytical framework,
including the choice of inputs, distributional assumptions, and weighting of quantitative and
qualitative elements. The institution would also have to document and justify any subsequent
changes to these assumptions.
An institution’s operational risk analytical framework would have to use a combination of
internal operational loss event data, relevant external operational loss event data, business
environment and control factors, as well as scenario analysis. The institution would have to
combine these elements in the manner that most effectively enables it to quantify its operational
risk exposure. The institution would have to develop an analytical framework that is appropriate
to its business model and risk profile.
Regulatory capital for operational risk would be based on the sum of EL and UL. There
may be instances where an EL offset could be recognized, but the Agencies believe that this is
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likely to be difficult given existing supervisory and accounting standards. The Agencies have
considered both reserving and budgeting as potential mechanisms for EL offsets. The use of
reserves may be hampered by accounting standards, while budgeting raises concerns about
availability over a one-year time horizon to act as a capital replacement mechanism. The
Agencies are interested in specific examples of how business practices might be used to offset
EL in the operational risk framework.
An institution would have to document how its chosen analytical framework accounts for
dependence (for example, correlation) among operational losses across and within business lines.
The institution would have to demonstrate that its explicit and embedded dependence
assumptions are appropriate, and where dependence assumptions are uncertain, the institution
would have to use conservative estimates.
An institution would be able to reduce its operational risk exposure by no more than 20
percent to reflect the impact of risk mitigants such as insurance. Institutions would have to
demonstrate that qualifying risk mitigants meet a series of criteria (described in the supervisory
guidance) to assess whether the risk mitigants are sufficiently capital-like to warrant a reduction
of the operational risk exposure.
The Agencies seek comment on the reasonableness of the criteria for recognition
of risk mitigants in reducing an institution’s operational risk exposure. In
particular, do the criteria allow for recognition of common insurance policies? If
not, what criteria are most binding against current insurance products? Other
than insurance, are there additional risk mitigation products that should be
considered for operational risk?
An institution using an AMA for regulatory capital purposes would have to use advanced
data management practices to produce credible and reliable operational risk estimates. These
practices are comparable to the data maintenance requirements set forth under the A-IRB
approach for credit risk.
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The institution would have to test and verify the accuracy and appropriateness of the
operational risk framework and results. Testing and verification would have to be done
independently of the firm-wide risk management function and the lines of business.
VI.
Disclosure
Market discipline is a key component of the New Accord. The disclosure requirements
summarized below seek to enhance the public disclosure practices, and thereby the transparency,
of advanced approach organizations. Commenters are encouraged to consult the New Accord for
specifics on the disclosure requirements under consideration. The Agencies view enhanced
market discipline as an important complement to the advanced approaches to calculating
minimum regulatory capital requirements, which would be heavily based on internal
methodologies. Increased disclosures, especially regarding a banking organization’s use of the
A-IRB approach for credit risk and the AMA for operational risk, would allow a banking
organization’s private sector investors to more fully evaluate the institution’s financial condition,
risk profile, and capital adequacy. Given better information, private shareholders and debt
holders can better influence the funding and capital costs of a banking organization. Such
actions would enhance market discipline and supplement supervisory oversight of the
organization’s risk-taking and management.
A. Overview
Disclosure requirements would apply to the bank holding company representing the top
consolidated level of the banking group. Individual banks within the holding company or
consolidated group would not generally be required to fulfill the disclosure requirements set out
below. An exception to the general rule would be that individual banks and thrifts within a
group would still be required to disclose Tier 1 and total capital ratios and their components (that
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is, Tier 1, Tier 2 and Tier 3 capital), as is the case today. In addition, all banks and thrifts would
continue to be required to submit appropriate information to regulatory authorities (for example,
Report of Condition of Income (Call Reports) or Thrift Financial Reports).51
The Agencies are proposing a set of disclosure requirements that would allow market
participants to assess key pieces of information regarding a banking group’s capital structure,
risk exposures, risk assessment processes, and ultimately, the capital adequacy of the institution.
Failure to meet these minimum disclosure requirements, if not corrected, would render a banking
organization ineligible to use the advanced approaches or would otherwise cause the banking
organization to forgo potential capital benefits arising from the advanced approaches. In
addition, other supervisory measures may be taken if appropriate.
Management would have some discretion to determine the appropriate medium and
location of the required disclosure. Disclosures made in public financial reports (for example, in
financial statements or Management’s Discussion and Analysis included in periodic reports or
SEC filings) or other regulatory reports (for example, FR Y-9C Reports), could fulfill the
applicable disclosure requirements and would not need to be repeated elsewhere. For those
disclosures that are not made under accounting or other requirements, the Agencies are seeking
comment on the appropriate means of providing this data to market participants. Institutions
would be encouraged to provide all related information in one location; at a minimum,
institutions would be required to provide a cross reference to the location of the required
disclosures.
The Agencies intend to maximize a banking organization’s flexibility regarding where to
make the required disclosures while ensuring that the information is readily available to market
51
In order to meet supervisory responsibilities, the Agencies plan to collect more detailed information through the
supervisory process or regulatory reports. Much of this information may be proprietary and accordingly would
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participants without unnecessary burden. To balance these contrasting objectives, the Agencies
are considering requiring banking organizations to provide a summary table on their public
websites that indicate where all disclosures may be found. Such an approach also would allow
institutions to cross-reference other web addresses (for example, those containing public
financial reports or regulatory reports or other risk-oriented disclosures) where certain of the
disclosures are located.
Given longstanding requirements for robust quarterly disclosure in the United States, and
recognizing the potential for rapid change in risk profiles, the Agencies intend to require that the
disclosures be made on a quarterly basis. However, qualitative disclosures that provide a general
summary of a banking organization’s risk management objectives and policies, reporting system,
and definitions would be able to be published on an annual basis, provided any significant
changes to these are disclosed in the interim. When significant events occur, banking
organizations would be required to publish material information as soon as practicable rather
than at the end of the quarter.
The risks to which banking organizations are exposed and the techniques that they use to
identify, measure, monitor, and control those risks are important factors that market participants
consider in their assessment of an institution. Accordingly, banking organizations would be
required to have a formal disclosure policy approved by the board of directors that addresses the
institution’s approach for determining the disclosures it will make. The policy also would have
to address the associated internal controls and disclosure controls and procedures. The board of
directors and senior management would have to ensure that appropriate verification of the
disclosures takes place and that effective internal controls and disclosure controls and procedures
are maintained.
not be made public.
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Consistent with sections 302 and 404 of the Sarbanes-Oxley Act of 2002, management
would have to certify to the effectiveness of internal controls over financial reporting and
disclosure controls and procedures, and the banking organization’s external auditor would have
to attest to management’s assertions with respect to internal controls over financial reporting.
The scope of these reports would need to include all information included in regulatory reports
and the disclosures outlined in this ANPR. Section 36 of the Federal Deposit Insurance Act has
similar requirements. Accordingly, banking organizations would have to implement a process
for assessing the appropriateness of their disclosures, including validation and frequency. Unless
otherwise required by accounting or auditing standards, or by other regulatory authorities, the
proposed requirements do not mandate that the new disclosures be audited by an external auditor
for purposes of opining on whether the financial statements are presented in accordance with
GAAP.
B. Disclosure Requirements
Banking organizations would be required to provide disclosures related to scope of
application, capital structure, capital adequacy, credit risk, equities in the banking book, credit
risk mitigation, asset securitization, market risk, operational risk and interest rate risk in the
banking book. The disclosure requirements are summarized below.
The required disclosures pertaining to the scope of application of the advanced
approaches would include a description of the entities found in the consolidated banking group.
Additionally, banking organizations would be required to disclose the methods used to
consolidate them, any major impediments on the transfer of funds or regulatory capital within the
banking group, and specific disclosures related to insurance subsidiaries.
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Capital structure disclosures would provide summary information on the terms and
conditions of the main features of capital instruments issued by the banking organization,
especially in the case of innovative, complex, or hybrid capital instruments. Quantitative
disclosures include the amount of Tier 1, Tier 2, and Tier 3 capital, deductions from capital, and
total eligible capital.
Capital adequacy disclosures would include a summary discussion of the banking
organization’s approach to assessing the adequacy of its capital to support current and future
activities. These requirements also include a breakdown of the capital requirements for credit,
equity, market, and operational risks. Banking organizations would also be required to disclose
their Tier 1 and total capital ratios for the consolidated group, as well as those of significant bank
or thrift subsidiaries.
For each separate risk area, a banking organization would describe its risk management
objectives and policies. Such disclosures would include an explanation of the banking
organization’s strategies and processes; the structure and organization of the relevant risk
management function; the scope and nature of risk reporting and/or measurement systems; and
the policies for hedging and/or mitigating risk and strategies and processes for monitoring the
continuing effectiveness of hedges/mitigants.
The credit risk disclosure regime is intended to enable market participants to assess the
credit risk exposure of A-IRB banking organizations and the overall applicability of the A-IRB
framework, without revealing proprietary information or duplicating the role of the supervisor in
validating the framework the banking organization has put into place.
Credit risk disclosures would include breakdowns of the banking organization’s
exposures by type of credit exposure, geographic distribution, industry or counterparty type
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distribution, residual contractual maturity, amount and type of impaired and past due exposures,
and reconciliation of changes in the allowances for exposure impairment.
Banking organizations would provide disclosures discussing the status of the regulatory
acceptance process for the adoption of the A-IRB approach, including supervisory approval of
such transition. The disclosures would provide an explanation and review of the structure of
internal rating systems and relation between internal and external ratings; the use of internal
estimates other than for A-IRB capital purposes; the process for managing and recognizing credit
risk mitigation; and, the control mechanisms for the rating system including discussion of
independence, accountability, and rating systems review. Required qualitative disclosures would
include a description of the internal ratings process and separate disclosures pertaining to the
banking organization’s wholesale, retail and equity exposures.
There would be two categories of quantitative disclosures for credit risk: those that focus
on the analysis of risk and those that focus on the actual results. Risk assessment disclosures
would include the percentage of total credit exposures to which A-IRB disclosures relate. Also,
for each portfolio except retail, the disclosures would have to provide: (1) a presentation of
exposures across a sufficient number of PD grades (including default) to allow for a meaningful
differentiation of credit risk;52 and (2) the default weighted-average LGD for each PD; and the
amount of undrawn commitments and weighted average EAD.53 For retail portfolios, banking
organization would provide either:54 (a) disclosures outlined above on a pool basis (that is, the
52 Where banking organizations are aggregating PD grades for the purposes of disclosure, this would be a
representative breakdown of the distribution of PD grades used in the A-IRB approach.
53 Banking organizations need only provide one estimate of EAD for each portfolio. However, where banking
organizations believe it is helpful, in order to give a more meaningful assessment of risk, they may also disclose
EAD estimates across a number of EAD categories, against the undrawn exposures to which these relate.
54 Banking organizations would normally be expected to follow the disclosures provided for the non-retail
portfolios. However, banking organizations would be able to adopt EL grades as the basis of disclosure where
they believe this can provide the reader with a meaningful differentiation of credit risk. Where banking
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same as for non-retail portfolios); or (b) analysis of exposures on a pool basis against a sufficient
number of EL grades to allow for a meaningful differentiation of credit risk.
Quantitative disclosures pertaining to historical results would include: actual losses (for
example, charge-offs and specific provisions) in the preceding period for each portfolio and how
this differs from past experience and a discussion of the factors that affected the loss experience
in the preceding period. In addition, disclosures would include banking organizations’ estimates
against actual outcomes over a longer period.55 At a minimum, this would include information
on estimates of losses against actual losses in each portfolio over a period sufficient to allow for
a meaningful assessment of the performance of the internal rating processes. Banking
organizations would further be expected to decompose this to provide analysis of PD, LGD and
EAD estimates against estimates provided in the quantitative risk assessment disclosures
above.56
Disclosures for banking book equity positions would include both balance sheet and fair
values, and the types and nature of investments. The total cumulative realized gains or losses
arising from sales and liquidations would be disclosed, together with total unrealized gains/losses
and any amounts included in Tier 1 and/or Tier 2 capital. Details on the equity capital
requirements would also be disclosed.
organizations are aggregating internal grades (either PD/LGD or EL) for the purposes of disclosure, this should
be a representative breakdown of the distribution of those grades used in the IRB approach.
55
For banking organizations implementing the A-IRB and AMA in 2007, the disclosures would be required from
year-end-2008; In the meantime, early adoption would be encouraged. The phased implementation is to allow
banking organizations sufficient time to build up a longer run of data that will make these disclosures
meaningful. For banking organizations that may adopt the advanced approaches at a later date, they would also
be subject to a one-year phase in period after which the disclosures would be required.
56
Banking organizations would have to provide this further decomposition where it would allow users greater
insight into the reliability of the estimates provided in the ‘quantitative disclosures: risk assessment’. In
particular, banking organizations should provide this information where there are material differences between
the PD, LGD or EAD estimates given by banking organizations compared to actual outcomes over the long run.
Banking organizations should also provide explanations for such differences.
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Disclosures relating to credit risk mitigation would include a description of the policies
and processes for netting and collateral valuation and management, and the types of collateral
accepted by the bank. Banking organizations would also be expected to include information
about the main types of guarantor or credit derivative counterparties, and any risk concentrations
arising from the use of a mitigation technique.
Securitization disclosures would summarize the banking organization’s accounting
policies for securitization activities and the current year’s securitization activity. Further,
banking organizations would be expected to disclose the names of the external credit rating
providers used for securitizations. They would also provide details of the outstanding exposures
securitized by the banking organization and subject to the securitization framework, including
impairments and losses, exposures retained or purchased broken down into risk weight banks,
and aggregate outstanding amount of securitized revolving exposures.
Disclosures for market risk would include a description of the models, stress testing, and
backtesting used in assessing market risk, as well as information on the scope of supervisory
acceptance. Quantitative disclosures would include the aggregate VaR, the high, mean, and low
VaR values over the reporting period, and a comparison of VaR estimates with actual outcomes.
A key disclosure under the operational risk framework would be a description of the
AMA the banking organization uses, including a discussion of relevant internal and external
factors considered in the banking organization’s measurement approach. In addition, the
banking organization would disclose the operational risk charge before and after any reduction in
capital resulting from the use of insurance or other potential risk mitigants.
Finally, disclosures relating to interest rate risk in the banking book would include the
nature of that risk, key assumptions made, and the frequency of risk measurement. They would
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also include the increase or decline in earnings or economic value for upward and downward rate
shocks according to management’s method for measuring interest rate risk in the banking book.
The Agencies seek comment on the feasibility of such an approach to the
disclosure of pertinent information and also whether commenters have
any other suggestions regarding how best to present the required
disclosures.
Comments are requested on whether the Agencies’ description of the
required formal disclosure policy is adequate, or whether additional
guidance would be useful.
Comments are requested regarding whether any of the information sought
by the Agencies to be disclosed raises any particular concerns regarding
the disclosure of proprietary or confidential information. If a commenter
believes certain of the required information would be proprietary or
confidential, the Agencies seek comment on why that is so and alternatives
that would meet the objectives of the required disclosure.
The Agencies also seek comment regarding the most efficient means for
institutions to meet the disclosure requirements. Specifically, the Agencies are
interested in comments about the feasibility of requiring institutions to provide all
requested information in one location and also whether commenters have other
suggestions on how to ensure that the requested information is readily available
to market participants.
VII. REGULATORY ANALYSIS
Federal agencies are required to consider the costs, benefits, or other effects of their
regulations for various purposes described by statute or executive order. In particular, an
executive order and several statutes may require the preparation of detailed analyses of the costs,
benefits, or other effects of rules, depending on threshold determinations as to whether the
rulemaking in question triggers the substantive requirements of the applicable statute or
executive order.
For the reasons described above, the proposed and final rules that the Agencies may issue
to implement the New Accord would represent a significant change to their current approach to
the measurement of regulatory capital ratios, and the supervision of institutions’ internal risk
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management processes with respect to capital allocations. First, in this ANPR, core and opt-in
banks would rely on their own analyses to derive some of the principal inputs that would
determine their regulatory capital requirements. Core and opt-in banks would incur new costs to
create and refine their internal systems and to attract and train the staff expertise necessary to
develop, oversee, manage and test those systems. Second, the measured regulatory capital ratios
(although not the minimums) would likely change, perhaps substantially for core and opt-in
banks. Third, the Agencies' approach to supervising capital adequacy would become bifurcated;
that is, general banks would continue to use the Agencies' existing regulatory capital rules, either
in their current form or as modified. As a result, there may be significant differences in the
regulatory capital assigned to a particular type of asset depending on whether the bank is a core,
opt-in, or general bank. To the extent that an institution’s product mix would be directly affected
by a change in the landscape of regulatory capital requirements, this might also affect the
customers of those institutions due to the changes in pricing and market strategies.
The economic impact that would be created by these possibly unforeseen competitive
effects is difficult to estimate, and the Agencies encourage comment. In particular, the Agencies
are interested in comments on the competitive impact that a change in the regulatory capital
regime applied to large institutions would have relative to the competitive position of smaller
institutions that remain subject to the general risk-based capital rules. Conversely, if the
regulatory burden of the more prescriptive A-IRB approach applied to core institutions were so
large as to offset the potential for a lower measured capital requirement for certain exposures,
then the competitive position of large institutions, with respect to both their domestic and
international competitors, might be worsened. The Agencies are also interested in comments
that address the competitive position of regulated institutions in the United States with respect to
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financial service providers, both domestic and foreign, that are not subject to the same degree of
regulatory oversight.
None of the Agencies has yet made the threshold determinations required by executive
order or statute with respect to this ANPR. Because the proposed approaches to assessing capital
adequacy described in this ANPR are new, the Agencies currently lack information that is
sufficiently specific or complete to permit those determinations to be made or to prepare any
economic analysis that may ultimately be required. Therefore, this section of the ANPR
describes the relevant executive order and statutes, and asks for comment and information that
will assist in the determination of whether such analyses would be necessary before the Agencies
published proposed or final rules.
Quantitative information would be the most useful to the Agencies. However,
commenters may also provide estimates of costs, benefits, or other effects, or any other
information they believe would be useful to the Agencies in making the determinations. In
addition, commenters are asked to identify or estimate start-up, or non-recurring, costs separately
from costs or effects they believe would be ongoing.
A. Executive Order 12866
Executive Order 12866 requires preparation of an economic analysis for agency actions
that are "significant regulatory actions." "Significant regulatory actions" include, among other
things, regulations that "have an annual effect on the economy of $100 million or more or
adversely affect in a material way the economy, a sector of the economy, productivity,
competition, jobs, the environment, public health or safety, or state, local, or tribal governments
or communities . . . ." 57 Regulatory actions that satisfy one or more of these criteria are called
57
Executive Order 12866 (Sept. 30, 1993), 58 FR 51735 (Oct. 4, 1993), as amended by Executive Order 13258, 67
FR 9385 [referred to hereafter as E.O. 12866]. For the complete text of the definition of "significant regulatory
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"economically significant regulatory actions." E.O. 12866 applies to the OCC and the OTS, but
not the Board or the FDIC. If the OCC or the OTS determines that the rules implementing the
New Accord comprise an "economically significant regulatory action," then the agency making
that determination would be required to prepare and submit to the Office of Management and
Budget's (OMB) Office of Information and Regulatory Affairs (OIRA) an economic analysis that
includes:
•
a description of the need for the rules and an explanation of how they will meet the need;
•
an assessment of the benefits anticipated from the rules (for example, the
promotion of the efficient functioning of the economy and private markets)
together with, to the extent feasible, a quantification of those benefits;
•
an assessment of the costs anticipated from the rules (for example, the direct cost
both to the government in administering the regulation and to businesses and
others in complying with the regulation, and any adverse effects on the efficient
functioning of the economy, private markets (including productivity,
employment, and competitiveness)), together with, to the extent feasible, a
quantification of those costs; and
•
an assessment of the costs and benefits of potentially effective and reasonably
feasible alternatives to the planned regulation (including improving the current
regulation and reasonably viable nonregulatory actions), and an explanation why
action," see E.O. 12866 at § 3(f). A "regulatory action" is "any substantive action by an agency (normally
published in the Federal Register) that promulgates or is expected to lead to the promulgation of a final rule or
regulation, including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed
rulemaking." E.O. 12866 at § (e).
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the planned regulatory action is preferable to the identified potential
alternatives.58
For purposes of determining whether this rulemaking would constitute an "economically
significant regulatory action," as defined by E.O. 12866, and to assist any economic analysis that
E.O. 12866 may require, the OCC and the OTS encourage commenters to provide information
about:
•
the direct and indirect costs, for core banks and those banks who intend to qualify as optin banks, of compliance with the approach described in this ANPR and the related
supervisory guidance;
•
the costs, for general banks, of adopting the approach;
•
the effects on regulatory capital requirements for core, opt-in, and general banks;
•
the effects on competitiveness, in both domestic and international markets, for core, optin, and general banks. This would include the possible effects on the customers served
by these U.S. institutions through changes in the mix of product offerings and prices;
•
the economic benefits of the approach for core, opt-in, or general banks, as measured by
lower regulatory capital ratios, and a potentially more efficient allocation of capital. This
might also include estimates of savings associated with regulatory capital arbitrage
transactions that are currently undertaken in order to optimize return on capital under the
current capital regime. That is, what estimates might exist to quantify the improvements
in market efficiency form no longer pursuing regulatory capital arbitrage transactions?
58
The components of the economic analysis are set forth in E.O. 12866 § 6(a)(3)(C)(i)-(iii). For a description of the
methodology that OMB recommends for preparing an economic analysis, see Office of Management and
Budget, "Economic Analysis of Federal Regulations Under Executive Order 12866" (January 11, 1996). This
publication is available on OMB's website at www.whitehouse.gov/omb/inforeg/riaguide.html. OMB recently
published revisions to this publication for comment. See 68 FR 5492 (February 3, 2003).
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•
the features of the A-IRB approach that provide an incentive for a bank to seek to
qualify to use it, that is, to become an opt-in bank.
The OCC and the OTS also encourage comment on any alternatives to the
regulatory approaches described in the ANPR that the Agencies should consider.
B. Regulatory Flexibility Act
The Regulatory Flexibility Act (RFA) generally requires agencies to prepare a
"regulatory flexibility analysis" unless the head of the agency certifies that a regulation will not
"have a significant economic impact on a substantial number of small entities." 59 The RFA
applies to all of the Agencies.
The Agencies understand that the RFA has been construed to require consideration only
of the direct impact on small entities.60 The Small Business Administration (SBA) has said:
"The courts have held that the RFA requires an agency to perform a regulatory flexibility
analysis of small entity impacts only when a rule directly regulates them," that is, when it
directly applies to them.61 Since the proposed approach would directly apply to only a limited
number of large banking organizations, it would appear that the Agencies may certify that the
issuance of this ANPR would not have significant economic impact on a substantial number of
small entities.
Do the potential advantages of the A-IRB approach, as measured by the specific capital
requirements on lower-risk loans, create a competitive inequality for small institutions, which are
59
The RFA is codified at 5 U.S.C. 601 et seq.
With respect to banks, the Small Business Administration (SBA) has defined a small entity to be a bank with total
assets of $150 million or less. 13 C.F.R. § 121.201.
61
SBA Office of Advocacy, A Guide for Government Agencies, "How to Comply with the Regulatory Flexibility
Act (May 2003), at 20 (emphasis added). See also Mid-Tex Electric Cooperative, Inc. v. FERC, 773 F.2d 327,
340-43 (D.C. Cir. 1985) ("[W]e conclude that an agency may properly certify that no regulatory flexibility
analysis is necessary when it determines that the rule will not have a significant economic impact on a
substantial number of small entities that are subject to the requirements of the rule.") (emphasis added)
(construing language in the RFA that was unchanged by subsequent statutory amendments).
60
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effectively precluded from adopting the A-IRB due to stringent qualification standards?
Conversely, would small institutions that remain on the general risk-based capital rules be at a
competitive advantage from specific capital requirements on higher risk assets vis-à-vis
advanced approach institutions? How might the Agencies estimate the effect on credit
availability to small businesses or retail customers of general banks?
C. Unfunded Mandates Reform Act
The Unfunded Mandates Reform Act of 1995 (UMRA) requires preparation of a written
budgetary impact statement before promulgation of any rule likely to result in a "Federal
mandate" that "may result in the expenditure by State, local, and tribal governments, in the
aggregate, or by the private sector, of $100,000,000 or more (adjusted annually for inflation) in
any 1 year."62 A "Federal mandate" includes any regulation "that would impose an enforceable
duty upon the private sector. . . ." If a budgetary impact statement is required, the UMRA further
requires the agency to identify and consider a reasonable number of regulatory alternatives
before promulgating the rule in question. The UMRA applies to the OCC and the OTS, but not
the Board or the FDIC.
The OCC and the OTS have asked for comments and information from core and opt-in
banks on compliance costs and, generally, on alternative regulatory approaches, for purposes of
evaluating what actions they need to take in order to comply with E.O. 12866. That same
information (with cost information adjusted annually for inflation) is relevant to those agencies'
determination of whether a budgetary impact statement is necessary pursuant to the UMRA.
Commenters are therefore asked to be mindful of the UMRA requirements when they provide
information about compliance costs and in suggesting alternatives to the approach described in
this ANPR.
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D. Paperwork Reduction Act
Each of the Agencies is subject to the Paperwork Reduction Act of 1995 (PRA).63 The
PRA requires burden estimates that will likely be based on some of the same information that is
necessary to prepare an economic analysis under E.O. 12866 or an estimate of private sector
expenditures pursuant to the UMRA.
In particular, an agency may not "conduct or sponsor" a collection of information without
conducting an analysis that includes an estimate of the "burden" imposed by the collection. A
collection of information includes, essentially, the eliciting of identical information – whether
through questions, recordkeeping requirements, or reporting requirements – from 10 or more
persons. "Burden" means the "time, effort, or financial resources expended by persons to
generate, maintain, or provide information" to the agency. The rulemaking initiated by this
ANPR will likely impose requirements, either in the regulations themselves or as part of
interagency implementation guidance, that are covered by the PRA. In order to estimate burden,
the Agencies will need to know, for example, the cost – in terms of time and money – that
mandatory and opt-in banks would have to expend to develop and maintain the systems,
procedures, and personnel that compliance with the rules would require. With this in mind, to
assist in their analysis of the treatment of retail portfolios and other exposures, the Agencies
intend to request from U.S. institutions additional quantitative data for which confidential
treatment may be requested in accordance with the Agencies’ applicable rules.
While it will be difficult to identify those requirements with precision before a proposed
rule is issued, this notice and the draft supervisory guidance published elsewhere in today’s
Federal Register generally describes aspects of the Agencies' implementation of the revised
62
63
The Unfunded Mandates Reform Act is codified at 2 U.S.C. 1532 et seq.
44 U.S.C. § 3501 et seq.
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Basel accord where new reporting and recordkeeping requirements would be likely.
Commenters are asked to provide any estimates they can reasonably derive about the time, effort,
and financial resources that will be required to provide the Agencies with the requisite plans,
reports, and records that are described in this notice and in the supervisory guidance.
Commenters also are requested to identify any activities that will be conducted as a result from
the capital and methodological standards in the framework presented in this ANPR that would
impose new recordkeeping or reporting burden. Commenters should specify whether certain
capital and methodological standards would necessitate the acquisition or development of new
compliance/ information systems or the significant modification of existing
compliance/information systems.
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List of Acronyms
ABCP
ADC
AIG
A-IRB
ALLL
AMA
ANPR
BIS
BSC
CCF
CEDE
CF
CRE
CRM
EAD
EL
FFIEC
FMI
GAAP
HVCRE
IMF
IRB
KIRB
LGD
M
MDB
OF
OTC
PCA
PD
PDF
PF
PFE
PMI
PRA
PSE
QIS3
QRE
R
RBA
RFA
S
SBIC
Asset-Backed Commercial Paper
Acquisition, Development, and Construction
Accord Implementation Group
Advanced Internal Ratings-Based (approach for credit risk)
Allowance for Loan and Lease Losses
Advanced Measurement Approach (for operational risk)
Advance Notice of Proposed Rulemaking
Bank for International Settlements
Basel Committee on Banking Supervision
Credit Conversion Factor
Community and Economic Development Entity
Commodities Finance
Commercial Real Estate
Credit Risk Mitigation
Exposure at Default
Expected Loss
Federal Financial Institutions Examination Council
Future Margin Income
Generally Accepted Accounting Principles
High Volatility Commercial Real Estate
International Monetary Fund
Internal Ratings-Based
Capital for Underlying Pool of Exposures (securitizations)
Loss Given Default
Maturity
Multilateral Development Bank
Object Finance
Over-the-Counter (derivatives)
Prompt Corrective Action (regulation)
Probability of Default
Probability Density Function
Project Finance
Potential Future Exposure
Private Mortgage Insurance
Paperwork Reduction Act
Public-Sector Entity
Third Quantitative Impact Study
Qualifying Revolving Exposures
Asset Correlation
Ratings-Based Approach (securitizations)
Regulatory Flexibility Act
Borrower-Size
Small Business Investment Company
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SFA
SL
SME
SPE
SSC
UL
UMRA
VaR
Supervisory Formula Approach (securitizations)
Specialized Lending
Small- to Medium-Sized Enterprise
Special Purpose Entity
Supervisory Slotting Criteria
Unexpected Loss
Unfunded Mandates Reform Act
Value at Risk (model)
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[THIS SIGNATURE PAGE RELATES TO THE JOINT ADVANCE NOTICE OF
PROPOSED RULEMAKING ON “RISK-BASED CAPITAL GUIDELINES; INTERNAL
RATINGS-BASED CAPITAL REQUIREMENT”]
_______________________
Date
__________________________________
John D. Hawke, Jr.
Comptroller of the Currency
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[THIS SIGNATURE PAGE RELATES TO THE JOINT ADVANCE NOTICE OF PROPOSED
RULEMAKING ON “RISK-BASED CAPITAL GUIDELINES; INTERNAL RATINGSBASED CAPITAL REQUIREMENT]
By order of the Board of Governors of the Federal Reserve System (INSERT DATE HERE]
Jennifer J. Johnson
Secretary of the Board
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[THIS SIGNATURE PAGE RELATES TO THE JOINT ADVANCE NOTICE OF PROPOSED
RULEMAKING ON “RISK-BASED CAPITAL GUIDELINES; INTERNAL RATINGSBASED CAPITAL REQUIREMENT]
By order of the Board of Directors.
Dated at Washington, DC, this day of
Federal Deposit Insurance Corporation
2003.
Robert E. Feldman,
Executive Secretary.
(SEAL)
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[THIS SIGNATURE PAGE RELATES TO THE JOINT ADVANCE NOTICE OF PROPOSED
RULEMAKING ON “RISK-BASED CAPITAL GUIDELINES; INTERNAL RATINGSBASED CAPITAL REQUIREMENT]
Dated:
2003.
Director, Office of Thrift Supervision
183
Attachment 2
Draft Supervisory Guidance on
Internal Ratings-Based Systems
for Corporate Credit
Draft Date: July 1, 2003
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CONTENTS
INTRODUCTION ..............................................................................................187
PURPOSE .................................................................................................................................. 187
OVERVIEW OF SUPERVISORY EXPECTATIONS .............................................................................. 188
Ratings Assignment ............................................................................................................ 189
Quantification ...................................................................................................................... 190
Data Maintenance............................................................................................................... 190
Control and Oversight Mechanisms.................................................................................... 191
SCOPE OF GUIDANCE ................................................................................................................ 192
TIMING ...................................................................................................................................... 192
CHAPTER 1: RATINGS FOR IRB SYSTEMS...................................................193
I. OVERVIEW ............................................................................................................................. 193
II. CREDIT RATINGS ................................................................................................................... 193
Rating Assignment Techniques .......................................................................................... 194
1. Expert Judgment......................................................................................................... 194
2. Models ........................................................................................................................ 195
3. Constrained Judgment ............................................................................................... 196
III. IRB RATINGS SYSTEM ARCHITECTURE .................................................................................. 196
A. Two-Dimensional Rating System ................................................................................... 196
Definition of Default ........................................................................................................ 197
Obligor Ratings............................................................................................................... 198
Loss Severity Ratings..................................................................................................... 202
B. Other Considerations of IRB Rating System Architecture............................................. 204
Timeliness of Ratings ..................................................................................................... 204
Multiple Ratings Systems ............................................................................................... 204
Recognition of the Risk Mitigation Benefits of Guarantees ............................................ 205
C. Validation Process......................................................................................................... 205
1. Ratings System Developmental Evidence................................................................. 207
2. Ratings System Ongoing Validation .......................................................................... 208
3. Back Testing .............................................................................................................. 210
CHAPTER 2: QUANTIFICATION OF IRB SYSTEMS.......................................211
I. INTRODUCTION ....................................................................................................................... 211
A. Stages of the Quantification Process ............................................................................. 211
B. General Principles for Sound IRB Quantification ........................................................... 213
II. PROBABILITY OF DEFAULT (PD).............................................................................................. 216
A. Data ................................................................................................................................ 216
B. Estimation ....................................................................................................................... 217
C. Mapping.......................................................................................................................... 220
D. Application...................................................................................................................... 224
III. LOSS GIVEN DEFAULT (LGD) ................................................................................................ 227
A. Data ................................................................................................................................ 227
B. Estimation ....................................................................................................................... 229
C. Mapping.......................................................................................................................... 232
D. Application...................................................................................................................... 233
IV. EXPOSURE AT DEFAULT (EAD) ............................................................................................. 234
A. Data ................................................................................................................................ 234
B. Estimation ....................................................................................................................... 235
C. Mapping.......................................................................................................................... 236
D. Application...................................................................................................................... 237
V. MATURITY (M)....................................................................................................................... 238
VI. VALIDATION .......................................................................................................................... 240
APPENDIX TO CHAPTER 2: ILLUSTRATIONS OF THE QUANTIFICATION PROCESS ............................. 243
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CHAPTER 3: DATA MAINTENANCE ...............................................................248
I. OVERVIEW.............................................................................................................................. 248
II. DATA MAINTENANCE FRAMEWORK .......................................................................................... 249
Life Cycle Tracking ............................................................................................................. 249
Rating Assignment Data ..................................................................................................... 250
Example Data Elements ..................................................................................................... 250
III. DATA ELEMENT FUNCTIONS .................................................................................................. 253
Validation and Refinement.................................................................................................. 253
Developing Parameter Estimates ....................................................................................... 254
Applying Rating System Improvements Historically ........................................................... 254
Calculating Capital Ratios and Reporting to the Public ...................................................... 256
Supporting Risk Management............................................................................................. 256
IV. MANAGING DATA QUALITY AND INTEGRITY .............................................................................. 256
Documentation and Definitions........................................................................................... 256
Electronic Storage............................................................................................................... 257
Data Gaps ........................................................................................................................... 257
CHAPTER 4: CONTROL AND OVERSIGHT MECHANISMS...........................258
I. OVERVIEW ............................................................................................................................. 258
II. INDEPENDENCE IN THE RATING APPROVAL PROCESS ............................................................... 260
III. TRANSPARENCY ................................................................................................................... 262
IV. ACCOUNTABILITY .................................................................................................................. 263
A. Responsibility for Assigning Ratings .............................................................................. 264
B. Responsibility for Rating System Performance .............................................................. 264
V. USE OF RATINGS .................................................................................................................. 264
VI. RATING SYSTEM REVIEW (RSR) ........................................................................................... 265
VII. INTERNAL AUDIT .................................................................................................................. 266
External Audit...................................................................................................................... 267
VIII. CORPORATE OVERSIGHT .................................................................................................... 267
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Introduction
Purpose
1.
This document describes supervisory expectations for banking
organizations (institutions) adopting the advanced internal ratings-based
approach (IRB) for the determination of minimum regulatory risk-based capital
requirements. The focus of this guidance is corporate credit portfolios. Retail,
commercial real estate, securitizations, and other portfolios will be the focus of
later guidance. This draft guidance should be considered with the advance
notice of proposed rulemaking (ANPR) on revisions to the risk-based capital
standard as published in the Federal Register on July______ no.____________.
2.
The primary objective of IRB is to enhance the sensitivity of regulatory
capital requirements to credit risk. To accomplish that objective, IRB harnesses a
bank’s own risk rating and quantification capabilities. In general, the IRB
approach reflects and extends recent developments in risk management and
banking supervision. However, the degree to which any individual bank will need
to modify its own credit risk management practices to deliver accurate and
consistent IRB risk parameters will vary from institution to institution.
3.
This guidance is intended to provide supervisors and institutions with a
clear description of the essential components and characteristics of an
acceptable IRB framework. Toward that end, this document sets forth IRB
system supervisory standards that are highlighted in bold and designated by the
prefix “S.” Whenever possible, these supervisory standards are principle-based
to enable institutions to implement the framework flexibly. However, when
prudential concerns or the need for standardization override the desire for
flexibility, the supervisory standards are more detailed. Ultimately, institutions
must have credit risk management practices that are consistent with the
substance and spirit of the standards in this guidance.
4.
The IRB conceptual framework outlined in this document is intended
neither to dictate the precise manner by which institutions should seek to meet
supervisory expectations, nor to provide technical guidance on how to develop
such a framework. As institutions develop their IRB systems in anticipation of
adopting them for regulatory capital purposes, supervisors will be evaluating, on
an individual bank basis, the extent to which institutions meet the standards
outlined in this document. In evaluating institutions, supervisors will rely on this
supervisory guidance as well as examination procedures, which will be
developed separately. This document assumes that readers are familiar with the
proposed IRB approach to calculating minimum regulatory capital articulated in
the ANPR.
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Overview of Supervisory Expectations
5.
Rigorous credit risk measurement is a necessary element of advanced risk
management. Qualifying institutions will use their internal rating systems to
associate a probability of default (PD) with each obligor grade, as well as a loss
given default (LGD) with each credit facility. In addition, institutions will estimate
exposure at default (EAD) and will calculate the effective remaining maturity (M)
of credit facilities.
6.
Qualifying institutions will be expected to have an IRB system consisting of
four interdependent components:
•
A system that assigns ratings and validates their accuracy (Chapter 1),
•
A quantification process that translates risk ratings into IRB parameters
(Chapter 2),
•
A data maintenance system that supports the IRB system (Chapter 3),
and,
•
Oversight and control mechanisms that ensure the system is
functioning as intended and producing accurate ratings (Chapter 4).
Together these rating, quantification, data, and oversight mechanisms present a
framework for defining and improving the evaluation of credit risk.
7.
It is expected that rating systems will operate dynamically. As ratings are
assigned, quantified and used, estimates will be compared with actual results
and data will be maintained and updated to support oversight and validation
efforts and to better inform future estimates. The rating system review and
internal audit functions will serve as control mechanisms that ensure that the
process of ratings assignment and quantification function according to policy and
design and that noncompliance and weaknesses are identified, communicated to
senior management and the board, and addressed. Rating systems with
appropriate data and oversight feedback mechanisms foster a learning
environment that promotes integrity in the rating system and continuing
refinement.
8.
IRB systems need the support and oversight of the board and senior
management to ensure that the various components fit together seamlessly and
that incentives to make the system rigorous extend across line, risk management,
and other control groups. Without strong board and senior management support
and involvement, rating systems are unlikely to provide accurate and consistent
risk estimates during both good and bad times.
9.
The new regulatory minimum capital requirement is predicated on an
institution’s internal systems being sufficiently advanced to allow a full and
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accurate assessment of its risk exposures. Under the new framework, an
institution could experience a considerable capital shortfall in the most difficult of
times if its risk estimates are materially understated. Consequently, the IRB
framework demands a greater level of validation work and controls than
supervisors have required in the past. When properly implemented, the new
framework holds the potential for better aligning minimum capital requirements
with the risk taken, pushing capital requirements higher for institutions that
specialize in riskier types of lending, and lower for those that specialize in safer
risk exposures.
10.
Supervisors will evaluate compliance with the supervisory standards for
each of the four components of an IRB system. However, evaluating compliance
with each of the standards individually will not be sufficient to determine an
institution’s overall compliance. Rather, supervisors and institutions must also
evaluate how well the various components of an institution’s IRB system
complement and reinforce one another to achieve the overall objective of
accurate measures of risk. In performing their evaluation, supervisors will need
to exercise considerable supervisory judgment, both in evaluating the individual
components and the overall IRB framework. A summary of the key supervisory
expectations for each of the IRB components follows.
Ratings Assignment
11.
The first component of an IRB system involves the assignment and
validation of ratings (see Chapter 1). Ratings must be accurately and consistently
applied to all corporate credit exposures and be subject to initial and ongoing
validation. Institutions will have latitude in designing and operating IRB rating
systems subject to five broad standards:
Two-dimensional risk-rating system – IRB institutions must be able to make
meaningful and consistent differentiations among credit exposures along
two dimensions—obligor default risk and loss severity in the event of a
default.
Rank order risks – IRB institutions must rank obligors by their likelihood of
default, and facilities by the loss severity expected in default.
Calibration – IRB obligor ratings must be calibrated to values of the
probability of default (PD) parameter and loss severity ratings must be
calibrated to values of the loss given default (LGD) parameter.
Accuracy – Actual long-run actual default frequencies for obligor rating
grades must closely approximate the PDs assigned to those grades and
realized loss rates on loss severity grades must closely approximate the
LGDs assigned to those grades.
Validation process – IRB institutions must have ongoing validation
processes for rating systems that include the evaluation of developmental
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evidence, process verification, benchmarking, and the comparison of
predicted parameter values to actual outcomes (back-testing).
Quantification
12.
The second component of an IRB system is a quantification process (see
Chapter 2). Since obligor and facility ratings may be assigned separately from
the quantification of the associated PD and LGD parameters, quantification is
addressed as a separate process. The quantification process must produce
values not only for PD and LGD but also for EAD and for the effective remaining
maturity (M). The quantification of those four parameters is expected to be the
result of a disciplined process. The key considerations for effective quantification
are as follows:
Process – IRB institutions must have a fully specified process covering all
aspects of quantification (reference data, estimation, mapping, and
application).
Documentation – The quantification process, including the role and scope
of expert judgment, must be fully documented and updated periodically.
Updating – Parameter estimates and related documentation must be
updated regularly.
Review – A bank must subject all aspects of the quantification process,
including design and implementation, to an appropriate degree of
independent review and validation.
Constraints on Judgment – Judgmental adjustments may be an
appropriate part of the quantification process, but must not be biased
toward lower risk estimates.
Conservatism – Parameter estimates must incorporate a degree of
conservatism that is appropriate for the overall robustness of the
quantification process.
Data Maintenance
13.
The third component of an IRB system is an advanced data management
system that produces credible and reliable risk estimates (see Chapter 3). The
broad standard governing an IRB data maintenance system is that it supports the
requirements for the other IRB system components, as well as the institution’s
broader risk management and reporting needs. Institutions will have latitude in
managing their data, subject to the following key data maintenance standards:
Life Cycle Tracking – Institutions must collect, maintain, and analyze
essential data for obligors and facilities throughout the life and disposition
of the credit exposure.
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Rating Assignment Data – Institutions must capture all significant
quantitative and qualitative factors used to assign the obligor and loss
severity rating.
Support of IRB System – Data collected by institutions must be of sufficient
depth, scope, and reliability to:
•
•
•
•
•
•
•
•
Validate IRB system processes,
Validate parameters,
Refine the IRB system,
Develop internal parameter estimates,
Apply improvements historically,
Calculate capital ratios,
Produce internal and public reports, and
Support risk management.
Control and Oversight Mechanisms
14.
The fourth component of an IRB system is comprised of control and
oversight mechanisms that ensure that the various components of the IRB
system are functioning as intended (see Chapter 4). Given the various uses of
internal risk ratings, including their direct link to regulatory capital requirements,
there is enormous, sometimes conflicting, pressure on banks’ internal rating
systems. Control structures are subject to the following broad standards:
Interdependent System of Controls – IRB institutions must implement a
system of interdependent controls that include the following elements:
•
•
•
•
•
•
•
Independence,
Transparency,
Accountability,
Use of ratings,
Rating system review,
Internal audit, and
Board and senior management oversight.
Checks and Balances – Institutions must combine the various control
mechanisms in a way that provides checks and balances for ensuring IRB
system integrity.
15.
The system of oversight and controls required for an effective IRB system
may operate in various ways within individual institutions. This guidance does
not prescribe any particular organizational structure for IRB oversight and control
mechanisms. Banks have broad latitude to implement structures that are most
effective for their individual circumstances, as long as those structures support
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and enhance the institution’s ability to satisfy the supervisory standards
expressed in this document.
Scope of Guidance
16.
This draft guidance reflects work performed by supervisors to evaluate and
compare current practices at institutions with the concepts and requirements for
an IRB framework. For instances in which a range of practice was observable,
examples are provided on how certain practices may or may not qualify.
However, in many other instances, practices were at such an early stage of
development that it was not feasible to describe specific examples. In those
cases, requirements tend to be principle-based and without examples.
Given that institutions are still in the early stages of developing qualifying IRB
systems, it is expected that this guidance will evolve over time to more explicitly
take into account new and improving practices.
Timing
S.
An IRB system must be operating fully at least one year prior to the
institution’s intended start date for the advanced approach.
17.
As noted in the ANPR, the significant challenge of implementing a fully
complying IRB system requires that institutions and supervisors have sufficient
time to observe whether the IRB system is delivering risk-based capital figures
with a high level of integrity. The ability to observe the institution’s ratings
architecture, validation, data maintenance and control functions in a fully
operating environment prior to implementation will help identify how well the IRB
system design functions in practice. This will be particularly important given that
in the first year of implementation institutions will not only be subject to the new
minimum capital requirements, but will also be disclosing risk-based capital ratios
for the public to rely upon in the assessment of the institution’s financial health.
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Chapter 1: Ratings for IRB Systems
I. Overview
18.
This chapter describes the design and operation of risk-rating systems that
will be acceptable in an internal ratings-based (IRB) framework. Banks will have
latitude in designing and operating IRB rating systems, subject to five broad
standards:
Two-dimensional risk-rating system – IRB institutions must be able to make
meaningful and consistent differentiations among credit exposures along
two dimensions—obligor default risk and loss severity in the event of a
default.
Rank order risks – IRB institutions must rank obligors by their likelihood of
default, and facilities by the loss severity expected in default.
Calibration – IRB obligor ratings must be calibrated to values of the
probability of default (PD) parameter and loss severity ratings must be
calibrated to values of the loss given default (LGD) parameter.
Accuracy – Actual long-run actual default frequencies for obligor rating
grades must closely approximate the PDs assigned to those grades and
actual loss rates on loss severity grades must closely approximate the
LGDs assigned to those grades.
Validation process – IRB institutions must have ongoing validation
processes for rating systems that include the evaluation of developmental
evidence, process verification, benchmarking, and the comparison of
predicted parameter values to actual outcomes (back-testing).
II. Credit Ratings
19.
In general, a credit rating is a summary indicator of the relative risk on a
credit exposure. Credit ratings can take many forms. The most widely known
credit ratings are the public agency ratings, which are expressed as letters; bank
internal ratings tend to be expressed as whole numbers – for example, 1 through
10. Some rating model outputs are expressed in terms of probability of default or
expected default frequency, in which case they may be more than relative
measures of risk. Regardless of the form, meaningful credit ratings share two
characteristics:
•
•
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They group credits to discriminate among possible outcomes.
They rank the perceived levels of credit risk.
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20.
Banks have used credit ratings of various types for a variety of purposes.
Some ratings are intended to rank obligors by risk of default and some are
intended to rank facilities1 by expected loss, which incorporates risk of default
and loss severity. Bank rating systems that are geared solely to expected loss
will need to be amended to meet the two-dimensional requirements of the IRB
approach.
Rating Assignment Techniques
21.
Banks use different techniques, such as expert judgment and models, to
assign credit risk ratings. For banks using the IRB approach, how ratings are
assigned is important because different techniques will require different validation
processes and control mechanisms to ensure the integrity of the rating system.
To assist the discussion of rating architecture requirements, described below are
some of the current rating assignment techniques. Any of these techniques –
expert judgment, models, constrained judgment, or a combination thereof – could
be acceptable within an IRB system, provided the bank meets the standards
outlined in this document.
1. Expert Judgment
22.
Historically, banks have used expert judgment to assign ratings to
commercial credits. With this technique, an individual weighs relevant
information and reaches a conclusion about the appropriate risk rating.
Presumably, the rater makes informed judgments based on knowledge gained
through experience and training.
23.
The key feature of expert-judgment systems is flexibility. The prevalence
of judgmental rating systems reflects the view that the determinants of default are
too complicated to be captured by a single quantitative model. The quality of
management is often cited as an example of a risk determinant that is difficult to
assess through a quantitative model. In order to foster internal consistency,
banks employing expert judgment rating systems typically provide narrative
guidelines that set out ratings criteria. However, the expert must decide how
narrative guidelines apply to a given set of circumstances.
24.
The flexibility possible in the assignment of judgmental ratings has
implications for the types of ratings review that are feasible. As part of the ratings
validation process, banks will attempt to confirm that raters follow bank policy.
However, two individuals exercising judgment can use the same information to
support different ratings. Thus, the review of an expert judgment rating system
will require an expert who can identify the impact of policy and the impact of
judgment on a rating.
1
Facilities – loans, lines, or other separate extensions of credit to an obligor.
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2. Models
25.
In recent years, models have been developed for use in rating commercial
credits. In a model-based approach, inputs are numeric and provide quantitative
and qualitative information about an obligor. The inputs are combined using
mathematical equations to produce a number that is translated into a categorical
rating. An important feature of models is that the rating is perfectly replicable by
another party, given the same inputs.
26.
The models used in credit rating can be distinguished by the techniques
used to develop them. Some models may rely on statistical techniques while
others rely on expert-judgment techniques.
Statistical models. Statistically developed models are the result of
statistical optimization, in which well-defined mathematical criteria are
used to choose the model that has the closest fit to the observed data.
Numerous techniques can be used to build statistical models; regression
is one widely recognized example. Regardless of the specific statistical
technique, a knowledgeable independent reviewer will have to exercise
judgment in evaluating the reasonableness of a model’s development,
including its underlying logic, the techniques used to handle the data, and
the statistical model building techniques.
Expert-derived models. Several
Scorecards: Some banks have
banks have built rating models by
developed credit rating models that they
asking their experts to decide what
refer to as “scorecards,” but they have
weights to assign to critical
used expert judgment to derive the
variables in the models. Drawing on weights. While they are models, they
their experience, the experts first
are not scoring models in the now
identify the observable variables
conventional use of the term. In its
that affect the likelihood of default.
conventional use, the term scoring model
They then reach agreement on the
is reserved for a rating model derived
weights to be assigned to each of
using statistical techniques.
the variables. Unlike statistical
optimization, the experts are not necessarily using clear, consistent criteria
to select the weights attached to the variables. Indeed, expert-judgment
model building is often a practical choice when there is not enough data to
support a statistical model building. Despite its dependence on expert
judgment, this method can be called model-based as long as the result –
the equation, most likely with linear weights – is used as the basis to rate
the credits. Once the equation is set, the model shares the feature of
replicability with statistically derived models. Generally, independent
credit experts use judgment to evaluate the reasonableness of the
development of these models.
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3. Constrained Judgment
27.
The alternatives just described present the extremes, but in practice, many
banks use rating systems that combine models with judgment. Two approaches
are common.
Judgmental systems with quantitative guidelines or model results as inputs.
Historically, the most common approach to rating has involved individuals
exercising judgment about risks, subject to policy guidelines containing
quantitative criteria such as minimum values for particular financial ratios.
Banks develop quantitative criteria to guide individuals in assigning ratings,
but often believe that those criteria do not adequately reflect the information
needed to assign a rating.
One version of this constrained judgment approach features a model output
as one among several criteria that an individual may consider in assigning
ratings. The individual assigning the rating is responsible for prioritizing the
criteria, reconciling conflicts between criteria, and if warranted, overriding
some criteria. Even if individuals incorporate model results as one of the
factors in their ratings, they will exercise judgment in deciding what weight to
attach to the model result. The appeal of this approach is that the model
combines many pieces of information into a single output, which simplifies
analysis, while the rater retains flexibility regarding the use of the model
output.
Model-based ratings with judgmental overrides. When banks use rating
models, individuals are generally permitted to override the results under
certain conditions and within tolerance levels for frequency. Credit-rating
systems in which individuals can override models raise many of the same
issues presented separately by pure judgment and model-based systems. If
overrides are rare, the system can be evaluated largely as if it is a modelbased system. If, however, overrides are prevalent, the system will be
evaluated more like a judgmental system.
Since constrained judgment systems combine features of both expert judgment
and model-based systems, their evaluation will require the skills required to
evaluate both of these other systems.
III. IRB Ratings System Architecture
A. Two-Dimensional Rating System
S.
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IRB risk rating systems must have two rating dimensions – obligor and loss
severity ratings.
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S.
IRB obligor and loss severity ratings must be calibrated to values of the
probability of default (PD) and the loss given default (LGD), respectively.
28.
Regardless of the type of rating system(s) used by an institution, the IRB
approach imposes some specific requirements. The first requirement is that an
IRB rating system must be two-dimensional. Banks will assign obligor ratings,
which will be associated with a PD. They will also either assign a loss severity
rating, which will be associated with LGD values, or directly assign LGD values to
each facility. The process of assigning the obligor and loss severity ratings –
hereafter referred to as the rating system – is discussed below, and the process of
calibrating obligor and loss severity ratings to PD and LGD parameters is
discussed in Chapter 2.
S.
Banks must record obligor defaults in accordance with the IRB definition of
default.
Definition of Default
29.
The consistent identification of defaults is fundamental to any IRB rating
system. For IRB purposes, a default is considered to have occurred with regard
to a particular obligor when either or both of the two following events have taken
place:
•
The obligor is past due more than 90 days on any material credit
obligation to the banking group. Overdrafts will be considered as
being past due once the customer has breached an advised limit
or been advised of a limit smaller than current outstandings.
•
The bank considers that the obligor is unlikely to pay its credit
obligations to the banking group in full, without recourse by the
bank to actions such as liquidating collateral (if held).
30.
Any obligor (or its underlying credit facilities) that meets one or more of the
following conditions is considered unlikely to pay and therefore in default:
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•
The bank puts the credit obligation on non-accrual status.
•
The bank makes a charge-off or account-specific provision
resulting from a significant perceived decline in credit quality
subsequent to the bank taking on the exposure.
•
The bank sells the credit obligation at a material credit-related
economic loss.
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•
The bank consents to a distressed restructuring of the credit
obligation where this is likely to result in a diminished financial
obligation caused by the material forgiveness, or postponement,
of principal, interest or (where relevant) fees.
•
The bank has filed for the obligor’s bankruptcy or a similar order
in respect of the obligor’s credit obligation to the banking group.
•
The obligor has sought or has been placed in bankruptcy or
similar protection where this would avoid or delay repayment of
the credit obligation to the banking group.
31.
While most conditions of default currently are identified by bank reporting
systems, institutions will need to augment data capture systems to collect those
default circumstances that may not have been traditionally identified. These
include facilities that are current and still accruing but where the obligor declared
or was placed in bankruptcy. They must also capture so called "silent defaults" –
defaults when the loss on a facility was avoided by liquidating collateral.
32.
Loan sales on which a bank experiences a material loss due to credit
deterioration are considered a default. Material credit related losses are defined
as XX. (The agencies seek comment on how to define “material” loss in the case
of loans sold at a discount).Banks should ensure that they have adequate
systems to identify such transactions and to maintain adequate records so that
reviewers can assess the adequacy of the institution’s decision-making process
in this area.
Obligor Ratings
S.
Banks must assign discrete obligor grades.
33.
While banks may use models to estimate probabilities of default for
individual obligors, the IRB approach requires banks to group the obligors into
discrete grades. Each obligor grade, in turn, must be associated with a single
PD.
S.
The obligor-rating system must result in a ranking of obligors by likelihood
of default.
34.
The proper operation of the obligor-rating system will feature a ranking of
obligors by likelihood of default. For example, if a bank uses a rating system
based on a 10-point scale, with 1 representing obligors of highest financial
strength and 10 representing defaulted obligors, grades 2 through 9 should
represent groups of ever-increasing risk. In a rating system in which risk
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increases with the grade, an obligor with a grade 4 is riskier than an obligor with a
grade 2, but need not be twice as risky.
S.
Separate exposures to the same obligor must be assigned to the same
obligor rating grade.
35.
As noted above, the IRB framework requires that the obligor rating be
distinct from the loss severity rating, which is assigned to the facility. Collateral
and other facility characteristics should not influence the obligor rating. For
example, in a 1-to-10 rating system, where risk increases with the number grade,
a defaulted borrower with a fully cash-secured transaction should be rated a 10 –
defaulted – regardless of the remote expectation of loss. Likewise, a borrower
whose financial condition warrants the highest investment grade rating should be
rated a 1 even if the bank’s transactions are subordinate to other creditors and
unsecured. Since the rating is assigned to the obligor and not the facility,
separate exposures to the same obligor must be assigned to the same obligor
rating grade.
36.
At the bottom of any IRB system rating scale is a default grade. Once an
obligor is considered to be in default for IRB purposes, that obligor must be
assigned a default grade until such time as its financial condition and
performance improve sufficiently to clearly meet the bank’s internal rating
definition for one of its non-default grades. Once an obligor is in default on any
material credit obligation to the subject bank, all of its facilities at that institution
are considered to be in default.
S.
In assigning an obligor to a rating category, the bank must assess the risk
of obligor default over a period of at least one year.
S.
Obligor ratings must reflect the impact of financial distress.
37.
In assigning an obligor to a rating category, the bank must assess the risk
of obligor default over a period of at least one year. This use of a one-year
assessment horizon does not mean that a bank should limit its consideration to
outcomes for that obligor that are most likely over that year; the rating must take
into account possible adverse events that might increase an obligor’s likelihood
of default.
Rating Philosophy—Decisions Underlying Ratings Architecture
S.
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Banks must adopt a ratings philosophy. Policy guidelines should describe
the ratings philosophy, particularly how quickly ratings are expected to
migrate in response to economic cycles.
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S.
A bank’s capital management policy must be consistent with its ratings
philosophy in order to avoid capital shortfalls in times of systematic
economic stress.
38.
In the IRB framework, banks assign obligors to groups that are expected to
share common default frequencies. That general description, however, still
leaves open different possible implementations, depending on how the bank
defines the set of possible adverse events that the obligor might face. A bank
must decide whether obligors are grouped by expected common default
frequency over the next year (a so-called point-in-time rating system) or by an
expected common default frequency over a wider range of possible stress
outcomes (a so-called through-the-cycle rating system). Choosing between a
point-in-time system and a through-the-cycle system yields a rating philosophy.
39.
In point in time rating systems, obligors are assigned to groups that are
expected to share a common default frequency in a particular year. Point-in-time
ratings change from year to year as borrowers’ circumstances change, including
changes due to the economic possibilities faced by the borrowers. Since the
economic circumstances of many borrowers reflect the common impact of the
general economic environment, the transitions in point-in-time ratings will reflect
that systematic influence. A Merton-style probability of default prediction model
is commonly believed to be an example of a point-in-time approach to rating
(although that may depend on the specific implementation of the model).
40.
Through-the-cycle rating systems do not ask the question, what is the
probability of default over the next year. Instead, they assign obligors to groups
that would be expected to share a common default frequency if the borrowers in
them were to experience distress, regardless of whether that distress is in the
next year. Thus, as the descriptive title suggests, this rating philosophy abstracts
from the near-term economic possibilities and considers a richer assessment of
the possibilities. Like point-in-time ratings, through the cycle ratings will change
from year to year due to changes in borrower circumstance. However, since this
rating philosophy abstracts from the immediate economic circumstance and
considers the implications of hypothetical stress circumstances, year to year
transitions in ratings will be less influenced by changes in the actual economic
environment. The ratings agencies are commonly believed to use through-thecycle rating approaches.
41.
Current practice in many banks in the U.S. is to rate obligors using an
approach that combines aspects of both point-in-time and through the cycle
approaches. The explanation provided by banks that combine those approaches
is that they want rating transitions to reflect the directional impact of changes in
the economic environment, but that they do not want all of the volatility in ratings
associated with a point-in-time approach.
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42.
Regardless of which ratings philosophy a bank chooses, an IRB bank
must articulate clearly its approach and the implications of that choice. As part of
the choice of rating philosophy, the bank must decide whether the same ratings
philosophy will be employed for all of the bank’s portfolios. And management
must articulate the implications that the bank’s ratings philosophy has on the
bank’s capital planning process. If a bank chooses a ratings philosophy that is
likely to result in ratings transitions that reflect the impact of the economic cycle,
its capital management policy must be designed to avoid capital shortfalls in
times of systematic economic stress.
Obligor-Rating Granularity
S.
An institution must have at least seven obligor grades that contain only
non-defaulted borrowers and at least one grade to which only defaulted
borrowers are assigned.
43.
The number of grades used in a rating system should be sufficient to
reasonably ensure that management can meaningfully differentiate risk in the
portfolio, without being so large that it limits the practical use of the rating system.
To determine the appropriate number of grades beyond the minimum seven nondefault grades, each institution must perform its own internal analysis.
S.
An institution must justify the number of obligor grades used in its rating
system and the distribution of obligors across those grades.
44.
The mere existence of an exposure concentration in a grade (or grades)
does not, by itself, reflect weakness in a rating system. For example, banks may
focus on a particular type of lending, such as asset-based lending, in which the
borrowers may have similar default risk. Banks with such focused lending
activities may use close to the minimum number of obligor grades, while banks
with a broad range of lending activities should have more grades. However,
banks with a high concentration of obligors in a particular grade are expected to
perform a thorough analysis that supports such a concentration.
45.
A significant concentration within an obligor grade may be suspected if the
financial strength of the borrowers within that grade varies considerably. If
obligors seem unduly concentrated, then management should ask themselves
the following questions:
•
Are the criteria for each grade clear? Those rating criteria may be too
vague to allow raters to make clear distinctions. Ambiguity may be an
issue throughout the rating scale or it may be limited to the most
commonly used ratings.
•
How diverse are the obligors? That is how many market segments (for
example, large commercial, middle market, private banking, small
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business, geography, etc.) are significantly represented in the bank’s
borrower population? If a bank’s commercial loan portfolio is not
concentrated in one market segment, its risk rating distribution is not likely
to be concentrated.
•
How broad are the bank’s internal rating categories compared to those of
other lenders? The bank may be able to learn enough from publicly
available information to adjust its rating criteria.
46.
Some banks use “modifiers” to provide more risk differentiation to a given
rating system. A risk rating modified with a plus, minus or other indicator does
not constitute a separate grade unless the bank has developed a distinct rating
definition and criteria for the modified grade. In the absence of such distinctions,
grades such as 5, 5+, and 5- are viewed as a single grade for regulatory capital
purposes regardless of the existence of the modifiers.
Loss Severity Ratings
S.
Banks must rank facilities by the expected severity of the loss upon
default.
47.
The second dimension of an IRB system is the loss severity rating, which
is calibrated to LGD. A facility’s LGD estimate is the loss the bank is likely to
incur in the event that the obligor defaults, and is expressed as a percentage of
exposure at the time of default. LGD estimates can be assigned either through
the use of a loss severity rating system or they can be directly assigned to each
facility.
48.
LGD analysis is still in very early stages of development relative to default
risk modeling. Academic research in this area is relatively sparse, data are not
abundant, and industry practice is still widely varying and evolving. Given the
lack of data and the lack of research into LGD modeling, some banks are likely,
as a first step, to segment their portfolios by a handful of available characteristics
and determine the appropriate LGDs for those segments. Over time, banks' LGD
methodologies are expected to evolve. Long-standing banking experience and
existing research on LGD, while preliminary, suggests that collateral values,
seniority, industry, etc. are predictive of loss severity.
S.
Banks must have empirical support for LGD rating systems regardless of
whether they use an LGD grading system or directly assign LGD
estimates.
49.
Whether a bank chooses to assign LGD values directly or, alternatively, to
rate facilities and then quantify the LGD for the rating grades, the key
requirement is that it will need to identify facility characteristics that influence
LGD. Each of the loss severity rating categories must be associated with an
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empirically supported LGD estimate. In much the same way an obligor- rating
system ranks exposures by the probability of default, a facility rating system must
rank facilities by the likely loss severity.
50.
Regardless of the method used to assign LGDs (loss severity grades or
direct LGD estimation), data used to support the methodology must be gathered
systematically. For many banks, the quality and quantity of data available to
support the LGD estimation process will have an influence on the method they
choose.
Stress Condition LGDs
S.
Loss severity ratings must reflect losses expected during periods with a
relatively high number of defaults.
51.
Like obligor ratings, which group obligors by expected default frequency,
loss severity ratings assign facilities to groups that are expected to experience a
common loss severity. However, the different treatment accorded to PD and
LGD in the model used to calculate IRB capital requirements mandates an
asymmetric treatment of obligor and loss severity ratings. Obligor ratings assign
obligors to groups that are expected to experience common default frequencies
across a number of years, some of which are years of general economic stress
and some of which are not. In contrast, loss severity ratings (or estimates) must
pertain to losses expected during periods with a high number of defaults –
particular years that can be called stress conditions. For cases in which loss
severities do not have a material degree of cyclical variability, use of a long-run
default weighted average is appropriate, although stress condition LGD generally
exceeds these averages.
Loss Severity Rating/LGD Granularity
S.
Banks must have a sufficiently fine loss severity grading system or
prediction model to avoid grouping facilities with widely varying LGDs
together.
52.
While there is no stated minimum number of loss severity grades, the
systems that provide LGD estimates must be flexible enough to adequately
segment facilities with significantly varying LGDs. Banks should have a
sufficiently fine LGD grading system or LGD prediction model to avoid grouping
facilities with widely varying LGDs together. For example, a bank using a loss
severity rating-scale approach that has credit products with a variety of collateral
packages or financing structures would be expected to have more LGD grades
than those institutions with fewer options in their credit products.
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B. Other Considerations of IRB Rating System Architecture
Timeliness of Ratings
S. All risk ratings must be updated whenever new relevant information is
received, but must be updated at least annually.
53.
A bank must have a policy that requires a dynamic ratings approach
ensuring that obligor and loss severity ratings reflect current information. That
policy must also specify minimum financial reporting and collateral valuation
requirements. For example, at the time of servicing events, banks typically
receive updated financial information on obligors. For cases in which loss
severity grades or estimates are dependent on collateral values or other factors
that change periodically, that policy must take into account the need to update
these factors.
54.
Banks’ policies may include an alternative rating update timetable for
exposures below a de minimus amount that is justified by the lack of materiality of
the potential impact on capital. For example, some banks use triggering events
to prompt an update of their ratings on de minimus exposures rather than
adhering to a specific timetable.
Multiple Ratings Systems
55.
Some banks may develop one risk-rating system that can be used across
the entire commercial loan portfolio. However, a bank can choose to deploy any
number of rating systems as long as all exposures are assigned PD and LGD
values. A different rating system could be used for each business line and each
rating system could use a different rating scale. A bank could also use a different
rating system for each business line with each system using a common rating
scale. Rating models could be used for some portfolios and expert judgment
systems for others. An institution’s complexity and sophistication, as well as the
size and range of products offered, will affect the types and numbers of rating
systems employed.
56.
While using a number of rating systems is feasible, such a practice might
make it more difficult to meet supervisory standards. Each rating system must
conform to the standards in this guidance and must be validated for accuracy and
consistency. The requirement that each rating systems be calibrated to
parameter values imposes the ultimate constraint, which is that ratings be applied
consistently.
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Recognition of the Risk Mitigation Benefits of Guarantees
S.
Banks reflecting the risk-mitigating effect of guarantees must do so by
either adjusting PDs or LGDs, but not both.
S.
To recognize the risk-mitigating effects of guarantees, institutions must
ensure that the written guarantee is evidenced by an unconditional and
legally enforceable commitment to pay that remains in force until the debt
is satisfied in full.
57.
Adjustments for guarantees must be made in accordance with specific
criteria contained in the bank’s credit policy. The criteria should be plausible and
intuitive, and should address the guarantor’s ability and willingness to meet its
obligations. Banks are expected to gather evidence that confirms the riskmitigating effect of guarantees.
58.
Other forms of written third-party support (for example, comfort letters or
letters of awareness) that are not legally binding should not be used to adjust PD
or LGD unless a bank can demonstrate through analysis of internal data the riskmitigating effect of such support. Banks may not adjust PDs or LGDs to reflect
implied support or verbal assurances.
59.
Regardless of the method used to recognize the risk-mitigating effects of
guarantees, a bank must adopt an approach that is applied consistently over time
and across the portfolio. Moreover, the onus is on the bank to demonstrate that
its approach is supported by logic and empirical results. While guarantees may
provide grounds for adjusting PD or LGD, they cannot result in a lower risk weight
than that assigned to a similar direct obligation of the guarantor.2
C. Validation Process
S.
IRB rating system architecture must be designed to ensure rating system
accuracy
60.
As part of their IRB rating system architecture, banks must implement a
process to ensure the accuracy of their rating systems. Rating system accuracy
is defined as the combination of the following outcomes:
2
The probability that an obligor and a guarantor (who supports the obligor’s debt) will both default
on a debt is lower than the probability that either the obligor or the guarantor will default. This
favorable risk-mitigation effect is known as the reduced likelihood of “double default.” In
determining their rating criteria and procedures, banks are not permitted to consider possible
favorable effects of imperfect expected correlation between default events for the borrower and
guarantor for purposes of regulatory capital requirements. Thus, the adjusted risk weight cannot
reflect the risk mitigation of double default. The ANPR solicits public comment on the doubledefault issue.
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•
The actual long-run average default frequency for each rating grade is
not significantly greater than the PD assigned to that grade.
•
The actual stress-condition loss rates experienced on defaulted
facilities are not significantly greater than the LGD estimates assigned
to those facilities.
61.
Some differences across individual grades between observed outcomes
and the estimated parameter inputs to the IRB equations can be expected. But if
systematic differences suggest a bias toward lowering regulatory capital
requirements, the integrity of the rating system (of either the PD or LGD
dimensions or of both) becomes suspect. Validation is the set of activities
designed to give the greatest possible assurances of ratings system accuracy.
S.
Banks must have ongoing validation processes that include the review of
developmental evidence, ongoing monitoring, and the comparison of
predicted parameter values to actual outcomes (back-testing).
62.
Validation is an integral part of the rating system architecture. Banks must
have processes designed to give reasonable assurances of their rating systems’
accuracy. The ongoing process to confirm and ensure rating system accuracy
consists of:
•
•
•
The evaluation of developmental evidence,
Ongoing monitoring of system implementation and reasonableness
(verification and benchmarking), and
Back-testing (comparing actual to predicted outcomes).
63.
IRB institutions are expected to employ all of the components of this
process. However, the data to perform comprehensive back-testing will not be
available in the early stages of implementing an IRB rating system. Therefore,
banks will have to rely more heavily on developmental evidence, quality control
tests, and benchmarking to assure themselves and other interested parties that
their rating systems are likely to be accurate. Since the time delay before rating
systems can be back-tested is likely to be an important issue — because of the
rarity of defaults in most years and the bunching of defaults in a few years — the
other parts of the validation process will assume greater importance. If rating
processes are developed in a learning environment in which banks attempt to
change and improve ratings, back testing may be delayed even further.
Validation in its early stages will depend on bank management’s exercising
informed judgment about the likelihood of the rating system working — not simply
on empirical tests.
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1. Ratings System Developmental Evidence
64.
The first source of support for the validity of a bank’s rating system is
developmental evidence. Evaluating developmental evidence involves making a
reasonable assessment of the quality of the rating system by analyzing its design
and construction. Developmental evidence is intended to answer the question,
Could the rating system be expected to work reasonably if it is implemented as
designed? That evidence will have to be revisited whenever the bank makes a
change to its rating system. If a bank adopts a rating system and does not make
changes, this step will not have to be revisited. However, since rating systems
are likely to change over time as the bank learns about the effectiveness of the
system and incorporates the results of those analyses, the evaluation of
developmental evidence is likely to be an ongoing part of the process. The
particular steps taken in evaluating developmental evidence will depend on the
type of rating system.
65.
Generally, the evaluation of developmental evidence will include a body of
expert opinion. For example, developmental evidence in support of a statistical
rating model must include information on the logic that supports the model and an
analysis of the statistical model-building techniques. In contrast, developmental
evidence in support of a constrained-judgment system that features guidance
values of financial ratios might include a description of the logic and evidence
relating the values of the ratios to past default and loss outcomes.
66.
Regardless of the type of rating system, the developmental evidence will
be more persuasive when it includes empirical evidence on how well the ratings
might have worked in the past. This evidence should be available for a statistical
model since such models are chosen to maximize the fit to outcomes in the
development sample. In addition, statistical models should be supported by
evidence that they work well outside the development sample. Use of “holdout”
sample evidence is a good model-building practice to ensure that the model is
not merely a statistical quirk of the particular data set used to build the model.
67.
Empirical developmental evidence of rating effectiveness will be more
difficult to produce for a judgmental rating system. Such evidence would require
asking raters how they would have rated past credits for which they did not know
the outcomes. Those retrospective ratings could then be compared to the
outcomes to determine whether the ratings were correct on average. Conducting
such tests, however, will be difficult because historical data sets may not include
all of the information that an individual would have actually used in making a
judgment about a rating.
68.
The sufficiency of the developmental evidence will itself be a matter of
informed expert opinion. Even if the rating system is model-based, an evaluation
of developmental evidence will entail judging the merits of the model-building
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technique. Although no bright line tests are feasible because expert judgment is
essential to the evaluation of rating system development, experts will be able to
draw conclusions about whether a well-implemented system would be likely to
perform satisfactorily.
2. Ratings System Ongoing Validation
69.
The second source of analytical support for the validity of a bank rating
system is the ongoing analysis intended to confirm that the rating system is being
implemented and continues to perform as intended. Such analysis involves
process verification and benchmarking.
Process Verification
70.
Verification activities address the question, Are the ratings being assigned
as intended? Specific verification activities will depend on the rating approach. If
a model is used for rating, verification analysis begins by confirming that the
computer code used to deploy the model is correct. The computer code can be
verified in a number of established ways. For example, a qualified expert can
duplicate the code or check the code line by line. Process verification for a model
will also include confirmation that the correct data are being used in the model.
71.
For expert-judgment and constrained-judgment systems, verification
requires other individual reviewers to evaluate whether the rater followed rating
policy. The primary requirements for verification of ratings assigned by
individuals are:
•
•
•
a transparent rating process,
a database with information used by the rater, and
documentation of how the decisions were made.
The specific steps will depend on how much the process incorporates specific
guidelines and how much the exercise of judgment is allowed. As the
dependence on specific guidelines increases, other individuals can more easily
confirm that guidelines were followed by reference to sufficient documentation.
As the dependence on judgment rises, the ratings review function will have to be
staffed increasingly by experts with appropriate skills and knowledge about the
rating policies of the bank.
72.
Ratings process verification also includes override monitoring. If
individuals have the ability to override either models or policies in a constrainedjudgment system, the bank should have both a policy stating the tolerance for
overrides and a monitoring system for identifying the occurrence of overrides. A
reporting system capturing data on reasons for overrides will facilitate learning
about whether overrides improve accuracy.
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Benchmarking
S.
Banks must benchmark their internal ratings against internal, market and
other third-party ratings.
73.
Benchmarking is the set of activities that uses alternative tools to draw
inferences about the correctness of ratings before outcomes are actually known.
The most important type of benchmarking of a rating system is to ask whether
another rater or rating method attaches the same rating to a particular obligor or
facility. Regardless of the rating approach, the benchmark can be either a
judgmental or a model-based rating. Examples of such benchmarking include:
•
Ratings reviewers who completely re-rate a sample of credits rated
by individuals in a judgmental system.
•
An internally developed model is used to rate credits rated earlier in a
judgmental system.
•
Individuals rate a sample of credits rated by a model.
•
Internal ratings are compared against results from external agencies
or external models.
74.
Because it will take considerable time before outcomes will be available,
using alternative ratings as benchmarks will be a very important validation
device. Such benchmarking must be applied to all rating approaches, and the
benchmark can be either a model or judgment. At a minimum, banks must
establish a process in which a representative sample of its internal ratings is
compared to third-party ratings (e.g., independent internal raters, external rating
agencies, models, or other market data sources) of the same credits.
75.
Benchmarking also includes activities designed to draw broader
inferences about whether the rating system – as opposed to individual ratings – is
working as expected. The bank can look for consistency in ranking or
consistency in the values of rating characteristics for similarly rated credits.
Examples of such benchmarking activities include:
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•
Analyzing the characteristics of obligors that have received common
ratings.
•
Monitoring changes in the distribution of ratings over time.
•
Calculating a transition matrix calculated from changes in ratings in a
bank’s portfolio and comparing it to historical transition matrices from
internal bank data or publicly available ratings.
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While benchmarking activities allow for inferences about the correctness of the
ratings system, they are the not same thing as back-testing. The benchmark
itself is a prediction and may be in error. If benchmarking evidence suggests a
pattern of rating differences, it should lead the bank to investigate the source of
the differences. Thus, the benchmarking process illustrates the possibility of
feedback from ongoing validation to model development, underscoring the
characterization of validation as a process.
3. Back Testing
S. Banks must develop statistical tests to back-test their IRB rating systems.
S. Banks must establish internal tolerance limits for differences between
expected and actual outcomes.
S. Banks must have a policy that requires remedial actions be taken when policy
tolerances are exceeded.
76.
The third component of a validation process is back-testing, which is the
comparison of predictions with actual outcomes. Back-testing of IRB systems is
the empirical test of the accuracy of the parameter values, PD and LGD,
associated with obligor and loss severity ratings, respectively. For IRB rating
systems, back-testing addresses the combined effectiveness of the assignment
of obligor and loss severity ratings and the calibration of the parameters PD and
LGD attached to those ratings.
77.
At this time, there is no generally agreed-upon statistical test of the
accuracy of IRB systems. Banks must develop statistical tests to back-test their
IRB rating systems. In addition, banks must have a policy that specifies internal
tolerance limits for comparing back-testing results. Importantly, that policy must
outline the actions that would be taken whenever policy limits are exceeded.
78.
As a combined test of ratings effectiveness, back-testing is a conceptual
bridge between the ratings system architecture discussed in this chapter and the
quantification of parameters, discussed in Chapter 2. The final section of
Chapter 2 discusses back-testing as one type of quantitative test required to
validate the quantification of parameter values.
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Chapter 2: Quantification of IRB Systems
79.
Ratings quantification is the process of assigning numerical values to the
four key components for internal ratings-based assessments of credit-risk capital:
probability of default (PD), the expected loss given default (LGD), the expected
exposure at default (EAD), and maturity (M). Section I establishes an organizing
framework for considering IRB quantification and develops general principles that
apply to the entire process. Sections II through IV cover specific principles or
supervisory standards that apply to PD, LGD, and EAD respectively. The
maturity component, which is much less dependent on statistical estimates and
the use of data, receives somewhat different treatment in section V. Validation of
the quantification process is covered in section VI.
I. Introduction
A. Stages of the Quantification Process
80.
With the exception of maturity, the risk components are unobservable and
must be estimated. The estimation must be consistent with sound practice and
supervisory standards. In addition, a bank must have processes to ensure that
these estimates remain valid.
81.
Calculation of risk components for IRB involves two sets of data: the
bank’s actual portfolio data, consisting of current credit exposures assigned to
internal grades, and a “reference data set,” consisting of a set of defaulted credits
(in the case of LGD and EAD estimation) or both defaulted and non-defaulted
credits (in the case of PD estimation). The bank estimates a relationship
between the reference data set and probability of default, loss severity, or
exposure; then this estimated relationship is applied to the actual portfolio data
for which capital is being assessed.
82.
Quantification proceeds through four logical stages: obtaining reference
data; estimating the reference data’s relationship to the parameters; mapping the
correspondence between the reference data and the portfolio’s data; and
applying the relationship between reference data and parameters to the
portfolio’s data. (Readers may find it helpful to refer to the appendix to this
chapter, which illustrates how this four-stage framework can be applied to ratings
quantification approaches in practice.) An evaluation of any bank’s IRB
quantification process focuses on understanding how the bank implements each
stage for each of the key parameters, and on assessing the adequacy of the
bank’s approach.
Data – First, the bank constructs a reference data set, or source of data,
from which parameters can be estimated.
Reference data sets include internal data, external data, and pooled
internal/external data. Important considerations include the comparability
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of the reference data to the current credit portfolio, whether the sample
period “appropriately” includes periods of stress, and the definition of
default used in the reference data. The reference data must be described
using a set of observed characteristics; consequently, the data set must
contain variables that can be used for this characterization. Relevant
characteristics might include external debt ratings, financial measures,
geographic regions, or any other factors that are believed to be related in
some way to PD, LGD, or EAD. More than one reference data set may be
used.
Estimation – Second, the bank applies statistical techniques to the
reference data to determine a relationship between characteristics of the
reference data and the parameters (PD, LGD, or EAD).
The result of this step is a model that ties descriptive characteristics of the
obligor or facility in the reference data set to PD, LGD, or EAD estimates.
In this context, the term ‘models’ is used in the most general sense; a
model may be simple, such as the calculation of averages, or more
complicated, such as an approach based on advanced regression
techniques. This step may include adjustments for differences between
the IRB definition of default and the default definition in the reference data
set, or adjustments for data limitations. More than one estimation
technique may be used to generate estimates of the risk components,
especially if there are multiple sets of reference data or multiple sample
periods.
Mapping – Third, the bank creates a link between its portfolio data and the
reference data based on common characteristics.
Variables or characteristics that are available for the current portfolio must
be mapped to the variables used in the default, loss-severity, or exposure
model. (In some cases, the bank constructs the link for a representative
exposure in each internal grade, and the mapping is then applied to all
credits within a grade.) An important element of mapping is making
adjustments for differences between reference data sets and the bank’s
portfolio. The bank must create a mapping for each reference data set
and for each combination of variables used in any estimation model.
Application – Fourth, the bank applies the relationship estimated for the
reference data to the actual portfolio data.
The ultimate aim of quantification is to attribute a PD, LGD, or EAD to
each exposure within the portfolio, or to each internal grade if the mapping
was done at the grade level. This step may include adjustments to default
frequencies or loss rates to “smooth” the final parameter estimates. If the
estimates are applied to individual transactions, the bank must in some
way aggregate the estimates at the grade level. In addition, if multiple
data sets or estimation methods are used, the bank must adopt a means
of combining the various estimates.
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83.
A number of examples are given in this chapter to aid exposition and
interpretation. None of the examples is sufficiently detailed to incorporate all the
considerations discussed in this chapter. Moreover, technical progress in the
area of quantification is rapid. Thus, banks should not interpret an example that
is consistent with the standard being discussed, and that resembles the bank’s
current practice, as creation of a “safe harbor” or as an indication that the bank’s
practice will be approved as-is. Banks should consider this guidance in its
entirety when determining whether systems and practices are adequate.
B. General Principles for Sound IRB Quantification
84.
Several core principles apply to all elements of the overall ratings
quantification process; those general principles are discussed in this introductory
section. Each of these principles is, in effect, a supervisory standard for IRB
systems. Other supervisory standards, specific to particular elements or
parameters, are discussed in the relevant sections.
85.
Supervisory evaluation of IRB quantification requires consideration of all of
these principles and standards, both general and specific. Particular practical
approaches to ratings quantification may be highly consistent with some
standards, and less so with others. In any particular case, an ultimate
assessment relies on the judgment of supervisors to weigh the strengths and
weaknesses of a bank’s chosen approach, using these supervisory standards as
a guide.
S.
IRB institutions must have a fully specified process covering all aspects of
quantification (reference data, estimation, mapping, and application). The
quantification process, including the role and scope of expert judgment,
must be fully documented and updated periodically.
86.
A fully specified quantification process must describe how all four stages
(data, estimation, mapping, and application) are implemented for each
parameter. Documentation promotes consistency and allows third parties to
review and replicate the entire process. Examples of third parties that might use
of the documentation include rating-system reviewers, auditors, and bank
supervisors. Periodic updates to the process must be conducted to ensure that
new data, analytical techniques, and evolving industry practice are incorporated
into the quantification process.
S.
Parameter estimates and related documentation must be updated
regularly.
87.
The parameter estimates must be updated at least annually, and the
process for doing so must be documented in bank policy. The update should
also evaluate the judgmental adjustments embedded in the estimates; new data
or techniques may suggest a need to modify those adjustments. Particular
attention should be given to new business lines or portfolios in which the mix of
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obligors is believed to have changed substantially. A material merger,
acquisition, divestiture, or exit clearly raises questions about the continued
applicability of the process and should trigger an intensive review and updating.
88.
The updating process is particularly relevant for the reference data stage
because new data become available all the time. New data must be
incorporated, into the PD, LGD, and EAD estimates, using a well-defined
process.
S.
A bank must subject all aspects of the quantification process, including
design and implementation, to an appropriate degree of independent
review and validation.
89.
An independent review is an assessment conducted by persons not
accountable for the work being reviewed. The reviewers may be either internal or
external parties. The review serves as a check that the quantification process is
sound and works as intended; it should be broad-based, and must include all of
the elements of the quantification process that lead to the ultimate estimates of
PD, LGD, and EAD. The review must cover the full scope of validation:
evaluation of the integrity of data inputs, analysis of the internal logic and
consistency of the process, comparison with relevant benchmarks, and
appropriate back-testing based on actual outcomes.
S.
Judgmental adjustments may be an appropriate part of the quantification
process, but must not be biased toward lower estimates of risk.
90.
Judgment will inevitably play a role in the quantification process and may
materially affect the estimates. Judgmental adjustments to estimates are often
necessary because of some limitations on available reference data or because of
inherent differences between the reference data and the bank’s portfolio data.
The bank must ensure that adjustments are not biased toward optimistically low
parameter estimates for PD, LGD, and EAD. Individual assumptions are less
important than broad patterns; consistent signs of judgmental decisions that
lower parameter estimates materially may be evidence of bias.
91.
The reasoning and empirical support for any adjustments, as well as the
mechanics of the calculation, must be documented. The bank should conduct
sensitivity analysis to demonstrate that the adjustment procedure is not biased
toward reducing capital requirements. The analysis must consider the impact of
any judgmental adjustments on estimates and risk weights, and must be fully
documented.
S.
Parameter estimates must incorporate a degree of conservatism that is
appropriate for the overall robustness of the quantification process.
92.
In estimating values of PD, LGD, and EAD should be as precise and
accurate as possible. However, estimates of PD, LGD and EAD are statistics,
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and thus inherently subject to uncertainty and potential error. It is often possible
to be reasonably confident that a risk component or other parameter lies within a
particular range, but greater precision is difficult to achieve. Aspects of the
ratings quantification process that are apt to introduce uncertainty and potential
error include the following:
•
•
•
The estimation of coefficients of particular variables in a regression-based
statistical default or severity model.
The calculation of average default or loss rates for particular categories of
credits in external default databases.
The mapping between portfolio obligors or facilities and reference data
when the set of common characteristics does not align exactly.
93.
A general principle of the IRB approach is that a bank must adjust
estimates conservatively in the presence of uncertainty or potential error. In
many cases this corresponds to assigning a final parameter estimate that
increases required capital relative to the best estimate produced through soundpractice estimation techniques. The extent of this conservative adjustment
should be related to factors such as the relevance of the reference data, the
quality of the mapping, the precision of the statistical estimates, and the amount
of judgment used throughout the process. Margins of conservatism need not be
added at each step; indeed, that could produce an excessively conservative
result. The overall margin of conservatism should adequately account for all
uncertainties and weaknesses; this is the general interpretation of requirements
to incorporate appropriate degrees of conservatism. Improvements in the
quantification process (use of better data, estimation techniques, and so on) may
reduce the appropriate degree of conservatism over time.
94.
Estimates of PD, LGD, EAD, or other parameters or coefficients should be
presented with an accompanying sense of the statistical precision of the
estimates; this facilitates an assessment of the appropriate degree of
conservatism.
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II. Probability of Default (PD)
A. Data
95.
To estimate PD accurately, a bank must have a comprehensive reference
data set with observations that are comparable to the bank's current portfolio of
obligors. Clearly, the data set used for estimation should be similar to the portfolio
to which such estimates will be applied. The same comparability standard
applies to both internal and external data sets.
96.
To ensure ongoing applicability of the reference data, a bank must assess
the characteristics of its current obligors relative to the characteristics of obligors
in the reference data. Such variables might include qualitative and quantitative
obligor information, internal and external rating, rating dates, and line of business
or geography. To this end, a bank must maintain documentation that fully
describes all explanatory variables in the data set, including any changes to
those variables over time. A well-defined and documented process must be in
place to ensure that the reference data are updated as frequently as is practical,
as fresh data become available or portfolio changes make necessary.
S.
The sample for the reference data must be at least five years, and must
include periods of economic stress during which default rates were
relatively high.
97.
To foster more robust estimation, banks should use longer time series
when more than five years of data are available. However, the benefits of using a
longer time series (longer than five years) may have to be weighed against a
possible loss of data comparability. The older the reference data, the less similar
they are likely to be to the bank's current portfolio; striking the correct balance is a
matter of judgment. Reference obligors must not differ from the current portfolio
obligors systematically in ways that seem likely to be related to obligor default
risk. Otherwise, the derived PD estimates may not be applicable to the current
portfolio.
98.
Note that this principle does not simply restate the requirement for five
years of data: periods of stress during which default rates are relatively high
must be included in the data sample. Exclusion of such periods biases PD
estimates downward and unjustifiably lowers regulatory capital requirements.
Example 1
A bank's reference data set covers the years1987 through 2001. Each year
includes identical data elements, and each year is similarly populated. For its
grade PD estimates, the bank relies upon data from a sub-sample covering 1992
through 2001. The bank provides no justification for dropping the years from
1987 through 1991. The bank contends that it is not necessary to include those
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data, as the reference sample they use for estimation satisfies the five-year
requirement. This practice is not consistent with the standard because the bank
has not supported its decision to ignore available data. The fact that the
excluded years include a recession would raise particular concerns.
S.
The definition of default within the reference data must be reasonably
consistent with the IRB definition of default.
99.
Regardless of the source of the reference data, a bank must apply the
same default definition throughout the quantification processes. This fosters
consistent estimation across parameters and reduces the potential for undesired
bias. In addition, consistent application of the same definition across banks will
permit true horizontal analysis by supervisors and engaged market participants.
100. This standard applies to both internal and external reference data. For
internal data, a bank's default definition is expected to be consistent with the IRB
definition going forward. Banks will be expected to make appropriate
adjustments to their data systems such that all defaults as defined for IRB are
captured by the time a bank fully implements its IRB system. For any historical or
external data that do not fully comply with the IRB definition of default, a bank
must make conservative adjustments to reflect such discrepancies. Larger
discrepancies require larger adjustments for conservatism.
Example 1
To identify defaults in its historical data, a bank applies a consistent definition of
"placed on nonaccrual." This definition is used in the bank's quantification
exercises to estimate PD, LGD, and EAD. The bank recognizes that use of the
nonaccrual definition fails to capture certain defaults as identified in the IRB rules.
Specifically, the bank indicates that the following kinds of defaulted facilities
would not have been placed on nonaccrual: (1) credit obligations that were sold
at a material credit-related economic loss, and (2) distressed restructurings. To
be consistent with the standard, the bank must make a well-supported
adjustment to its grade PD estimates to reflect the difference in the default
definitions.
B. Estimation
101. Estimation of PD is the process by which characteristics of the reference
data are related to default frequencies.3 The relevant characteristics that help to
determine the likelihood of default are referred to as “drivers of default”. Drivers
3
The New Basel Capital Accord produced by the Basel Committee on Banking Supervision
discusses three techniques for PD estimation. IRB banks are not constrained to select from
among these three techniques; they have broad flexibility to implement appropriate approaches to
quantification. The three Basel techniques are best regarded not as a complete taxonomy of the
possible approaches to PD estimation, but rather as illustrations of a few of the many possible
approaches.
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might include variables such as financial ratios, management expertise, industry,
and geography.
S.
Estimates of default rates must be empirically based and must represent a
long-run average.
102. Estimates must capture average default experience over a reasonable mix
of high-default and low-default years of the economic cycle. The average is
labeled “long-run” because a long observation period would span both peaks and
valleys of the economic cycle. The emphasis should not be on time-span; the
long-run average concept captures the breadth, not the length, of experience.
103. If the reference data are characterized by internal or external rating
grades, one estimation approach is to calculate the mean of one-year realized
default rates for each grade, giving equal weight to each year’s realized default
rate. PD estimates generally should be calculated in this manner.
104. Another approach is to pool obligors in a given grade over a number of
years and then calculate the mean default rate. In this case, each year’s default
rate is weighted by the number of obligors. This approach may underestimate
default rates. For example, if lending declines in recessions so that obligors are
fewer in those years than in others, weighting by number of obligors would dilute
the effect of the recession year on the overall mean. The obligor-weighted
calculation, or another approach, will be allowed only if the bank can demonstrate
that this approach provides a better estimate of the long-run average PD. At a
minimum, this would involve comparing the results of both methods.
105. Statistical default prediction models may also play a role in PD estimation.
For example, the characteristics of the reference data might include financial
ratios or a distance-to-default measure, as defined by a specific implementation
of a Merton-style structural model.
106. For a model-based approach to meet the requirement that ultimate grade
PD estimates be long-run averages, the reference data used in the default model
must meet the long-run requirement. For example, a model can be used to relate
financial ratios to likelihood of default based on the outcome for the firms – default
or non-default. Such a model must be calibrated to capture the default
experience over a reasonable mix of good and bad years of the economic cycle.
The same requirement would hold for a structural model; distance to default must
be calibrated to default frequency using long-run experience. This applies to both
internal and vendor models, and a bank must verify that this requirement is met.
Example 1
A bank uses external data from a rating agency to estimate PD. The PD estimate
for each agency grade is calculated as the mean of yearly realized default rates
over a time period (1980 through 2001) that includes several recessions and
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high-default years. The bank provides support that this time period adequately
represents long-run experience. This illustrates an estimation method that is
consistent with the standard.
Example 2a
Like the institution in example 1, a bank maps internal ratings to agency grades.
The estimates for the agency grades are set indirectly, using the default
probabilities from a default prediction model. The bank does so because
although it links internal and agency grades, the bank views the default model’s
results as more predictive than the historical agency default experience. For
each agency grade, the bank calculates a PD estimate as the mean of the modelbased default probabilities for the agency-rated obligors. In order to meet the
long-run requirement, the bank calculates the estimates over the seven years
from 1995 through 2001. The bank demonstrates that this time period includes a
reasonable mix of high-default and low-default experience. This estimation
method is consistent with the standard.
Example 2b
In a variant of example 2a, a bank uses the mean default frequency per agency
rating grade for a single year, such as 2001. Empirical evidence shows that the
mean default frequency for agency grades varies substantially from year to year.
A single year thus does not reflect the full range of experience, because a longrun average should be relatively stable year to year. Such instability makes this
estimation method unacceptable.
Example 2c
Another bank calculates the agency grade PD estimates as the median default
probability of companies in that grade. The bank does so without demonstrating
that the median is a better statistical estimator than the mean. This estimation
method is not consistent with the standard. A median gives less weight to
obligors with high estimated default probabilities than a simple mean does. The
difference between mean and median can be material because distributions of
credits within grades often are substantially skewed toward higher default
probabilities: the riskier obligors within a grade tend to have individual default
probabilities that are substantially worse than the median, while the least risky
have default probabilities only somewhat better than the median.
S.
Judgmental adjustments may play an appropriate role in PD estimation,
but must not be biased toward lower estimates.
107. The following examples illustrate how supervisors will evaluate
adjustments:
Example 1
A bank uses the last five years of internal default history to estimate grade PDs.
However, they recognize that the internal experience does not include any highdefault years. In order to remedy this and still take advantage of its experience,
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the bank uses external agency data to adjust the estimates upward. Using the
agency data, the bank calculates the ratio between the long-run average and the
mean default rate per grade over the last five years. The bank assumes that the
relationship observed in the agency data applies to its portfolio, and adjusts the
estimates for the internal data accordingly. This practice is consistent with the
standard.
Example 2
A bank uses internal default experience to estimate grade PDs. However, the
bank has historically failed to recognize defaults when the loss on the default
obligation was avoided by seizing collateral. The bank makes no adjustment for
such missing defaults. The realized default rate using the more inclusive
definition would be higher than that observed by the bank (and loss severity rates
would be correspondingly lower). This practice would not be consistent with the
standard, unless the bank demonstrates that the necessary adjustment is
immaterial.
C. Mapping
108. Mapping is the process of establishing a correspondence between the
bank’s current obligors and the reference obligor data used in the default model.
Hence, mapping involves identifying how default-related characteristics of the
current portfolio correspond to the characteristics of reference obligors. Such
characteristics might include financial and nonfinancial variables, and assigned
ratings or grades.
109. Mapping can be thought of as taking each obligor in the bank's portfolio
and characterizing it as if it were part of the reference data. There are two broad
approaches to the mapping process:
Obligor mapping: Each portfolio obligor is mapped to the reference data
based on its individual characteristics. For example, if a bank applies a
default model, a default probability will be generated for each obligor. That
individual default probability is then used to assign each obligor to a
particular internal grade, based on the bank's established criteria. To
obtain a final estimate of the grade PD in the subsequent application
stage, the bank averages the default probabilities of individual obligors
within each grade.
Grade mapping: Characteristics of the obligors within an internal grade
are averaged or otherwise summarized to construct a “typical” or
representative obligor for each grade. Then, the bank maps that
representative obligor to the reference data. For example, if the bank uses
a default model, the default probability associated with that typical obligor
will serve as the grade PD in the application stage. Alternatively, the bank
may map the typical obligor to a particular external rating grade based on
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quantitative and qualitative characteristics, and assign the long-run default
rate for that rating to the internal grade in the application stage.
110. Either grade mapping or obligor mapping can be part of the quantification
process; either method can produce a single PD estimate for each grade in the
application stage. However, in the absence of other compelling considerations,
banks should use obligor mapping for two reasons:
•
First, default probabilities are nonlinear under many estimation
approaches. As a result, the default probability of the typical obligor — the
result of a grade mapping approach — is often lower than the mean of the
individual obligor default probabilities from the obligor mapping approach.
For example, consider a bank that maps to the S&P scale and uses
historical S&P bond default rates. For ease of illustration, suppose that
one internal grade contains only three obligors that individually map to BB,
BB-, and B+. The historical default rates for these three grades are 1.07,
1.76, and 3.24 percent, respectively (based on 1981–2001 data). Using
obligor mapping, those rates would be assigned directly to the three
obligors, yielding a mean PD of 2.02 percent for the grade. Using grade
mapping, the grade PD would be only 1.76, because the grade’s typical
obligor is rated BB-.
•
Second, a hypothetical obligor with a grade’s average characteristics may
not represent well the risks presented by the grade’s typical obligor. For
example, a bank might observe that obligors with high leverage and low
earnings variability have about the same default risk as obligors with low
leverage and high earnings variability. These two types of obligors might
both end up in the same grade, for example, Grade 6. If so, the typical
obligor in Grade 6 would have moderate leverage and moderate earnings
variability — a combination that might fail to reflect any of the individual
obligors in Grade 6, and that could easily result in a PD for the grade that
is too low.
111. A bank electing to use grade mapping instead of obligor mapping should
be especially careful in choosing a “typical” obligor for each grade. Doing so
typically requires that the bank examine the actual distribution of obligors within
each grade, as well as the characteristics of those obligors. Banks should be
aware that different measures of central tendency (such as mean, median, or
mode) will give different results, and that these different results may have a
material effect on a grade’s PD; they must be able to justify their choice of a
measure. Banks must have a clear and consistent policy toward the calculation.
S.
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The mapping must be based on a robust comparison of available data
elements that are common to the portfolio and the reference data.
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112. Sound mapping practice uses all common elements that are available in
the data as the basis for mapping. If a bank chooses to ignore certain common
variables or to weight some variables more heavily than others, those choices
must be supported. Mapping should also take into account differences in rating
philosophy (for example, point-in-time or through-the-cycle) between any ratings
embedded in the reference data set and the bank’s own rating regime.
113. A mapping should be plausible, and should be consistent with the rating
philosophy established by the bank as part of its obligor rating policy. For a bank
that uses grade mapping, levels and ranges of key variables within each internal
grade should be close to values of similar variables for corresponding obligors
within the reference data.
114. The standard allows for use of a limited set of common variables that are
predictive of default risk, in part to permit flexibility in early years when data may
be far from ideal. Nevertheless, banks will eventually be expected to use
variables that are widely recognized as the most reliable predictors of default risk
in mapping exercises. In the meantime, banks relying on data elements that are
weak predictors must compensate by making their estimates more conservative.
For example, leverage and cash flow are widely recognized to be reliable
predictors of corporate default risk. Borrower size is also predictive, but less so.
A mapping based solely on size is by nature less reliable than one based on
leverage, cash flow, and size.
Example 1
In estimating PD, a bank relies on observed default rates on bonds in various
agency grades for PD quantification. To map its internal grades to the agency
grades, the bank identifies variables that together explain much of the rating
variation in the bond sample. The bank then conducts a statistical analysis of
those same variables within its portfolio of obligors, using a multivariate distance
calculation to assign each portfolio obligor to the external rating whose
characteristics it matches most closely (for example, assigning obligors to ratings
so that the sum of squared differences between the external grade averages and
the obligor’s characteristics is minimized). This practice is broadly consistent
with the standard.
Example 2
A bank uses grade mapping to link portfolio obligors to the reference data set
described by agency ratings. The bank looks at publicly rated portfolio obligors
within an internal grade to determine the most common external rating, does the
same for all grades, and creates a correspondence between internal and external
ratings. The strength of the correspondence is a function of the number of
externally rated obligors within each grade, the distribution of those external
ratings within each grade and the similarity of externally rated obligors in the
grade to those not externally rated. This practice is broadly consistent with this
standard, but would require a comparison of rating philosophies and may require
adjustments and the addition of margins of conservatism.
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S.
A mapping process must be established for each reference data set and
for each estimation model.
115. Banks should never assume that a mapping is self-evident. Even a rating
system that has been explicitly designed to replicate external agency ratings may
or may not be effective in producing a replica; formal mapping is still necessary.
Indeed, in such a system the kind of analysis involved in mapping may help
identify inconsistencies in the rating process itself.
116. A mapping process is needed even where the reference obligors come
from internal historical experience. Banks must not assume that internal data do
not require mapping, because changes in bank strategy or external economic
forces may alter the composition of internal grades or the nature of the obligors in
those grades over time. Mappings must be reaffirmed regardless of whether
rating criteria or other aspects of the ratings system have undergone explicit
changes during the period covered by the reference data set.
117. Banks often use multiple reference data sets, and then combine the
resulting estimates to get a grade PD. A bank that does that must conduct a
rigorous mapping process for each data set.
118. Supervisors expect all meaningful characteristics of obligors to be factored
directly into the rating process; this should include characteristics like the
obligor’s industry or physical location. But in some circumstances, certain effects
related to industry, geography, or other factors are not reflected in rating
assignments or default estimates. In such cases, it may be appropriate for banks
to capture the impact of the omissions by using different mappings for different
business lines or types of obligors. Supervisors expect this practice to be
transitional; banks will eventually be required to incorporate the omitted effects
into the rating system and the estimation process as they are uncovered and
documented, rather than adjusting the mapping.
Example 1
The bank maps its internal grades carefully to one rating agency, and then
assumes a correspondence to another agency’s scale despite known differences
in the rating methods of the two agencies. The bank then applies a mean of the
grade default rates from these two public debt-rating agencies to its internal
grades. This practice is not consistent with the standard, because the bank
should map to each agency’s scale separately.
Example 2
A bank uses internal historical data as its reference data. The bank computes a
mean default rate for each grade as the grade PD for capital purposes, and
asserts that mapping is unnecessary because "its strong credit culture ensures
that a 4 is always a 4." This practice is not consistent with the standard, because
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no mapping has been done; there is no assurance that a representative obligor in
a grade today is comparable to an obligor in that same grade in the past.
S.
The mapping must be updated and independently validated regularly.
119. The appropriate mapping between a bank's portfolio and the reference
data may change over time. For example, relationships between internal grades
and external agency grades may change during the economic cycle because of
differences in rating philosophy. Similarly, distance-to-default measures for
obligors in a given grade may not be constant over time. These likely changes
make it imperative that the bank update all mappings regularly.
120. Sound validation practices may include tests for internal consistency such
as “reverse mapping.” Using this technique, a bank evaluates obligors from the
reference data set as if they were subject to the bank’s rating system (that is, part
of the bank’s current portfolio). The bank’s mapping is then applied to these
reverse-mapped obligors to see whether the mapped characterization of the
reference obligor is consistent with that of the initial evaluation.4 Another
valuable technique is to apply different mapping methods and compare the
results. For example, mappings based on financial ratio comparisons can be
rechecked using mappings based on available external ratings.
Example 1
A bank mapped its internal grades to the rating scale of one public debt-rating
agency in 1992. Since then, the bank has completed a major acquisition of
another large bank and significantly changed its business mix in other ways. The
bank continues to use the same mapping, without reassessing its validity. This
practice is not consistent with the standard.
D. Application
121. In the application stage, the bank applies the PD estimation method to the
current portfolio of obligors using the mapping process. It obtains final PD
estimates for each rating grade, which will be used to calculate minimum
regulatory capital. To arrive at those estimates, a bank may adjust the raw
results derived from the estimation stage. For example, it might aggregate
individual obligor default probabilities to the rating grade level, or smooth results
because a rating grade’s PD estimate was higher than a lower quality grade. The
bank must explain and support all adjustments when documenting its
quantification process.
4
For example, suppose a bank asserts that its Grade 3 corresponds to an S&P rating of A.
Applying reverse mapping, the bank would take a sample of A-rated obligors from the reference
data, run them through the bank’s rating process (perhaps a simplified version), and check to see
that those obligors usually receive a grade of 3 on the bank’s internal scale.
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Example
A bank uses external data to estimate long-run average PDs for each grade. The
resulting PD estimate for Grade 2 is slightly higher than the estimate for Grade 3,
even though Grade 2 is supposedly of higher credit quality. The bank uses
statistics to demonstrate that this anomaly occurred because defaults are rare in
the highest quality rating grades. The bank judgmentally adjusts the PD
estimates for grades 2 and 3 to preserve the expected relationship between
obligor grade and PD, but requires that total risk-weighted assets across both
grades using the adjusted PD estimates be no less than total risk-weighted
assets based on the unadjusted estimates, using a typical distribution of obligors
across the two grades. Such an adjustment during the application stage is
consistent with this guidance.
S.
IRB institutions that aggregate the default probabilities of individual
portfolio obligors when calculating PD estimates for internal grades must
have a clear policy governing the aggregation process.
122. As noted above, mapping may be grade-based or obligor-based. Gradebased mappings naturally provide a single PD per grade, because the estimated
default model is applied to the representative obligor for each grade. In contrast,
obligor-based mappings must aggregate in some manner the individual PD
estimates to the grade level. The expectation is that the grade PD estimate will
be calculated as the mean. The bank will be allowed to calculate this estimate
differently only if it can demonstrate that the alternative method provides a better
estimate of the long-run average PD. To obtain this evidence, the bank must at
least compare the results of both methods.
S.
IRB institutions that combine estimates from multiple sets of reference
data must have a clear policy governing the combination process, and
must examine the sensitivity of the results to alternative combinations.
123. Because a bank should make use of as much information as possible
when mapping, it will usually use multiple data sets. The manner in which the
data or the estimates from those multiple data sets are combined is extremely
important. A bank must document its justification for the particular combination
methods selected. Those methods must be subject to appropriate approval and
oversight.
124. The data may come from the same basic data source but from different
time periods or from different data sources altogether. For example, banks often
combine internal data with external data, use external data from different sample
periods, or combine results from corporate-bond default databases with results
from equity-based models of obligor default. Different combinations will produce
different PD estimates. The bank should investigate alternative combinations
and document the impact on the estimates. When ultimate results are highly
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sensitive to how estimates from different data sources are combined, the bank
must choose among the alternatives conservatively.
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III. Loss Given Default (LGD)
125. The LGD estimation process is similar to the PD estimation process. The
bank identifies a reference data set of defaulted credits and relevant descriptive
characteristics. Once the bank obtains these data sets (with the facility
characteristics), it must select a technique to estimate the economic loss per
dollar of exposure at default, for a defaulted exposure with a given array of
characteristics. The bank’s portfolio must then be mapped, so that the model can
be applied to generate an estimate of LGD for each portfolio transaction or
severity grade.
A. Data
126. Unlike reference data sets used for PD estimation, data sets for severity
estimation contain only exposures to defaulting obligors. At least two broad
categories of data are necessary to produce LGD estimates.
127. First, data must be available to calculate the actual economic loss
experienced for each defaulted facility. Such data may include the market value
of the facility at default, which can be used to proxy a recovery rate. Alternatively,
economic loss may be calculated using the exposure at the time of default, loss
of principal, interest, and fees, the present value of subsequent recoveries and
related expenses (or the costs as calculated using an approved allocation
method), and the appropriate discount rate.
128. Second, factors must be available to group the defaulted facilities in
meaningful ways. Characteristics that are likely to be important in predicting loss
rates include whether or not the facility is secured and the type and coverage of
collateral if the facility is secured, seniority of the claim, general economic
conditions, and obligor’s industry. Although these factors have been found to be
significant in existing academic and industry studies, a bank's quantification of
LGD certainly need not be limited to these variables. For example, a bank might
expand its loss severity research by examining many other potential drivers of
severity (characteristics of an obligor that might help the bank predict the severity
of a loss), including obligor size, line of business, geographic location, facility
type, obligor ratings (internal or external), historical internal severity grade, or
tenor of the relationship.
129. A bank must ensure that the reference data remains applicable to its
current portfolio of facilities. It must implement established processes to ensure
that reference data sets are updated when new data become available. All data
sources, variables, and the overall processes concerning data collection and
maintenance must be fully documented, and that documentation should be
readily available for review.
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S.
The sample period for the reference data must be at least seven years,
and must include periods of economic stress during which defaults were
relatively high.
130. Seven years is the minimum sample period for the LGD reference data. A
longer sample period is desirable, because more default observations will be
available for analysis and may serve to refine severity estimates. In any case, a
bank must select a sample period that includes episodes of economic stress,
which are defined as periods with a relatively high number of defaults. Inclusion
of stress periods increases the size and potentially the breadth of the reference
data set. According to some empirical studies, the average loss rate is higher
during periods of stress.
Example 1
A bank intends to rely primarily on internal data when quantifying all parameter
estimates, including LGD. Its internal data cover the period 1994 through 2000.
The bank will continue to extend its data set as time progresses. Its current
policy mandates that credits be resolved within two years of default, and the data
set contains the most recent data available. Although the current data set
satisfies the seven-year requirement, the bank is aware that it does not include
stress periods. In comparing its loss estimates with rates published in external
studies for similarly stratified data, the bank observes that its estimates are
systematically lower. To be consistent with the standard, the bank must take
steps to include stress periods in its estimates.
S.
The definition of default within the reference data must be reasonably
consistent with the IRB definition of default.
131. This standard parallels a similar standard in the section on PD. The
following examples illustrate how it applies in the case of LGD.
Example 1
For LGD estimation, a bank includes in its default data base only defaulted
facilities that actually experience a loss, and excludes credits for which no loss
was recorded because liquidated collateral covered the loss (effectively applying
a "loss given loss" concept). This practice is not consistent with the standard
because the bank's default definition for LGD is narrower than the IRB definition.
Example 2
A bank relies on external data sources to estimate LGD because it lacks
sufficient internal data. One source uses “bankruptcy filing” to indicate default
while another uses “missed principal or interest payment,” and the two sources
result in significantly different loss estimates for the severity grades defined by
the bank. The bank’s practice is not consistent with the standard, and the bank
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should determine whether the definitions used in the reference data sets differ
substantially from the IRB definition. If so, and the differences are difficult to
quantify, the bank should seek other sources of reference data. For more minor
differences, the bank may be able to make appropriate adjustments during the
estimation stage.
B. Estimation
132. Estimation of LGD is the process by which characteristics of the reference
data are related to loss severity. The relevant characteristics that help explain
how severe losses tend to be upon default might include variables such as
seniority, collateral, facility type, or business line.
S.
The estimates of loss severity must be empirically based and must reflect
the concept of “economic loss.”
133. Loss severity is defined as economic loss, which is different from
accounting measures of loss. Economic loss captures the value of recoveries
and direct and indirect costs discounted to the time of default, and it should be
measured for each defaulted facility. The scope of the cash flows included in
recoveries and costs is meant to be broad. Workout costs that can be clearly
attributed to certain facilities or types of facilities must be reflected in the bank’s
LGD assignments for those exposures. When such allocation is not practical, the
bank may assign those costs using factors based on broad averages.
134. A bank must establish a discount rate that reflects the time value of money
and the opportunity cost of funds to apply to recoveries and costs. The discount
rate must be no less than the contract interest rate on new originations of a type
similar to the transaction in question, for the lowest-quality grade in which a bank
originates such transactions.5 Where possible, the rate should reflect the fixed
rate on newly originated exposures with term corresponding to the average
resolution period of defaulting assets.
135. Ideally, severity should be measured once all recoveries and costs have
been realized. However, a bank may not resolve a defaulted obligation for many
years following default. For practical purposes, banks may choose to close the
period of observation before this final resolution occurs — that is, at a point in time
when most costs have been incurred and when recoveries are substantially
complete. Banks that do so should estimate the additional costs and recoveries
that would likely occur beyond this period and include them in the LGD estimates.
A bank must document its choice of the period of observation, and how it
estimated additional costs and recoveries beyond this period.
5
The appropriate discount rate for IRB purposes may differ from the contract interest rate
required under FAS 114 for accounting purposes rate.
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136. LGD for each type of exposure must be the loss per default (expressed as
a percentage of exposure at default) expected during periods when default rates
are relatively high. This expected loss rate is referred to as “stress-condition
LGD.” For cases in which loss severities do not have a material degree of
cyclical variability, use of the long-run default-weighted average is appropriate,
although stress-condition LGD generally exceeds this average.
137. The drivers of severity can be linked to loss estimates in a number of
ways. One approach is to segment the reference defaults into groups that do not
overlap. For example, defaults could be grouped by business line, predominant
collateral type, and loan-to-value coverage. The LGD estimate for each category
is the mean loss calculated over the category’s defaulted facilities. Loss must be
calculated as the default-weighted average (where individual defaults receive
equal weight) rather than the average of annual loss rates, and must be based on
results from periods during which default rates were relatively numerous if loss
rates are materially cyclical.
138. Banks can also draw estimates of LGD from a statistical model. For
example, they can build a regression model of severity using data on loss
severity and some quantitative measures of the loss drivers. Any model must
meet the requirements for model validation discussed in Chapter 1. Other
methods for computing LGD could also be appropriate.
Example 1
A bank has internal data on defaulted facilities, including information on business
line, facility type, seniority, and predominant collateral type (if the facility is
secured). The data allow for a reasonable calculation of economic loss. The
data span eight years and include three years that can be termed high-default
years. After analyzing the economic cycle using internal and external data, the
bank concludes that the data show no evidence of material cyclical variability in
loss severities, and that the default data span enough experience to allow
estimation of a long-run average. On the basis of preliminary analysis, the bank
determines that the drivers of loss severity for large corporate facilities are similar
to those for middle-market loans, and that the two groups can be estimated as a
pool. Again on the basis of preliminary analysis, the bank segments this pool by
seniority and by six collateral groupings, including unsecured. These groupings
contain enough defaults to allow reasonably precise estimates. The loss severity
estimates are then calculated by averaging loss rates within each segment. This
practice is consistent with the standard.
Example 2
A bank uses internal data in which information on security and seniority is
lacking. The bank groups corporate and middle-market defaulted facilities into a
single pool and calculates the LGD estimate as the mean loss rate. No
adjustments for the lack of data are made in the estimation or application steps.
This practice is unacceptable because there is ample external evidence that
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security and seniority matter in these segments. A bank with such limited internal
default data must incorporate external or pooled data into the estimation.
Example 3
A bank determines that a business unit – for example, a unit dedicated to a
particular type of asset-based lending – forms a homogeneous pool for the
purposes of estimating loss severity. That is, although the facilities in this pool
may differ in some respects, the bank determines that they share a similar loss
experience in default. The bank must provide reasonable support for this pooling
through analysis of lending practices and available internal and external data. In
this example, the mean of a single segment is consistent with the standard.
S.
Judgmental adjustments may play an appropriate role in LGD estimation,
but must not be biased toward lower estimates.
139. It is difficult to make general statements about good and bad practices in
this area, because adjustments can take many different forms. The following
examples illustrate how supervisors would be likely to evaluate particular
adjustments observed in practice.
Example 1
A bank divides observed defaults into segments according to collateral type. One
of the segments has too few observations to produce a reliable estimate. Relying
on external data and judgment, the bank determines that the segment’s
estimated severity of loss falls somewhere between the estimates for two other
categories. This segment’s severity is set judgmentally to be the mean of the
estimates for the other segments. This practice is consistent with the standard.
Example 2
A bank does not know when recoveries (and related costs) occurred in a portfolio
segment; therefore, it cannot properly discount the segment’s cash flows.
However, the bank has sufficient internal data to calculate economic loss for
defaulted facilities in another portfolio segment. The bank can support the
assumption that the timing of cash flows for the two segments is comparable.
Using the available data and informed judgment, the bank estimates that the
measured loss without discounting should be grossed up to account for the time
value of money and the opportunity cost of funds. This practice is consistent with
the standard.
Example 3
A bank segments internal defaults in a business unit by some factors, including
collateral. Although the available internal and external evidence indicates a
higher LGD, the bank judgmentally assigns a loss estimate of 2 percent for
facilities secured by cash collateral. The basis for this adjustment is that the
lower estimate is justified by the expectation that the bank would do a better job
of following policies for monitoring cash collateral in the future. Such an
adjustment is generally not appropriate because it is based on projections of
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future performance rather than realized experience. This practice is not
consistent with the standard.
C. Mapping
140. LGD mapping follows the same general principles that PD mapping does.
A mapping must be plausible and must be based on a comparison of severityrelated data elements common to both the reference data and the current
portfolio. The mapping approach is expected to be unbiased, such that the
exercise of judgment does not consistently lower LGD estimates. The default
definitions in the reference data and the current portfolio of obligors should be
comparable. The mapping process must be updated regularly, well-documented,
and independently reviewed.
S.
A bank must conduct a robust comparison of available common elements
in the reference data and the portfolio.
141. Mapping involves matching facility-specific data elements available in the
current portfolio to the factors in the reference data set used to estimate expected
loss severity rates. Examples of factors that influence loss rates include
collateral type and coverage, seniority, industry, and location.
142. At least three kinds of mapping challenges may arise. First, even if
similarly named variables are available in the reference data and portfolio data,
they may not be directly comparable. For example, the definition of particular
collateral types, or the meaning of “secured,” may vary from one application to
another. Hence, a bank must ensure that linked variables are truly similar.
Although adjustments to enhance comparability can be appropriate, they must be
rigorously developed and documented. Second, levels of aggregation may vary.
For example, the reference data may only broadly identify collateral types, such
as financial and nonfinancial. The bank’s information systems for its portfolio
might supply more detail, with a wide variety of collateral type identifiers. To
apply the estimates derived from the reference data, the internal data must be
regrouped to match the coarser level of aggregation in the reference data. Third,
reference data often do not include workout costs and will often use different
discounting. Judgmental adjustments for such problems must be welldocumented and, as much as possible, empirically based.
S.
A mapping process must be established for each reference data set and
for each estimation model.
143. Mapping is never self-evident. Even when reference data are drawn from
internal default experience, a bank must still link the characteristics of the
reference data with those of the current portfolio.
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144. Different data sets and different approaches to severity estimation may be
entirely appropriate, especially for different business segments or product lines.
Each mapping process must be specified and documented.
D. Application
145. At the application stage, banks apply the LGD estimation framework to
their current portfolio of credit exposures. Doing so might require them to
aggregate individual LGD estimates into broader averages (for example, into
discrete severity grades) or to combine estimates in various ways.
146. The inherent variability of recovery, due in part to unanticipated
circumstances, demonstrates that no facility type is wholly risk-free, regardless of
structure, collateral type, or collateral coverage. The existence of recovery risk
dictates that application of a zero percent LGD is not acceptable.
S.
IRB institutions that aggregate LGD estimates for severity grades from
individual exposures within those grades must have a clear policy
governing the aggregation process.
147. Banks with discrete severity grades compute a single estimate of LGD for
a representative exposure within each of those grades. If a bank with a discrete
scale of severity grades maps those grades to the reference data using grade
mapping, there will be a single estimate of LGD for each grade, and the bank
does not need to aggregate further. However, if the bank maps at the individual
transaction level, the bank may then choose to aggregate those individual LGD
estimates to the grade level and use the grade LGD in capital calculations.
Because different methods of aggregation are possible, a bank must have a clear
policy regarding how aggregation should be accomplished; in general, simple
averaging is preferred. (This standard is irrelevant for banks that choose to
assign LGD estimates directly to individual exposures rather than grades,
because aggregation is not required in that case.)
S.
An IRB institution must have a policy describing how it combines multiple
sets of reference data.
148. Multiple data sets may produce superior estimates of loss severity, if the
results are appropriately combined. Combining such sets differently usually
produces different estimates of LGD. As a matter of internal policy, a bank
should investigate alternative combinations, and document the impact on the
estimates. If the results are highly sensitive to the manner in which different data
sources are combined, the bank must choose conservatively among the
alternatives.
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IV. Exposure at Default (EAD)
149. Compared with PD and LGD quantification, EAD quantification is less
advanced. As such, it is addressed in somewhat less detail in this guidance than
are PD and LGD quantification. Banks should continue to innovate in the area
EAD estimation, refining and improving practices in EAD measurement and
prediction. Additional supervisory guidance will be provided as more data
become available and estimation techniques evolve.
150. A bank must provide an estimate of expected EAD for each facility in its
portfolio. EAD is defined as the bank’s expected gross dollar exposure of the
facility upon the obligor’s default. For fixed exposures like term loans, EAD is
equal to the current amount outstanding. For variable exposures such as loan
commitments or lines of credit, exposure is equal to current outstandings plus an
estimate of additional drawings up to the time of default. This additional
drawdown, identified as loan equivalent exposure (LEQ) in many institutions, is
typically expressed as a percentage of the current total committed but undrawn
amount. EAD can thus be represented as:
EAD = current outstanding + LEQ x (total committed – current outstanding)
As it is the LEQ that must be estimated, LEQ is the focus of this guidance.
151. Even though EAD estimation is less sophisticated than PD and LGD
estimation, a bank still develops EAD estimates by working through the four
stages that produce the other types of quantification: The bank must use a
reference data set; it must apply an estimation technique to produce an expected
total dollar exposure at default for a facility with a given array of characteristics; it
must map its current portfolio to the reference data; and, by applying the
estimation model, it must generate an EAD estimate for each portfolio facility or
facility-type, as the case may be.
A. Data
152. Like reference data sets used for LGD estimation, LEQ data sets contain
only exposures to defaulting obligors. In many cases, the same reference data
may be used for both LGD and LEQ. In addition to relevant descriptive
characteristics (referred to as “drivers”) that can be used in estimation, the
reference data must include historical information on the exposure (both drawn
and undrawn amounts) as of some date prior to default, as well as the drawn
exposure at the date of default.
153. As discussed below under “Estimation,” LEQ estimates may be developed
using either a cohort method or a fixed-horizon method. The bank’s reference
data set must be structured so that it is consistent with the estimation method the
bank applies. Thus, the data must include information on the total commitment,
the undrawn amount, and the exposure drivers for each defaulted facility, either
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at fixed calendar dates for the cohort method or at a fixed interval prior to the
default date for the fixed-horizon method.
154. The reference data must contain variables that enable the bank to group
the exposures to defaulted obligors in meaningful ways. Obligor and facility risk
ratings are commonly believed to be significant characteristics for predicting
additional drawdown. Since less empirical research has been done on EAD
estimation, little is known about other potential drivers of EAD. Among the many
possibilities, banks may consider time from origination, time to expiration or
renewal, economic conditions, risk rating changes, or certain types of covenants.
Some potential drivers may be linked to a bank’s credit risk management skills,
while others may be exogenous. Industry practice is likely to improve as banks
extend their research to identify other meaningful drivers of EAD.
155. A bank must ensure continued applicability of the reference data to its
current portfolio of facilities. The reference data must include the types of
variable exposures found in a bank’s current portfolio. The definitions of default
and exposure in the reference data should be consistent with the IRB definition of
default, and consistent with the definitions used for PD and LGD quantification.
Established processes must be in place to ensure that reference data sets are
updated when new data are available. All data sources, variables, and the
overall processes governing data collection and maintenance must be fully
documented, and that documentation should be readily available for review.
156. Seven years of data are required for EAD (or LEQ) estimation. The
sample should include periods during which default rates were relatively high,
and ideally cover a complete economic cycle.
B. Estimation
157. To derive LEQ estimates, characteristics of the reference data are related
to additional drawings preceding a default event. The estimation process must
be capable of producing a plausible estimate of LEQ to support the EAD
calculation for each facility. Two broad types of estimation methods are used in
practice, the cohort method and the fixed-horizon method.
158. Under the cohort method, a bank groups defaults into discrete calendar
periods (such as a year or a quarter). The bank then estimates the relationship
between the drivers as of the start of that calendar period, and EAD or LEQ for
each exposure to a defaulter. For each exposure category (that is, for each
combination of exposure drivers identified by the bank), the LEQ estimate is
calculated as the mean additional drawing for facilities in that category. To
combine results for multiple periods into a single long-run average, the period-byperiod means should be weighted by the proportion of defaults occurring in each
period.
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159. Under the fixed-horizon method, for each exposure to a defaulted obligor
the bank compares additional drawdowns to the total commitment but undrawn
amount that existed at the start of a fixed interval prior to the date of the default
(the horizon). For example, the bank might base its estimates on a reference
data set that supplies the actual exposure at default along with the drawn and
undrawn amounts (as well as relevant drivers) at a date a fixed number of months
prior to the date of each default, regardless of the actual calendar date on which
the default occurred. Estimates of LEQ are computed from the average
drawdowns that occur over the fixed-horizon interval, for whatever combinations
of the driving variables the bank has determined are relevant for explaining and
predicting exposure at default.
160. Evidence may indicate that LEQ estimates are positively correlated with
economic downturns; that is, it may be that LEQs increase during high-default
periods. If so, the higher drawdowns that occur during high-default periods are
denoted “stress-condition LEQs,” analogous to the “stress-condition LGDs”
discussed earlier in this chapter. For any exposure type whose LEQ estimates
exhibit material cyclicality, a bank must use the stress-condition LEQ for
purposes of calculating EAD.
161. In general, all available data should be used; particular observations or
time periods should not be excluded from the data sample. Any adjustments a
bank makes to the estimation results should be justified and fully documented.
The analysis should be refreshed periodically as new data become available, and
a bank should have a process in place to ensure that advances in analytical
techniques and industry practice are considered as they emerge and are
incorporated as appropriate. LEQ estimates should be updated at least annually.
Detailed documentation, ongoing validation, and adequate oversight are
fundamental controls that support a sound estimation process.
C. Mapping
162. If the same variables that drive exposure in the reference data are also
available for facilities in the portfolio, mapping may be relatively easy. However,
the bank must still review the definitions to ensure that variables that seem to be
the same actually are. If the relevant variables are not available in a bank’s
current portfolio information system, the bank will encounter the same mapping
complexities that it does when mapping for PD and LGD in similar circumstances.
A bank should have well-documented policies that govern the mapping. Any
exceptions to mapping policy should be reviewed, justified and fully documented.
Mapping may be done for each exposure or for broad categories of exposure; the
latter would be analogous to the “grade mapping” discussed earlier in this
chapter.
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D. Application
163. In the application stage, the estimated relationship between drivers and
LEQ is applied to the bank’s actual portfolio. To ensure that estimated EAD is at
least as large as the currently drawn amount for all exposures, LEQs must not be
negative. Multiple reference data sets may be used for LEQ estimation and
combined at the application stage; those combinations should be rigorously
developed, approved, and documented. Any smoothing or use of expert
judgment to adjust the results should be well-justified and clearly documented.
This includes any adjustment for definitions of default that do not meet the
supervisory standards. The less robust the process, the more conservative the
result should be.
164. Some facility types may be treated as exceptions, and assigned an LEQ
that does not vary with characteristics such as line of business or risk rating.
Such exceptional treatment should be clearly justified, and the justification should
be fully documented.
165. EAD may be particularly sensitive to changes in the way banks manage
individual credits. For example, a change in policy regarding covenants may
have a significant impact on LEQ. When such changes take place, the bank
should consider them when making its estimates — and it should do so from a
conservative point of view. Policy changes likely to significantly increase LEQ
should prompt immediate increases in LEQ estimates. If a bank’s policy changes
seem likely to reduce LEQ, estimates should be reduced only after the bank
accumulates a significant amount of actual experience under the new policy to
support the reductions.
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V. Maturity (M)
166. A bank must assign a value of effective remaining maturity (M) to each
credit exposure in its portfolio. In general, M is the weighted-average number of
years to receipt of the cash flows the bank expects under the contractual terms of
the exposure, where the weights are equal to the fraction of the total
undiscounted cash flow to be received at each date. Mathematically, M is given
by:
M = ∑ t × wt
t
where wt is the fraction of the total cash flow received at time t, that is:
w t = Ct / ∑ Ct
t
Ct is the undiscounted cash flow received at time t, with t measured in years from
the date of the calculation of M.
167. Effective maturity, sometimes referred to as “average life,” need not be a
whole number, and often is not. For example, if 33 percent of the cash flow is
expected at the end of one year (t=1) and the other 67 percent two years from
today (t=2), then M is calculated as:
M = (1× 0.33 ) + ( 2 × 0.67 ) = 1.67
for an effective maturity of 1.67 years. This value of M would be used in the IRB
capital calculation.
168. The relevant cash flows are the future payments the bank expects to
receive from the obligor, regardless of form; they may include payments of
interest or fees, principal repayments, or other types of payments depending on
the structure of the transaction. For exposures whose cash flow schedule is
virtually predetermined unless the obligors defaults (fixed-rate loans, for
example), the calculation of the weighted-average remaining maturity is
straightforward, using the scheduled timing and amounts of the individual
undiscounted cash flows. These cash flows should be the contractually expected
payments; the bank should not take into account the possibility of delayed or
reduced cash flows due to potential future default.
169. Cash flows associated with other types of credit exposures may be
somewhat less certain. In such cases, the bank must establish a method of
projecting expected cash flows. In general, the method used for any exposure
should be the same as the one used by the bank for purposes of valuation or risk
management. The method must be well-documented and subject to independent
review and approval. A bank must demonstrate that the method used is standard
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industry practice, that it is widely used within the bank for purposes other than
regulatory capital calculations, or both.
170. To be conservative, a bank may set M equal to the maximum number of
years the obligor could take to fully discharge the contractual obligation (provided
that the maximum is not longer than five years, as noted below). In many cases,
this maximum will correspond to the stated or nominal maturity of the instrument.
Banks must make this conservative choice (maximum nominal maturity) if the
timing and amounts of the cash flows on the exposure cannot be projected with a
reasonable degree of confidence.
171. Certain over-the-counter derivatives contracts and repurchase
transactions may be subject to master netting agreements. In such cases, the
bank may compute a single value of M for the transactions as a group by
weighting each individual transaction’s effective maturity by that transaction’s
share of the total notional value subject to the netting agreement, and summing
the result across all of the transactions.
172. For IRB capital calculations, the value of M for any exposure is subject to
certain upper and lower limits, regardless of the actual effective maturity of the
exposure. In all cases, the value of M should be no greater than 5 years. If an
exposure clearly has an effective maturity that exceeds this upper limit, the bank
may simply use a value of M=5 rather than calculating the actual effective
maturity.
173. For most exposures, the value of M must be no less than one year. For
certain short-term exposures (repo-style transactions, money market
transactions, trade finance-related transactions, and exposures arising from
payment and settlement processes) that are not part of a bank’s ongoing
financing of a borrower and that have an original maturity of less than three
months, M may be set as low as one day. For over-the-counter derivative and
repurchase-style transactions subject to a master netting agreement, weighted
average maturity must be set at no less than five days.
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VI. Validation
174. Values of PD, LGD, and EAD are estimates with implications for credit risk
and the future performance of a bank’s credit portfolio under IRB; in essence,
they are forecasts. “Validation” of these estimates describes the full range of
activities used to assess their quality as forecasts of default rates, loss severity
rates, and exposures at default. Chapter 1 discusses validation of IRB systems
in general; this section focuses specifically on ratings quantification, which
includes the assignment of PD to obligor grades and the assignment of LGD,
EAD, and M to exposures.
S.
A validation process must cover all aspects of IRB quantification.
175. Banks must have a process for validating IRB quantification; their policies
must state who is accountable for validation, and describe the actions that will
proceed from the different possible results. Validation should focus on the three
estimated IRB parameters (PD, LGD, and EAD). Although the established
validation process should result in an overall assessment of IRB quantification for
each parameter, it also must cover each of the four stages of the quantification
process as described in preceding sections of this chapter (data, estimation,
mapping, and application). The validation process must be fully documented,
and must be approved by appropriate levels of the bank’s senior management.
The process must be updated periodically to incorporate new developments in
validation practices and to ensure that validation methods remain appropriate;
documentation must be updated whenever validation methods change.
176. Banks should use a variety of validation approaches or tools; no single
validation tool can completely and conclusively assess IRB quantification. Three
broad types of tools that are useful in this regard are evaluation of the conceptual
soundness of the approach to quantification (evaluation of logic), comparison to
other sources of data or estimates (benchmarking), and comparisons of actual
outcomes to predictions (back-testing). Each of these types of tools has a role to
play in validation, although the role varies across the four stages of quantification.
177. Evaluation of logic is essential in validating all stages of the quantification
process. The quantification process requires banks to adopt methods, choose
variables, and make adjustments; each of these actions requires an exercise of
judgment. Validation should ensure that these judgments are plausible and
informed.
178. A bank should also validate estimates by comparing them with relevant
external sources, a process broadly described as benchmarking. “External” in
this context refers to anything other than the specific reference data, estimation
approach, or mapping under consideration. Reference data can be compared
with other data sources; choices of variables can be compared with similar
choices made by others; estimation results can be compared with the results of
alternative estimation methods using the same reference data. Other data
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sources may show that default and severity rates across the economy or the
banking system are high or low relative to other periods, or may reveal unusual
effects in parts of the quality spectrum.
179. Effective validation must compare actual results with predictions. Such
comparisons, often referred to as “back-testing,” are valuable comprehensive
tests of the rating system and its quantification. However, they are only one
element of the broader validation regime, and should not be a bank’s only
method of validation. Because they test the results of the rating system as a
whole, they are unlikely to identify specific reasons for any divergence between
expectations and realizations. Rather they will indicate only that further
investigation is necessary.
180. By applying back-testing to the reference data set as it is updated with
new data, a bank can improve the estimation process. To further improve the
process, a bank must regularly compare realized default rates, loss severities,
and exposure-at-default experience from its portfolio with the PD, LGD, and EAD
estimates on which capital calculations are based. Realizations should be
compared with expected ranges based on the estimates. These expected ranges
should take into account the bank’s rating philosophy (the relative weight given to
current and stress conditions in assigning ratings). Depending on that philosophy,
year-by-year realized default rates and loss severities may be expected to differ
significantly from the long-run average. If a bank adjusts final estimates to be
conservative, it should likely do its back-testing on the unadjusted estimates.
181. A bank’s quantitative testing methods and other validation techniques
should be robust to economic cycles. A sound validation process should take
business cycles into account, and any adjustments for stages of the cycle should
be clearly specified in advance and fully documented as part of the validation
policy. The fact that a year has been “unusual” should not be taken as a reason
to abandon the bank’s standard validation practices.
S.
A bank must comprehensively validate parameter estimates at least
annually, must document the results, and must report these results to
senior management.
182. A full and comprehensive annual validation is a minimum for effective risk
management under IRB. More frequent validation may be appropriate for certain
parts of the IRB system and in certain circumstances; for example, during highdefault periods, banks should compute realized default and loss severity rates
more frequently, perhaps quarterly. They must document the results of
validation, and must report them to appropriate levels of senior risk management.
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S.
The validation policy must outline appropriate remedial responses to the
results of parameter validation.
183. The goal of validation should be to continually improve the rating process
and its quantification. To this end, the bank should establish thresholds or
accuracy tolerances for validation results. Results that breach thresholds should
bring an appropriate response; that response should depend on the results and
should not necessarily be to adjust the parameter estimates. When realized
default, severity, or exposures rates diverge from expected ranges, those
divergences may point to issues in the estimation or mapping elements of
quantification. They may also indicate potential problems in other parts of the
ratings assignment process. The bank’s validation policy must describe (at least
in broad terms) the types of responses that should be considered when relevant
action thresholds are crossed.
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Appendix to Chapter 2: Illustrations of the Quantification Process
This appendix provides examples to show how the logical framework
described in this guidance, with its four stages (data, estimation, mapping, and
application), applies when analyzing typical current bank practices. The
framework is broadly applicable — for PD or LGD or EAD; using internal, external,
or pooled reference data; for simple or complex estimation methods — although
the issues and concerns that arise at each stage depend on a bank’s approach.
These examples are intended only to illustrate the logic of the four-stage IRB
quantification framework, and should not be taken to endorse the particular
techniques presented in the examples. In fact, certain aspects of the examples
are not consistent with the standards outlined in this guidance.
Example 1: PD estimation from bond data
•
•
•
•
•
•
A bank establishes a correspondence between its internal
grades and external rating agency grades; the bank has
determined that its Grade 4 is equivalent to ¾ BB and ¼ B
on the Standard and Poor’s scale.
The bank regularly obtains published estimates of mean
default frequencies for publicly rated BB and B obligors in
North America from 1970 through 2002.
The BB and B historical default frequencies are weighted
75/25, and the result is a preliminary PD for the bank’s
internal Grade 4 credits.
However, the bank then increases the PD by 10 percent to
account for the fact that the S&P definition of default is more
lenient than the IRB definition.
The bank makes a further adjustment to ensure that the
resulting grade PD is greater than the PD attributed to Grade
3 and less than the PD attributed to Grade 5.
The result is the final PD estimate for Grade 4.
Process Analysis for Example 1:
Data – The reference data set consists of issuers of publicly rated debt in
North America over the period 1970 through 2002. The data description is
very basic: each issuer in the reference data is described only by its rating
(such as AAA, AA, A, BBB, and so on).
Estimation – The bank could have estimated default rates itself using a
database purchased from Standard and Poor’s, but since these estimates
would just be the mean default rates per year for each grade, the bank
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could just as well (and in this example does) use the published historical
default rates from S&P; in essence, the estimation step has been
outsourced to S&P. The 10 percent adjustment of PD is part of the
estimation process in this case because the adjustment was made prior to
the application of the agency default rates to the internal portfolio data.
Mapping – The bank’s mapping is an example of a grade mapping; internal
Grade 4 is linked to the 75/25 mix of BB and B. Based on the limited
information presented in the example, this step should be explored further.
Specifically, how did the bank determine the 75/25 mix?
Application – Although the application step is relatively straightforward in
this case, the bank does make the adjustment of the Grade 4 PD estimate
to give it the desired relationship to the adjacent grades. This adjustment
is part of the application stage because it is made after the adjusted
agency default rates are applied to the internal grades.
Example 2: PD estimation using a Merton-type equity-based model
•
A bank obtains a 20-year database of North American firms with publicly
traded equity, some of which defaulted during the 20-year period.
•
The bank uses the Merton approach to modeling equity in these firms as a
contingent claim, constructing an estimate of each firm’s distance-todefault at the start of each year in the database. The bank then ranks the
firm-years within the database by distance-to-default, divides the ordered
observations into 20 equal groups or buckets, and computes a mean
historical one-year default frequency for each bucket. That default
frequency is taken as an estimate of the applicable PD for any obligor
within the range of distance-to-default values represented by each of the
20 buckets.
•
The bank next looks at all obligors with publicly traded shares within each
of its internal grades, applies the same Merton-type model to compute
distance-to-default at quarter-end, sorts these observations into the 20
buckets from the previous step, and assigns the corresponding PD
estimate.
•
For each internal grade, the bank computes the mean of the individual
obligor default probabilities and uses that average as the grade PD.
Process Analysis for Example 2:
Data – The reference data set consists of the North American firms with
publicly traded equity in the acquired database. The reference data are
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described in this case by a single variable, specifically an identifier of the
specific distance-to-default range from the Merton model (one of the 20
possible in this case) into which a firm falls in any year.
Estimation – The estimation step is simple: the average default rate is
calculated for each distance-to-default bucket. Since the data cover 20
years and a wide range of economic conditions, the resulting estimates
satisfy the long-run average requirement.
Mapping – The bank maps selected portfolio obligors to the reference data
set using the distance-to-default generated by the Merton model.
However, not all obligors can be mapped, since not all have traded equity.
This introduces an element of uncertainty into the mapping that requires
additional analysis by the bank: were the mapped obligors representative
of other obligors in the same grade? The bank would need to demonstrate
comparability between the publicly traded portfolio obligors and those not
publicly traded. It may be appropriate for the bank to make conservative
adjustments to its ultimate PD estimates to compensate for the uncertainty
in the mapping. The bank also would need further analysis to demonstrate
that the implied distance-to-default for each internal grade represented
long-run expectations for obligors assigned to that grade; this could
involve computing the Merton model for portfolio obligors over several
years of relevant history that span a wide range of credit conditions.
Application – The final step is aggregation of individual obligors to the
grade level through calculation of the mean for each grade, and
application of this grade PD to all obligors in the grade. The bank might
also choose to modify PD assignments further at this stage, combining PD
estimates derived from other sources, applying adjustments for cyclicality,
introducing an appropriate degree of conservatism, or making other
adjustments.
Example 3: LGD estimation from internal default data
•
•
•
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For each loan in its portfolio, a bank records collateral coverage as a
percentage, as well as which of four types of collateral applies.
A bank has retained data on all defaulted loans since 1995. For each
defaulted loan in the database, the bank has a record of the collateral type
within the same four broad categories. However, collateral coverage is
only recorded at three levels (low, moderate, or high, depending on the
ratio of collateral to exposure at default).
The bank also records the timing and discounted value of recoveries net of
workout costs for each defaulted loan in the database. Cash flows are
tracked from the date of default to a “resolution date,” defined as the point
at which the remaining balance is less than 5 percent of the exposure at
the time of default. A recovery percentage is computed, equal to the value
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•
•
of recoveries discounted to the date of default, divided by the exposure at
default.
For each cell (each of the 12 combinations of collateral type and
coverage), the bank computes a simple mean LGD percentage as the
mean of one minus the recovery percentage. One of the categories has a
mean LGD of less than zero (recoveries have exceeded exposure on
average), so the bank sets the LGD at zero to be conservative.
The bank assigns an estimate of expected LGD to each loan in the current
portfolio by using collateral information to slot it into one of the 12 cells.
The bank then applies the mean historical LGD for that cell and adjusts the
result upward by 10 percent to compensate for the fact that the loss data
come from a period believed to be unusually good economic performance.
Process Analysis for Example 3:
Data – The reference data is the collection of historical defaults with the
loss amounts from the bank’s historical portfolio. The reference data are
described by the two categorical variables (levels of collateral coverage
and types of collateral). It would be important to determine whether the
defaults over the past few years are comparable to defaults from the
current portfolio. One would also want to ask why the bank ignores
potentially valuable information by converting the continuous data on
collateral coverage into a trimodal categorical variable.
Estimation – Conceptually, the bank is using a “loss severity model” in
which 12 binary variables, one for each loan coverage/type combination,
explain the percentage loss. The coefficients on the variables are just the
mean loss figures from the reference data.
Mapping – Mapping in this case is fairly straightforward, since all of the
relevant characteristics of the reference data are also in the loan system
for the current portfolio. However, the bank should determine whether the
variables are being recorded in the same way (for example, the same
definitions of collateral types), otherwise some adjustment might be
needed.
Application – The bank is able to apply the loss model by simply plugging
in the relevant values for the current portfolio (or what amounts to the
same thing, looking up the cell mean). The bank’s assignment of zero
LGD for one of the cells merits special attention; while the bank
represented this assignment as conservative, the adjustment does not
satisfy the supervisory requirement that LGD must exceed zero. A larger
upward adjustment is necessary. Finally, the upward adjustment of the
LGD numbers to account for the benign environment in which the
reference data were generated presents one additional wrinkle. The bank
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must provide a well-documented, empirically based analysis of why a 10
percent upward adjustment is sufficient.
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Chapter 3: Data Maintenance
I. Overview
184. Institutions using the IRB approach for regulatory capital purposes will
need advanced data management practices to produce credible and reliable risk
estimates. The guiding principle governing an IRB data maintenance system is
that it must support the requirements for the quantification, validation, control and
oversight mechanisms described in this guidance, as well as the institution’s
broader risk management and reporting needs. The precise data elements to be
collected will be dictated by the features and methodology of the IRB system
employed by the institution. The necessary data elements will therefore vary by
institution and even among business lines within an institution.
185. Institutions will have latitude in managing their data, subject to the
following key data maintenance standards:
Life Cycle Tracking – institutions must collect, maintain, and analyze
essential data for obligors and facilities throughout the life and disposition
of the credit exposure.
Rating Assignment Data – institutions must capture all significant
quantitative and qualitative factors used to assign the obligor and loss
severity ratings.
Support of IRB System – data collected by institutions must be of sufficient
depth, scope, and reliability to:
•
•
•
•
•
•
•
•
Validate IRB system processes,
Validate parameters,
Refine the IRB system,
Develop internal parameter estimates,
Apply improvements historically,
Calculate capital ratios,
Produce internal and public reports, and
Support risk management.
186. This chapter covers the requirements for maintaining internal data.
Reference data sets used for estimating IRB parameters are discussed in
Chapter 2.
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II. Data Maintenance Framework
Life Cycle Tracking
187. S. Institutions must collect, maintain, and analyze essential data for
obligors and facilities throughout the life and disposition of the credit exposure.
Using a life cycle or “cradle to grave” concept for each obligor and facility
supports front-end validation, back-testing, system refinements and risk
parameter estimates. A depiction of life-cycle tracking follows:
Origination
Restructuring
Ratings System Review
Default
Workout
Recoveries
1 Year
Ratings
Refreshment
Event
Ratings
Refreshment
2nd Year
Ratings
Refreshment
Final
Disposition
Loan
Sale
Repayment
Renewal
188. Data elements must be recorded at origination and whenever the rating is
reviewed, regardless of whether the rating is actually changed. Data elements
associated with current and past ratings must be retained and include the
following:
•
•
•
•
•
•
Key borrower and facility characteristics,
Ratings for obligor and loss severity grades,
Key factors used to assign the ratings,
Person or model responsible for assigning the rating,
Date rating assigned, and
Overrides to the rating and authorizing individual.
At disposition, data elements must include:
•
•
•
•
•
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Nature of disposition: renewal, repayment, loan sale, default,
restructuring,
For defaults: exposure, actual recoveries, source of recoveries, costs
of workouts and timing,
Guarantor support,
Sale price for loans sold, and
Other key elements that the bank deems necessary.
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Rating Assignment Data
189. S. Institutions must capture all significant quantitative and qualitative
factors used to assign the obligor and loss severity rating. Assigning a rating to
an obligor requires the systematic collection of various borrower characteristics
as these factors are critical to validating the rating system. Obligors are rated
using various methods, as discussed in Chapter 1. Each of these methods
presents different challenges for input collection. For example, in judgmental
rating systems, the factors used in the ratings decision have not traditionally been
explicitly recorded. For purposes of an IRB approach, institutions that use expert
and constrained judgment must record these factors and deliver them to the data
warehouse.
190. For loss severity estimates, institutions must record the basic structural
characteristics of facilities and the factors used in developing the facility rating or
LGD estimate. These often include the seniority of the credit, the amount and
type of collateral, the most recent collateral valuation date and its fair value.
191. Institutions must also track any overrides of the obligor or loss severity
rating. Tracking overrides separately allows risk managers to identify whether
the outcome of such overrides suggests either problems with rating criteria, or an
improper level of discretion in adjusting the ratings.
Example Data Elements
192. For illustrative purposes, the following section provides examples of the
kinds of data elements institutions will collect under an IRB data maintenance
framework.
General descriptive obligor and facility data
193. The data below could be contained within a loan record or derived from
various sources within the data warehouse. Guarantor data requirements are the
same as for the obligor.
Obligor / guarantor data
•
•
•
•
General data: name, address, industry
ID number (unique for all related parent / sub relationships)
Rating, date, and rater
PD percentage corresponding to rating
General facility characteristics
• Facility amounts: committed, outstanding
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•
•
•
•
•
•
•
•
•
•
Facility type: Term, revolver, bullet, amortizing, etc.
Purpose: acquisition, expansion, liquidity, inventory, working capital
Covenants
Facility ID number
Origination and maturity dates
Last renewal date
Obligor ID link
Rating, date and rater
LGD dollar amount or percentage
EAD dollar amount or percentage
Rating assignment data
194. The data below provide an example of the categories and types of data
that institutions must retain in order to continually validate and improve rating
systems. These data items should tie directly to the documented criteria that the
institution employs in assigning ratings, both qualitative and quantitative. For
example, rating criteria often include ranges of leverage or cash flow for a
particular obligor rating. In addition, qualitative factors, such as management
effectiveness can be recorded in numeric form. For example, a 1 may equate to
exceptionally strong management, and a 5 to very weak. The rating data
elements collected should be complete enough so that others can review the
relevant factors driving the rating decisions.
Quantitative factors in obligor ratings
• Asset and sale size
• Key ratios used within rating criteria:
¾ profitability,
¾ cash flow,
¾ leverage,
¾ liquidity, and
¾ other relevant factors.
Qualitative factors in obligor ratings
• Quality of earnings and cash flow
• Management effectiveness, reliability
• Strategic direction, industry outlook, position
• Country factors and political risk
• Other relevant factors
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External factors in obligor ratings
• Public debt rating and trend
• External credit model score and trend
Rating Notations
•
•
Flag for overrides or exceptions
Authorized individual for changing rating
Key facility factors in LGD ratings
• Seniority
• Collateral type: (cash, marketable securities, AR, stock, RE, etc.)
• Collateral value and valuation date
• Advance rates, LTV
• Industry
• Geography
Rating Notations
• Flag for overrides or exceptions
• Authorized individual for changing rating
Final disposition data
195. Only recently have institutions begun to collect more complete data about
a loan’s disposition. Many institutions maintain subsidiary systems for their
problem credits with details recorded, at times manually, on systems that were
not linked with the institution’s central loan or risk management systems. The
unlinked data are a significant hindrance in developing reliable PD, LGD, and
EAD estimates.
196. In advanced systems, the “grave” portion of obligor and exposure tracking
is an essential component for producing and validating risk estimates and is an
important feedback mechanism for adjusting and improving risk estimates over
time. Essential data elements are outlined below.
Obligor/guarantor
• Default date
• Circumstances of default (for example, nonaccrual, bankruptcy chapters 711, nonpayment)
Facility
• Outstandings at default
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•
Amounts undrawn and outstanding plus time series prior to and through
default
Disposition
• Amounts recovered and dates (including source: cash, collateral,
guarantor, etc.)
• Collection cost and dates
• Discount factors to determine economic cost of collection
• Final disposition (for example, restructuring or sale)
• Sales price, if applicable
• Accounting items (charge-offs to date, purchased discounts)
III. Data Element Functions
S. Data elements must be of sufficient depth, scope, and reliability to:
•
•
•
•
•
•
•
•
Validate IRB system processes,
Validate parameters,
Refine the IRB system,
Develop internal parameter estimates,
Apply improvements historically,
Calculate capital ratios,
Produce internal and public reports, and
Support risk management.
Validation and Refinement
197. The data elements collected by institutions must be capable of meeting the
validation requirements described in Chapters 1 and 2. These requirements
include validating the institution’s IRB system processes, including the “front end”
aspects such as assigning ratings so that any issues can be identified early. The
data must support efforts to identify whether raters and models are following
rating criteria and policies and whether ratings are consistent across portfolios.
In addition, data must support the validation of parameters, particularly the
comparison of realized outcomes with estimates. Thorough data on default and
disposition characteristics are of paramount importance for parameter backtesting.
198. A rich source of data for validation efforts provides insights on the
performance of the IRB system, and contributes to a learning environment in
which refinements can be made to the system. These potential refinements
include enhancements to rating assignment controls, processes, criteria or model
coefficients, rating system architecture and parameter estimates.
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Developing Parameter Estimates
199. As detailed in Chapter 2, institutions will be developing their PD, LGD, and
EAD parameter estimates using reference data sets comprised of internal,
pooled, and external data. Institutions are expected to work toward eventually
using as much of their own experience as possible in their reference data sets.
Applying Rating System Improvements Historically
200. For loss severity estimates, institutions must record the basic structural
characteristics of facilities and the factors used in developing the facility rating or
LGD estimate. These often include the seniority of the credit, the amount and
type of collateral, the most recent collateral valuation date and its fair value.
201. To maintain a consistent series of information for credit risk monitoring and
validation purposes, institutions need to be able to apply historically
improvements they make to their rating systems. In the example below, a bank
experiences unexpected and rapid migrations and defaults in its grade 4 category
during 2006. Analysis of the actual financial condition of borrowers that defaulted
compared with those that did not suggests the debt-to-EBITDA range for its
expert judgment criteria of 3.0 to 5.5 is too broad. Research indicates that grade
4 should be redefined to include only borrowers with debt-to-EBITDA ratios of
3.0–4.5 and grade 5 as 4.5–6.5. In 2007, the change is initiated, but prior years’
numbers are not recast (see Exhibit A). Consequently, a break in the series
prevents the bank from evaluating credit quality changes over several years and
from identifying whether applying the new rating criteria historically provides
reasonable results.
Exhibit A (Revision of Grades 4 and 5 in 2007)
1
2
3
4
5
6
7
D
Total
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Distribution of Obligor Risk Grades (%)
2004
2005
2006
2007
1
1.1
1.2
1.2
10
11
12
13
22
23
24
26
2008
1.3
13
25
Change
04-'08
0.3
3.0
3.0
30
20
30
21
32
19
16
33
17
34
(13.0)
8
4
5
100
7
4
2.9
100
7
3
1.8
100
7
2
1.8
100
6
1
2.7
100
(2.0)
(3.0)
(2.3)
0
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14.0
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202. Recognizing the need to provide senior managers and board members
with a consistent risk trend, the new criteria are applied historically to obligors in
grades 4 and 5 as reflected in Exhibit B. The original ratings assigned to the
grades are maintained along with notations describing what the grade would be
under the new rating criteria. If the precise weight an expert has given one of the
redefined criteria is unknown, institutions are expected to make estimates on a
best efforts basis. After the retroactive reallocation process, the bank observes
that the mix of obligors in grade 5 declined somewhat over the past several years
while the mix in grade 4 increased slightly. This contrasts with the trend identified
before the retroactive reallocation. The result is that the multiyear transition
statistics for grades 4 and 5 provide risk managers a clearer picture of risk.
1
2
3
4
5
6
7
D
Total
Exhibit B (After Recasting 2004-06)
Distribution of Obligor Risk Grades (%)
2004
2005
2006
2007
1
1.1
1.2
1.2
10
11
12
13
22
23
24
26
2008
1.3
13
25
Change
04-'08
0.3
3.0
3.0
16
35
15
36
16
35
16
33
17
34
(1.0)
8
4
4
100
7
4
2.9
100
7
3
1.8
100
7
2
1.8
100
6
1
2.7
100
(2.0)
(3.0)
(1.3)
0
1.0
203. This example is based on applying ratings historically using data already
collected by the bank. However, for some rating system refinements, institutions
may identify in the future drivers of default or loss that might not have been
collected for borrowers or facilities in the past. That is why institutions are
encouraged to collect data that they believe may serve as a stronger predictor of
default in the future. For example, certain elements of a borrower’s cash flow
might currently be suspected to overstate actual operational health for a
particular industry. In the future, should an institution decide to deduct this item
from cash flow with a resulting downgrade of many obligor ratings, the institution
that collected these data could apply this rating change for prior years. This
would provide the benefit of providing a consistent picture of risk over time and
also present opportunities to validate the new criteria using historical data.
Recognizing that institutions will not be able to anticipate fully the data they might
find useful in the future, institutions are expected to reallocate grades on a best
efforts basis when practical.
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Calculating Capital Ratios and Reporting to the Public
204. Data retained by the bank will be essential for regulatory risk-based capital
calculations and public reporting under the Pillar 3 disclosures. These uses
underscore the need for a well-defined data maintenance framework and strong
controls over data integrity. Control processes and data elements themselves
should also be subject to periodic verification and testing by internal and external
auditors. Supervisors will rely on these processes and also perform testing as
circumstances warrant.
Supporting Risk Management
205. The information that can be gleaned from more extensive data collection
will support a broad range of risk management activities. Risk management
functions will rely on accurate and timely data to track credit quality, make
informed portfolio risk mitigation decisions, and perform portfolio stress tests.
Trends developed from obligor and facility risk rating data will be used to support
internal capital allocation models, pricing models, ALLL calculations, and
performance management measures, among others. Summaries of these are
included in reports to institutions’ boards of directors, regulators, and in public
disclosures.
IV. Managing data quality and integrity
206. Because data are collected at so many different stages involving a variety
of groups and individuals, there are numerous challenges to ensuring the quality
of the data. For example:
•
•
•
Data will be retained over long timeframes,
Qualitative risk-rating variables will have subjective elements and will be
open to interpretation, and
Exposures will be acquired through mergers and purchases, but without
an adequate and easily retrievable institutional rating history.
Documentation and Definitions
207. Given the many challenges presented by data for an IRB system, the
management of data must be formalized. S. Institutions must document the
process for delivering, retaining and updating inputs to the data warehouse and
ensuring data integrity. Fully documenting how the institution’s flow of data is
managed provides a means for evaluating whether the data maintenance
framework is functioning as intended. Moreover, institutions must be able to
communicate to individuals developing or delivering various data the precise
definition of the items intended to be collected. Consequently, a “data dictionary”
is necessary to ensure consistent inputs from individuals and data vendors and to
allow third parties (such as the rating system review function, auditors, or bank
supervisors) to evaluate data quality and integrity. S. Institutions must develop
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comprehensive definitions for the data elements used within each credit group or
business line (a “data dictionary”).
Electronic Storage
208. To meet the significant data management challenges presented by the
validation and control features of an IRB system, institutions will need to store
their data electronically. S. Institutions must store data in electronic format to
allow timely retrieval for analysis, validation of risk rating systems, and required
disclosures. Institutions will have a variety of storage techniques and potentially
a variety of systems to create their data warehouses. IRB data requirements can
be achieved by melding together existing accounting, servicing, processing,
workout and risk management systems, provided the linkages among these
systems are well documented and include sufficient edit and integrity checks to
ensure the data can be used reliably.
209. Institutions without electronic databases would need to resort to manual
reviews of paper files for ongoing back-testing and ad hoc “forensic” data mining
and would be unable to perform that work in the timely and comprehensive
manner required of IRB systems. Forensic mining of paper files to build an initial
data warehouse from the institution’s credit history is encouraged. In some
instances, paper research may be necessary to identify data elements or factors
not originally considered significant in estimating the risk of a particular class of
obligor or facility.
Data Gaps
210. Rating histories are often lost or are irretrievable for loans acquired
through mergers, acquisitions, or portfolio purchases. Institutions are
encouraged wherever practical to collect any missing historical rating assignment
driver data and to re-grade the acquired obligors and facilities for prior periods.
In cases where retrieving historical data is not practical, institutions may attempt
to create a rating history through a careful mapping of the legacy system and the
new rating structure. Mapped ratings should be reviewed thoroughly for
accuracy. The level of effort placed on filling data gaps should be commensurate
with the size of the new exposures to be newly incorporated into the institution’s
IRB system.
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Chapter 4: Control and Oversight Mechanisms
I. Overview
211. Banks’ internal rating systems are the foundation for credit-risk
management practices and play an important role in pricing, reserving, portfolio
management, performance measurement, economic capital modeling, and longterm capital planning. Banks adopting the IRB approach will also use their creditrisk ratings to determine regulatory capital levels. The pivotal and varied uses of
such risk ratings put enormous, sometimes conflicting, pressure on banks’
internal rating systems. The consequences of inaccurate ratings and their
associated estimates are significant, particularly as they affect minimum
regulatory capital requirements.
212. As risk ratings and their related parameters become better integrated in
institutions’ decision making, conflicting incentives arise that, if not well managed,
can lead to overly optimistic or biased ratings. For example, sales and marketing
staff (relationship managers or RMs) are typically compensated according to the
volume of business they generate. That may predispose the RMs to assign more
favorable ratings in order to achieve rate-of-return and sales objectives. More
favorable ratings may create the appearance of higher risk-adjusted returns and
business line profitability. Banks need to be aware of the full range of incentive
conflicts that arise, and must develop effective controls to keep these incentive
conflicts in check.
213. Banks will have latitude in designing and implementing their control
structures subject to the following principle:
IRB institutions must implement a system of controls that includes
the following elements: independence, transparency, accountability,
use of ratings, rating system review, internal audit, and board and
senior management oversight. While banks will have flexibility in
how these elements are combined, they must incorporate sufficient
checks and balances to ensure that the credit risk management
system is functioning properly.
214. Banks additionally will want to embody the following more generic
principles in their control system: separation of duties, balancing incentives, and
layers of review. Table 4.1 lists the key components of an IRB control and
oversight system. How these control mechanisms can best be combined to
reinforce one another is a key challenge for banks implementing IRB systems:
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Table 4.1 Control and Oversight Mechanisms
Independence
The parties responsible for approving ratings and transactions
should be separate from the sales and marketing staff and be
principally compensated on risk-rating accuracy.
Transparency
The rating system and ratings should be sufficiently transparent
to enable third parties, such as rating system reviewers, auditors
and supervisors, the ability to understand the operations of the
rating system and the rating rationale.
Accountability
Accountability is holding people responsible for their actions and
establishing adverse consequences for inaccurate ratings.
Use of Ratings
Ratings should be used to guide day-to-day risk management
activities.
Rating System Review
Ratings and rating system performance should be evaluated by
an area independent of those responsible for assigning and
approving ratings.
Internal Audit
Responsibility for ensuring the adequacy of control and oversight
mechanisms and overall compliance with the IRB standards
should rest with the internal audit function.
Board and Senior
Management Oversight
Ultimate responsibility for the performance of the rating system
rests with senior management and the board.
215. As the following examples indicate, how a bank conducts its business will
influence how it designs its control structure. A bank using an expert-judgment
system will likely establish a different set of controls than a bank using mainly
models. Recognizing that its expert-judgment system is less than fully
transparent, a bank could offset this vulnerability by opting for complete
independence in the rating approval process and an enhanced rating system
review.
216. Other considerations would influence the choice of controls when banks
use models to assign ratings. While the ratings produced by models are
transparent, a model’s performance depends on how well the model was
developed, the model’s logic, and the quality of the data used to implement the
model. Banks that use models to assign ratings must implement a system of
controls that addresses model development, testing and implementation, data
integrity and overrides. These activities would be covered by a comprehensive
and independent rating system review and by ongoing spot checks on the
accuracy of model inputs. Other control mechanisms such as accountability and
audit would also be required.
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II. Independence in the Rating Approval Process
An independent rating process is one in which the parties
responsible for approving ratings and transactions are separate
from sales and marketing and in which the persons approving
ratings are principally compensated on risk-rating accuracy. As
relative independence increases, the likelihood of accurate ratings
assignments grows markedly.
217.
S. Ratings must be subject to independent approval or review.
One way institutions can better achieve objective and accurate risk ratings is by
ensuring that its rating approval process is independent. Institutions that firmly
separate sales/marketing from credit are better able to manage the conflict
between the goal of high sales volume and the need for good credit quality. An
institution whose rating process is less independent must compensate by
strengthening other control and oversight mechanisms. A significant factor in the
evaluation of the rating system will be the assessment of whether such
compensating controls are sufficient to offset a less-than-independent ratings
process. While the overriding objective is to achieve independence in the rating
approval process, in some instances, the relative materiality of a portfolio and
cost/benefit trade-offs may support a less rigorous control process.
218. The degree of independence achieved in the rating process depends on
how an institution is organized and how it conducts its lending activities.
A. Rating Approval Processes
219. Responsibility for recommending and approving ratings varies by
institution and, quite often, by portfolio6. At some institutions, ratings are
assigned and approved by relationship managers (RMs); at others, deal teams
assign ratings that are later approved by credit officers. Still other institutions
have independent credit officers assign and approve ratings. The culture of an
institution and its business mix generally determine whether the business line or
credit function is ultimately responsible for ratings.
6
Rating processes vary by institution but generally involve an "assignor" and an "approver." For
instance, at many organizations the rating assignor is the person who "owns" the relationship
(such as a "relationship manager") and the rating approver is an individual with credit authority (a
"credit risk manager"). In some cases, the rating assignor and approver are the same. Banks
that separate the rating assignment and approval processes do so in order to minimize potential
conflicts of interest and the potential for rating errors.
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220. The subsections that follow describe various rating assignment and
approval structures used by banking organizations and the challenges that
emerge in ensuring objective and consistent ratings. Any of the following
structures can work as long as ratings are subject to an independent approval or
review process, and are not unduly influenced by the line of business:
Relationship Managers. As noted earlier, relationship managers are
primarily responsible for marketing the bank’s products and services, and
their compensation is tied to the volume of business they generate. When
RMs also have responsibility for assigning and approving ratings, there is
an inherent conflict of interest. Credit quality and the ability to produce
timely and accurate risk ratings are generally not major factors in an RM’s
compensation, even when he or she has responsibility for assigning and
approving ratings. In addition, RMs also may become too close to the
borrower to maintain their objectivity and remain unbiased. When banks
delegate rating responsibility to RMs, they must offset the lack of
independence with rigorous controls to prevent bias from affecting the
rating process. Such controls must operate in practice, not just on paper,
and would include, at a minimum, a comprehensive, independent postclosing review of ratings by a rating system review function.
Deal Team. Some major banks employ a “deal-team” structure for credit
origination and rating assignment. Using this approach, all members of
the team — credit officers, investment bankers, underwriters, and others —
contribute to analyzing creditworthiness, underwriting the deal, and
assigning ratings.
On the one hand, deal teams increase the access of credit officers to
information on obligors and transactions early in the underwriting process,
enabling them to make more informed credit decisions and to influence
facility structure to address obligors’ weaknesses. On the other hand,
participation in the deal team could compromise the credit officer’s
objectivity. While credit officers typically report to an independent creditrisk-management function, they also have allegiance to the deal team that
reports to executives within the sales and marketing line of business. In
addition, credit officers may defer to the members of the team whose
compensation is based on the revenue and sales volume they generate for
the bank. Banks that maintain deal teams must ensure that the credit
officer’s independence is safeguarded through independent reporting lines
and well-defined performance measures (e.g., adherence to policy, rating
accuracy and timeliness).
Credit Officers. Some banks give sole responsibility for assigning and
approving ratings to credit officers who report to an independent credit
function. In addition to assigning and approving and assigning initial
ratings, credit officers regularly monitor the condition of obligors and
refresh ratings as necessary. The potential downside of this structure is
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that these credit officers may have limited access to borrower information.
Those credit officers that have a separate reporting line and whose
compensation is principally based on their risk-rating accuracy are
typically more independent than RMs or deal teams.
Models. At some institutions, models assign ratings directly; at other
institutions, models and judgment are combined to rate credits. Models
introduce a high degree of independence to the rating process, but they
too require human oversight and controls. Banks that use models must
incorporate an independent judgmental review of the rating assignments
to ensure that all relevant information is considered and to identify
potential rating errors. Judgmental reviews are also needed when model
outputs are overridden. In addition, controls are needed to ensure
accuracy of data inputs. When a bank uses a model to assign risk ratings,
an individual obligor’s rating is “transparent.” However, the model itself is
not “transparent” without a great deal of effort to document how the model
functions.
III. Transparency
Transparency is the ability of a third party, such as rating system
reviewers, auditors or bank supervisors, to observe how the
rating system operates and to understand the pertinent
characteristics of individual ratings
221.
S. IRB institutions must have a transparent rating system.
Transparency in a rating system is achieved through documentation that covers
the following:
•
•
•
•
•
•
The rating system’s design, purpose, performance horizon, and
performance standards;
The rating assignment process, including procedures for adjustments
and overrides;
Rating definitions and criteria, scorecard criteria, and model
specifications;
Parameter estimates and the process for their estimation;
Definition of the data elements to be warehoused to support controls,
oversight, validation, and parameter estimation; and
Specific responsibilities of, and performance standards for, individuals
and units involved in the rating system and its oversight.
Transparency allows third parties (such as rating system review, auditors, or
supervisors) to evaluate whether the rating system is performing as intended.
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Without transparency, it is difficult to hold people accountable for ratings errors
and to validate the performance of the system.
222.
S. Rating criteria must be clear and specific and must include qualitative and
quantitative factors.
To produce transparent individual ratings, a bank’s policies must contain clear,
detailed ratings definitions. Banks should specify criteria for each factor that
raters must consider, which may require unique rating definitions for certain
industries. Banks should consider criteria for factors such as liquidity, sales and
profitability, debt service and fixed charge coverage, minimum equity support,
position within the industry, strength of management. A rating system with vague
criteria or one merely defined by PDs or LGDs is not transparent. For example,
the following rating definitions are not transparent because they require the rater
to do too much interpreting:
Borrower exhibits satisfactory quality and demonstrates
acceptable principal and interest repayment capacity in the near
term.
Lower tier company in a cyclical industry. Unbalanced position
with tight liquidity and high leverage. Declining or erratic
profitability and marginal debt service capacity. Management is
untested.
IV. Accountability
“Accountability” is holding people responsible for their actions and
establishing adverse consequences for inaccurate ratings.
223.
S. Polices must identify the parties responsible for rating accuracy and rating
system performance.
For accountability to be effective, it should be both observable and ingrained in
the culture. Persons who assign and approve rate credits, derive parameter
estimates, or oversee rating systems must be held accountable for complying
with rating system policies and ensuring that aspects of the rating system within
their control are as unbiased and accurate as possible. These persons must
have the tools and resources necessary to carry out their responsibilities, and
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their performance should be evaluated against clear and specific objectives
documented in policy.
A. Responsibility for Assigning Ratings
224.
S.
Individuals must be held accountable for complying with rating system
policies and for assigning accurate ratings, and their performance and
compensation must be linked to well-defined measurable performance
standards.
Responsibilities of raters should be clear, and performance should be measured
against specific objectives. Performance evaluation and incentive compensation
should be tied to performance goals. Examples of performance measures
include:
•
•
•
Number and frequency of rating errors,
Significance of errors (for example, multiple downgrades), and
Proper and consistent application of criteria, including override criteria.
B. Responsibility for Rating System Performance
225. Just as individuals will be held accountable for the accuracy of ratings, an
individual must be held responsible for the overall performance of the rating
system. This individual must ensure that the rating system and all of its
component parts — rating assignments, parameter estimation, data collection,
control and oversight mechanisms — are functioning as intended. While these
components often are housed within separate units of the organization, an
individual must be responsible for ensuring that the parts work together
effectively and efficiently.
V. Use of Ratings
226.
S. Ratings used for regulatory capital must be the same ratings used to guide
day-to-day credit risk management activities.
The different uses and applications of the risk-rating system’s outputs should
promote greater accuracy and consistency of credit-risk evaluations across an
organization. Ratings and the associated default, loss, and EAD estimates need
to be incorporated within the credit-risk management, internal capital allocation,
and corporate governance functions of IRB banks.
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227.
S.
Banks that use parameter estimates for risk management that are different
from those used for regulatory capital must provide a well-documented
rationale for the differences.
PD and LGD parameters used for regulatory capital purposes may not be
appropriate for other uses purposes. For example, PD estimates used to
estimate reserve needs could reflect current economic conditions that are
different from the longer term view appropriate to calculations of regulatory
capital. When banks employ different estimates, those parameters must be
defensible and supported by the following:
•
•
Qualitative and quantitative analysis of the logic and rationale for the
difference(s); and
Senior management approval of the difference(s).
VI. Rating System Review (RSR)
228.
S.
Banks must have a comprehensive, coordinated, independent review
process to ensure that ratings are accurate and that the rating system is
performing as intended.
Rating system review (RSR) ensures that the rating system as a whole is
functioning as intended. A broad range of responsibilities come under RSR’s
purview, as outlined in Table 4.2:
Table 4.2 Responsibilities of Rating System Review
SCOPE OF REVIEW:
Design of the rating system.
Compliance with policies and procedures, including application of criteria.
Check of all risk-rating grades for accuracy.
Consistency across industries/portfolios/geographies.
Model development.
Model use, including inputs and outputs.
Overrides and policy exceptions.
Quantification process.
Back-testing (perform or review).
Actual and predicted ratings transitions.
Benchmarking against third-party data sources (perform or review).
Adequacy of data maintenance.
ANALYSIS AND REPORTING:
Identify errors and flaws.
Recommend corrective action.
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229. For each of these responsibilities, RSR is largely checking and confirming
the work of others and ensuring that the rating system’s components work well
together. RSR’s testing and review should identify current and potential
weaknesses and should lead to recommendations and corrective action such as
•
•
•
•
•
Adjusting policies and procedures,
Requiring additional training of staff,
Investing in infrastructure improvements,
Adjusting rating criteria, and
Adjusting parameter estimates.
230.
S. Rating system review must report significant findings to senior management
and the board quarterly.
RSR’s role is to identify issues and areas of concern and report findings to the
area that is accountable. When issues are systematic, RSR should bring them to
the attention of senior management and the board.
231. The activities of this function could be distributed across multiple areas or
housed within one unit. Organizations will choose a structure that fits within their
management and oversight framework. These units must always have high
standing within the organization and should be staffed by individuals possessing
the requisite stature, skills, and experience.
232. Like internal audit, RSR must be independent from all in-house designers
and developers (that is, system and model designers) and raters (that is, ratings
and parameter assigners) in the risk-rating process. RSR’s independence
eliminates potential conflicts of interest and gives the group credibility when it
reports findings and conclusions to the board and senior management.
VII. Internal Audit
233.
S. An independent internal audit function must determine whether rating system
controls function as intended.
S. Internal audit must evaluate annually whether the bank is in compliance with
the risk-based capital regulation and supervisory guidance.
Internal audit determines whether the bank’s system of controls over internal
ratings and the related parameters is robust. In its evaluation of controls, internal
audit must consider any trade-offs made between the various mechanisms and
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confirm their continued appropriateness and relevance. As part of its review of
control mechanisms, audit will evaluate the depth, scope, and quality of RSR’s
work and will conduct limited testing to ensure that their conclusions are well
founded. The amount of testing will depend on whether audit is the primary or
secondary reviewer of that work.
234. Internal audit will report to the board and management on whether the
bank is in compliance with the IRB standards. This report will allow the board
and management to disclose that its rating processes and the controls
surrounding these processes are in compliance with the IRB standards. This will
be critical for public disclosure and ongoing work of supervisors.
External Audit
235. As part of the process of certifying financial statements, external auditors
will confirm that the institution’s capital position is fairly presented. To verify that
actual capital exceeds regulatory minimums and to confirm compliance with the
IRB rules, the external auditors must ascertain that the IRB system is rating credit
risk appropriately and linking these ratings to appropriate estimates. Auditors
must evaluate the bank’s internal control functions and its compliance with the
risk-based capital regulation and supervisory guidance.
VIII. Corporate Oversight
236.
S. The full board or a committee of the board must approve key elements of the
IRB system.
Consistent with sound practice, bank management must ensure that a corporate
culture exists in which institutional needs are readily identified and appropriate
resources are brought to bear to rectify shortcomings. In the IRB context, senior
management and the board of directors must ensure the objectivity and accuracy
of the bank’s credit-risk management systems and approach.
237. Either the full board or a committee of the board should approve key
elements of the risk-rating system. Information provided to the board should be
sufficiently detailed to allow directors to confirm the continuing appropriateness of
the institution’s rating approach and to verify the adequacy of the controls
supporting the rating system.
238.
S. Senior management must ensure that all components of the IRB system,
including controls, are functioning as intended and comply with the risk-based
capital regulation and supervisory guidance.
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Senior management’s oversight should be even more active than that of the
board of directors. Senior management should articulate what it expects of the
technical and operational units of the risk-rating system, as well as what it
expects of the units that manage the system’s controls. To oversee the riskrating system, senior management must have an extensive understanding of
credit policies, underwriting standards, lending practices, and collection and
recovery practices, and must be able to understand how these factors affect
default and loss estimates. Senior management should not only oversee the
controls process (its traditional role) but also should periodically meet with raters
and validators to discuss the rating system’s performance, areas needing
improvement, and the status of efforts to improve previously identified
deficiencies.
239. The depth and frequency of information provided to the board and senior
management must be commensurate with their oversight responsibilities and the
condition of the institution. These reports should include the following
information:
•
•
•
•
•
•
•
Risk profile by grade,
Risk rating migration across grades with emphasis on unexpected
results,
Changes in parameter estimates by grade,
Comparison of realized PD, LGD, and EAD rates against expectations,
Reports measuring changes in regulatory and economic capital,
Results of capital stress testing, and
Reports generated by rating system review, audit, and other control
units.
Although all of an institution’s controls must function smoothly, independently,
and in concert with the others, the direction and oversight provided by the board
and senior management are perhaps most important to ensure that the IRB
system is functioning properly.
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ATTACHMENT 3
Supervisory Guidance on Operational Risk
Advanced Measurement Approaches for
Regulatory Capital
July 2, 2003
269
Table of Contents
I.
II.
III.
IV.
V.
VI.
VII.
VIII.
IX.
X.
XI.
Purpose
Background
Definitions
Banking Activities and Operational Risk
Corporate Governance
A.
Board and Management Oversight
B.
Independent Firm-wide Risk Management Function
C.
Line of Business Management
Operational Risk Management Elements
A.
Operational Risk Policies and Procedures
B.
Identification and Measurement of Operational Risk
C.
Monitoring and Reporting
D.
Internal Control Environment
Elements of an AMA Framework
A.
Internal Operational Risk Loss Event Data
B.
External Data
C.
Business Environment and Internal Control Factor Assessments
D.
Scenario Analysis
Risk Quantification
A.
Analytical Framework
B.
Accounting for Dependence
Risk Mitigation
Data Maintenance
Testing and Verification
Appendixes
A.
Supervisory Standards
270
I.
1.
Purpose
The purpose of this guidance is to set forth the expectations of the U.S. banking agencies
for banking institutions that use Advanced Measurement Approaches (AMA) for calculating the
operational risk capital charge under the new capital regulation. Institutions using the AMA will
have considerable flexibility to develop operational risk measurement systems appropriate to the
nature of their activities, business environment, and internal controls. An institution’s
operational risk regulatory capital requirement will be calculated as the amount needed to cover
its operational risk at a level of confidence determined by the supervisors, as discussed below.
Use of an AMA is subject to supervisory approval.
2.
This draft guidance should be considered with the advance notice of proposed rulemaking
(ANPR) on revisions to the risk-based capital standard as published in the Federal Register on
July______ no.____________. As with the ANPR, the Agencies are seeking industry comment
on this draft guidance. In addition to seeking comment on all specific aspects of this supervisory
guidance, the Agencies are seeking comment on the extent to which the supervisory guidance
strikes the appropriate balance between flexibility and specificity. Likewise, the Agencies are
seeking comment on whether an appropriate balance has been struck between the regulatory
requirements set forth in the ANPR and the supervisory standards set forth in this guidance.
II.
Background
3.
Effective management of operational risk is integral to the business of banking and to
institutions’ roles as financial intermediaries. Although operational risk is not a new risk,
deregulation and globalization of financial services, together with the growing sophistication of
financial technology, new business activities and delivery channels, are making institutions’
271
operational risk profiles (i.e., the level of operational risk across an institution’s activities and
risk categories) more complex.
4.
This guidance identifies the supervisory standards (S) that institutions must meet and
maintain to use an AMA for the regulatory capital charge for operational risk. The purpose of
the standards is to provide the foundation for a sound operational risk framework, while allowing
institutions to identify the most appropriate mechanisms to meet AMA requirements. Each
institution will need to consider its complexity, range of products and services, organizational
structure, and risk management culture as it develops its AMA. Operational risk governance
processes need to be established on a firm-wide basis to identify, measure, monitor, and control
operational risk in a manner comparable with the treatment of credit, interest rate, and market
risks.
5.
Institutions will be expected to develop a framework that measures and quantifies
operational risk for regulatory capital purposes. To do this, institutions will need a systematic
process for collecting operational risk loss data, assessing the risks within the institution, and
adopting an analytical framework that translates the data and risk assessments into an operational
risk exposure (see definition below). The analytical framework must incorporate a degree of
conservatism that is appropriate for the overall robustness of the quantification process. Because
institutions will be permitted to calculate their minimum regulatory capital on the basis of
internal processes, the requirements for data capture, risk assessment, and the analytical
framework described below are detailed and specific.
6.
Effective operational risk measurement systems are built on both quantitative and
qualitative risk assessment techniques. While the output of the regulatory framework for
operational risk is a measure of exposure resulting in a capital number, the integrity of that
272
estimate depends not only on the soundness of the measurement model, but also on the
robustness of the institution’s underlying risk management processes. In addition, supervisors
view the introduction of the AMA as an important tool to further promote improvements in
operational risk management and controls at large banking institutions.
7.
This document provides both AMA supervisory standards and a discussion of how those
standards should be incorporated into an operational risk framework. The relevant supervisory
standards are listed at the beginning of each section and a full compilation of the standards is
provided in Appendix A. Not every section has specific supervisory standards. When spanning
more than one section, supervisory standards are listed only once.
8.
Institutions will be required to meet, and remain in compliance with, all the supervisory
standards to use an AMA framework. However, evaluating an institution’s qualification with
each of the individual supervisory standards will not be sufficient to determine an institution’s
overall readiness for AMA. Instead, supervisors and institutions must also evaluate how well the
various components of an institution’s AMA framework complement and reinforce one another
to achieve the overall objectives of an accurate measure and effective management of operational
risk. In performing their evaluation, supervisors will exercise considerable supervisory
judgment, both in evaluating the individual components and the overall operational risk
framework.
9.
An institution’s AMA methodology will be assessed as part of the ongoing supervision
process. This will allow supervisors to incorporate existing supervisory efforts as much as
possible into the AMA assessments. Some elements of operational risk (e.g., internal controls
and information technology) have long been subject to examination by supervisors. Where this
is the case, supervisors will make every effort to leverage off these examination activities to
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assess the effectiveness of the AMA process. Substantive weaknesses identified in an
examination will be factored into the AMA qualification process.
III. Definitions
10.
There are important definitions that institutions must incorporate into an AMA
framework. They are:
•
•
•
Operational risk: The risk of loss resulting from inadequate or failed internal
processes, people and systems, or from external events. The definition includes legal
risk, which is the risk of loss resulting from failure to comply with laws as well as
prudent ethical standards and contractual obligations. It also includes the exposure to
litigation from all aspects of an institution’s activities. The definition does not
include strategic or reputational risks1.
Operational risk loss: The financial impact associated with an operational event that
is recorded in the institution’s financial statements consistent with Generally
Accepted Accounting Principles (GAAP). Financial impact includes all out-ofpocket expenses associated with an operational event but does not include
opportunity costs, foregone revenue, or costs related to investment programs
implemented to prevent subsequent operational risk losses. Operational risk losses
are characterized by seven event factors associated with:
i. Internal fraud: an act of a type intended to defraud, misappropriate property or
circumvent regulations, the law or company policy, excluding
diversity/discrimination events, which involve at least one internal party.
ii. External fraud: an act of a type intended to defraud, misappropriate property or
circumvent the law, by a third party.
iii. Employment practices and workplace safety: an act inconsistent with
employment, health or safety laws or agreements, from payment of personal
injury claims, or from diversity/discrimination events.
iv. Clients, products, and business practices: an unintentional or negligent failure
to meet a professional obligation to specific clients (including fiduciary and
suitability requirements), or from the nature or design of a product.
v. Damage to physical assets: the loss or damage to physical assets from natural
disaster or other events.
vi. Business disruption and system failures: disruption of business or system
failures.
vii. Execution, delivery, and process management: failed transaction processing or
process management, from relations with trade counterparties and vendors.
Operational risk exposure: An estimate of the potential operational losses that the
banking institution faces at a soundness standard consistent with a 99.9 per cent
confidence level over a one-year period. The institution will multiply the exposure by
1
An institution’s definition of operational risk may encompass other risk elements as long as the supervisory
definition is met.
274
•
12.5 to obtain risk-weighted assets for operational risk; this is added to the riskweighted assets for credit and market risk to arrive at the denominator of the
regulatory capital ratio.
Business environment and internal control factor assessments: The range of tools
that provide a meaningful assessment of the level and trends in operational risk across
the institution. While the institution may use multiple tools in an AMA framework,
they must all have the same objective of identifying key risks. There are a number of
existing tools, such as audit scores and performance indicators that may be acceptable
under this definition.
IV. Banking Activities and Operational Risk
11.
The above definition of operational risk gives a sense of the breadth of exposure to
operational risk that exists in banking today as well the many interdependencies among risk
factors that may result in an operational risk loss. Indeed, operational risk can occur in any
activity, function, or unit of the institution.
12.
The definition of operational risk incorporates the risks stemming from people, processes,
systems and external events. People risk refers to the risk of management failure, organizational
structure or other human resource failures. These risks may be exacerbated by poor training,
inadequate controls, poor staffing resources, or other factors. The risk from processes stem from
breakdowns in established processes, failure to follow processes, or inadequate process mapping
within business lines. System risk covers instances of both disruption and outright system
failures in both internal and outsourced operations. Finally, external events can include natural
disasters, terrorism, and vandalism.
13.
There are a number of areas where operational risks are emerging. These include:
•
•
•
Greater use of automated technology has the potential to transform risks from manual
processing errors to system failure risks, as greater reliance is placed on globally
integrated systems;
Proliferation of new and highly complex products;
Growth of e-banking transactions and related business applications expose an
institution to potential new risks (e.g., internal and external fraud and system security
issues);
275
•
•
•
•
14.
Large-scale acquisitions, mergers, and consolidations test the viability of new or
newly integrated systems;
Emergence of institutions acting as large-volume service providers create the need for
continual maintenance of high-grade internal controls and back-up systems;
Development and use of risk mitigation techniques (e.g., collateral, insurance, credit
derivatives, netting arrangements and asset securitizations) optimize an institution’s
exposure to market risk and credit risk, but potentially create other forms of risk (e.g.,
legal risk); and
Greater use of outsourcing arrangements and participation in clearing and settlement
systems mitigate some risks while increasing others.
The range of banking activities and areas affected by operational risk must be fully
identified and considered in the development of the institution’s risk management and
measurement plans. Since operational risk is not confined to particular business lines2, product
types, or organizational units, it should be managed in a consistent and comprehensive manner
across the institution. Consequently, risk management mechanisms must encompass the full
range of risks, as well as strategies that help to identify, measure, monitor and control those risks.
V.
Corporate Governance
Supervisory Standards:
S 1.
15.
The institution’s operational risk framework must include an independent firmwide operational risk management function, line of business management
oversight, and independent testing and verification functions.
The management structure underlying an AMA operational risk framework may vary
between institutions. However, within all AMA institutions, there are three key components that
must be evident -- the firm-wide operational risk management function, lines of business
management, and the testing and verification function. These three elements are functionally
2
Throughout this guidance, terms such as “business units” and “business lines” are used interchangeably and refer
not only to an institution’s revenue generating businesses, but also to corporate staff functions such as human
resources or information technology.
276
independent3 organizational components, but should work in cooperation to ensure a robust
operational risk framework.
A.
Board and Management Oversight
Supervisory Standards:
S 2.
The board of directors must oversee the development of the firm-wide
operational risk framework, as well as major changes to the framework.
Management roles and accountability must be clearly established.
S 3.
The board of directors and management must ensure that appropriate resources
are allocated to support the operational risk framework.
16.
The board is responsible for overseeing the establishment of the operational risk
framework, but may delegate the responsibility for implementing the framework to management
with the authority necessary to allow for its effective implementation. Other key responsibilities
of the board include:
•
•
•
•
•
17.
Ensuring appropriate management responsibility, accountability and reporting;
Understanding the major aspects of the institution’s operational risk as a distinct risk
category that should be managed;
Reviewing periodic high-level reports on the institution’s overall operational risk
profile, which identify material risks and strategic implications for the institution;
Overseeing significant changes to the operational risk framework; and
Ensuring compliance with regulatory disclosure requirements.
Effective board and management oversight forms the cornerstone of an effective
operational risk management process. The board and management have several broad
responsibilities with respect to operational risk:
•
To establish a framework for assessing operational risk exposure and identify the
institution’s tolerance for operational risk;
3
For the purposes of AMA, “functional independence” is defined as the ability to carry out work freely and
objectively and render impartial and unbiased judgments. There should be appropriate independence between the
firm-wide operational risk management functions, line of business management and staff and the testing/verification
functions. Supervisory assessments of independence issues will rely upon existing regulatory guidance (e.g. audit,
internal control systems, board of directors/management, etc.)
277
•
•
•
•
•
18.
To identify the senior managers who have the authority for managing operational
risk;
To monitor the institution’s performance and overall operational risk profile,
ensuring that it is maintained at prudent levels and is supported by adequate
capital;
To implement sound fundamental risk governance principles that facilitate the
identification, measurement, monitoring, and control of operational risk;
To devote adequate human and technical resources to operational risk
management; and
To institute remuneration policies that are consistent with the institution’s appetite
for risk and are sufficient to attract qualified operational risk management and
staff.
Management should translate the operational risk management framework into specific
policies, processes and procedures that can be implemented and verified within the institution’s
different business units. Communication of these elements will be essential to the understanding
and consistent treatment of operational risk across the institution. While each level of
management is responsible for effectively implementing the policies and procedures within its
purview, senior management should clearly assign authority, responsibilities, and reporting
relationships to encourage and maintain this accountability and ensure that the necessary
resources are available to manage operational risk. Moreover, management should assess the
appropriateness of the operational risk management oversight process in light of the risks
inherent in a business unit’s activities. The testing and verification function is responsible for
completing timely and comprehensive assessments of the effectiveness of implementation of the
institution’s operational risk framework at the line of business and firm-wide levels.
19.
Management collectively is also responsible for ensuring that the institution has qualified
staff and sufficient resources to carry out the operational risk functions outlined in the
operational risk framework. Additionally, management must communicate operational risk
278
issues to appropriate staff that may not be directly involved in its management. Key
management responsibilities include ensuring that:
•
•
•
B.
Operational risk management activities are conducted by qualified staff with the
necessary experience, technical capabilities and access to adequate resources;
Sufficient resources have been allocated to operational risk management, in the
business lines as well as the independent firm-wide operational risk management
function and verification areas, so as to sufficiently monitor and enforce
compliance with the institution’s operational risk policy and procedures; and
Operational risk issues are effectively communicated with staff responsible for
managing credit, market and other risks, as well as those responsible for
purchasing insurance and managing third-party outsourcing arrangements.
Independent Firm-wide Risk Management Function
Supervisory Standards:
S 4.
The institution must have an independent operational risk management function
that is responsible for overseeing the operational risk framework at the firm
level to ensure the development and consistent application of operational risk
policies, processes, and procedures throughout the institution.
S 5.
The firm-wide operational risk management function must ensure appropriate
reporting of operational risk exposures and loss data to the board of directors
and senior management.
20.
The institution must have an independent firm-wide operational risk management
function. The roles and responsibilities of the function will vary between institutions, but must
be clearly documented. The independent firm-wide operational risk function should have
organizational stature commensurate with the institution’s operational risk profile, while
remaining independent of the lines of business and the testing and verification function. At a
minimum, the institution’s independent firm-wide operational risk management function should
ensure the development of policies, processes, and procedures that explicitly manage operational
risk as a distinct risk to the institution’s safety and soundness. These policies, processes and
procedures should include principles for how operational risk is to be identified, measured,
279
monitored, and controlled across the organization. Additionally, they should provide for the
collection of the data needed to calculate the institution’s operational risk exposure.
21.
Additional responsibilities of the independent firm-wide operational risk management
function include:
•
•
•
•
•
C.
Assisting in the implementation of the overall firm-wide operational risk
framework;
Reviewing the institution's progress towards stated operational risk objectives,
goals and risk tolerances;
Periodically reviewing the institution’s operational risk framework to consider the
loss experience, effects of external market changes, other environmental factors,
and the potential for new or changing operational risks associated with new
products, activities or systems. This review process should include an assessment
of industry best practices for the institution’s activities, systems and processes;
Reviewing and analyzing operational risk data and reports; and
Ensuring appropriate reporting to senior management and the board.
Line of Business Management
Supervisory Standards:
S 6.
Line of business management is responsible for the day-to-day management of
operational risk within each business unit.
S 7.
Line of business management must ensure that internal controls and practices
within their line of business are consistent with firm-wide policies and
procedures to support the management and measurement of the institution’s
operational risk.
22.
Line of business management is responsible for both managing operational risk within
the business lines and ensuring that policies and procedures are consistent with and support the
firm-wide operational risk framework. Management should ensure that business-specific
policies, processes, procedures and staff are in place to manage operational risk for all material
products, activities, and processes. Implementation of the operational risk framework within
each line of business should reflect the scope of that business and its inherent operational
280
complexity and operational risk profile. Line of business management must be independent of
both the firm-wide operational risk management and the testing and verification functions.
VI.
Operational Risk Management Elements
23.
The operational risk management framework provides the overall operational risk
strategic direction and ensures that an effective operational risk management and measurement
process is adopted throughout the institution. The framework should provide for the consistent
application of operational risk policies and procedures throughout the institution and address the
roles of both the independent firm-wide operational risk management function and the lines of
business. The framework should also provide for the consistent and comprehensive capture of
data elements needed to measure and verify the institution’s operational risk exposure, as well as
appropriate operational risk analytical frameworks, reporting systems, and mitigation strategies.
The framework must also include independent testing and verification to assess the effectiveness
of implementation of the institution’s operational risk framework, including compliance with
policies, processes, and procedures.
24.
In practice, an institution’s operational risk framework must reflect the scope and
complexity of business lines, as well as the corporate organizational structure. Each institution’s
operational risk profile is unique and requires a tailored risk management approach appropriate
for the scale and materiality of the risks present, and the size of the institution. There is no single
framework that would suit every institution; different approaches will be needed for different
institutions. In fact, many operational risk management techniques continue to evolve rapidly to
keep pace with new technologies, business models and applications.
25.
The key elements in the operational risk management process include:
•
Appropriate policies and procedures;
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•
•
•
•
A.
Efforts to identify and measure operational risk;
Effective monitoring and reporting;
A sound system of internal controls; and
Appropriate testing and verification of the operational risk framework.
Operational Risk Policies and Procedures
Supervisory Standards:
S 8.
26.
The institution must have policies and procedures that clearly describe the
major elements of the operational risk management framework, including
identifying, measuring, monitoring, and controlling operational risk.
Operational risk management policies, processes, and procedures should be documented
and communicated to appropriate staff. The policies and procedures should outline all aspects of
the institution’s operational risk management framework, including:
•
•
•
•
•
•
•
•
•
•
B.
27.
The roles and responsibilities of the independent firm-wide operational risk
management function and line of business management;
A definition for operational risk, including the loss event types that will be
monitored;
The capture and use of internal and external operational risk loss data, including
large potential events (including the use of Scenario analysis);
The development and incorporation of business environment and internal control
factor assessments into the operational risk framework;
A description of the internally derived analytical framework that quantifies the
operational risk exposure of the institution;
An outline of the reporting framework and the type of data/information to be
included in line of business and firm-wide reporting;
A discussion of qualitative factors and risk mitigants and how they are
incorporated into the operational risk framework;
A discussion of the testing and verification processes and procedures;
A discussion of other factors that affect the measurement of operational risk; and
Provisions for the review and approval of significant policy and procedural
exceptions.
Identification and Measurement of Operational Risk
The result of a comprehensive program to identify and measure operational risk is an
assessment of the institution’s operational risk exposure. Management must establish a process
that identifies the nature and types of operational risk and their causes and resulting effects on
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the institution. Proper operational risk identification supports the reporting and maintenance of
capital for operational risk exposure and events, facilitates the establishment of mechanisms to
mitigate or control the risks, and ensures that management is fully aware of the sources of
emerging operational risk loss events.
C.
Monitoring and Reporting
Supervisory Standards:
S 9.
Operational risk management reports must address both firm-wide and line of
business results. These reports must summarize operational risk exposure, loss
experience, relevant business environment and internal control assessments, and
must be produced no less often than quarterly.
S 10.
28.
Operational risk reports must also be provided periodically to senior
management and the board of directors, summarizing relevant firm-wide
operational risk information.
Ongoing monitoring of operational risk exposures is a key aspect of an effective
operational risk framework. To facilitate monitoring of operational risk, results from the
measurement system should be summarized in reports that can be used by the firm-wide
operational risk and line of business management functions to understand, manage, and control
operational risk and losses. These reports should serve as a basis for assessing operational risk
and related mitigation strategies and creating incentives to improve operational risk management
throughout the institution.
29.
Operational risk management reports should summarize:
•
•
•
•
Operational risk loss experience on an institution, line of business, and event-type
basis;
Operational risk exposure;
Changes in relevant risk and control assessments;
Management assessment of early warning factors signaling an increased risk of
future losses;
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•
Trend analysis, allowing line of business and independent firm-wide operational
risk management to assess and manage operational risk exposures, systemic line
of business risk issues, and other corporate risk issues;
Exception reporting; and
To the extent developed, operational risk causal factors.
•
•
30.
High-level operational risk reports must also be produced periodically for the board and
senior management. These reports must provide information regarding the operational risk
profile of the institution, including the sources of material risk both from a firm-wide and line of
business perspective, versus established management expectations.
D.
Internal Control Environment
Supervisory Standards:
S 11.
31.
An institution’s internal control structure must meet or exceed minimum
regulatory standards established by the Agencies.
Sound internal controls are essential to an institution’s management of operational risk
and are one of the foundations of safe and sound banking. When properly designed and
consistently enforced, a sound system of internal controls will help management safeguard the
institution’s resources, produce reliable financial reports, and comply with laws and regulations.
Sound internal controls will also reduce the possibility of significant human errors and
irregularities in internal processes and systems, and will assist in their timely detection when
they do occur.
32.
The Agencies are not introducing any new internal control standards, but rather
emphasizing the importance of meeting existing standards. There is a recognition that internal
control systems will differ among institutions due to the nature and complexity of an institution’s
products and services, organizational structure, and risk management culture. The AMA
standards allows for these differences, while also establishing a baseline standard for the quality
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of the internal control structure. Institutions will be expected to at least meet the minimum
interagency standards4 relating to internal controls as a criterion for AMA qualification.
33.
The extent to which an institution meets or exceeds the minimum standards will primarily
be assessed through current and ongoing supervisory processes. As noted earlier, the Agencies
will leverage off existing examination processes, to avoid duplication in assessing an
institution’s implementation of an AMA framework. Assessing the internal control environment
is clearly an area where the supervisory authorities already focus considerable attention.
VII. Elements of an AMA Framework
Supervisory Standards:
S 12.
The institution must demonstrate that it has appropriate internal loss event
data, relevant external loss event data, assessments of business environment and
internal controls factors, and results from scenario analysis to support its
operational risk management and measurement framework.
S 13.
The institution must include the regulatory definition of operational risk as the
baseline for capturing the elements of the AMA framework and determining its
operational risk exposure.
S 14.
The institution must have clear standards for the collection and modification of
the elements of the operational risk AMA framework.
34.
Operational risk inputs play a significant role in both the management and measurement
of operational risk. Necessary elements of an institution’s AMA framework include internal loss
event data, relevant external loss event data, results of scenario analysis, and assessments of the
institution’s business environment and internal controls. Operational risk inputs aid the
institution in identifying the level and trend of operational risk, determining the effectiveness of
4
There are a number of interagency standards that cover topics relevant to the internal control structure. These
include, for example, the Interagency Policy Statement on the Internal Audit Function and Its Outsourcing (March
2003), the Federal Financial Institution’s Examination Council’s (FFIEC’s) Business Continuity Planning Booklet
(May 2003), the FFIEC’s Information Security Booklet (January 2003). In addition, each Agency has extensive
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risk management and control efforts, highlighting opportunities to better mitigate operational
risk, and assessing operational risk on a forward-looking basis.
35.
To use its AMA framework, an institution must demonstrate that it has established a
consistent and comprehensive process for the capture of all elements of the AMA framework.
The institution must also demonstrate that it has clear standards for the collection and
modification of all AMA inputs. While the analytical framework will generally combine these
inputs to develop the operational risk exposure , supervisors must have the capacity to review the
individual inputs as well; specifically, supervisors will need to review the loss information that is
being provided to the analytical framework that stems from internal loss event data, versus the
loss event information provided by external loss event data capture, scenario analysis, or the
assessments of the business environment and internal control factors.
36.
The capture systems must cover all material business lines, business activities and
corporate functions that could generate operational risk. The institution must have a defined
process that establishes responsibilities over the systems developed to capture the AMA
elements. In particular, the issue of overriding the data capture systems must be addressed. Any
overrides should be tracked separately and documented. Tracking overrides separately allows
management and supervisors to identify the nature and rationale, including whether they stem
from simple input errors or, more importantly, from exclusion because a loss event was not
pertinent for the quantitative measurement. Management should have clear standards for
addressing overrides and should clearly delineate who has authority to override the data systems
and under what circumstances.
guidance on corporate governance, internal controls, and monitoring and reporting in its respective examination
policies and procedures.
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37.
As noted earlier, for AMA qualification purposes, an institution’s operational risk
framework must, at a minimum, use the definition of operational risk that is provided in
paragraph 10 when capturing the elements of the AMA framework. Institutions may use an
expanded definition if considered more appropriate for risk management and measurement
efforts. However, for the quantification of operational risk exposure for regulatory capital
purposes, an institution must demonstrate that the AMA elements are captured so as to meet the
baseline definition.
A. Internal Operational Risk Loss Event Data
Supervisory Standards:
S 15.
The institution must have at least five years of internal operational risk loss
data5 captured across all material business lines, events, product types, and
geographic locations.
S 16.
The institution must be able to map internal operational risk losses to the seven
loss-event type categories.
S 17.
The institution must have a policy that identifies when an operational risk loss
becomes a loss event and must be added to the loss event database. The policy
must provide for consistent treatment across the institution.
S 18.
The institution must establish appropriate operational risk data thresholds.
S 19.
Losses that have any characteristics of credit risk, including fraud-related credit
losses, must be treated as credit risk for regulatory capital purposes. The
institution must have a clear policy that allows for the consistent treatment of
loss event classifications (e.g., credit, market, or operational risk) across the
organization.
38.
The key to internal data integrity is the consistency and completeness with which loss
event data capture processes are implemented across the institution. Management must ensure
that operational risk loss event information captured is consistent across the business lines and
5
With supervisory approval, a shorter initial historical observation period is acceptable for banks newly authorized
to use an AMA methodology.
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incorporates any corporate functions that may also experience operational risk events. Policies
and procedures should be addressed to the appropriate staff to ensure that there is satisfactory
understanding of operational risk and the data capture requirements under the operational risk
framework. Further, the independent operational risk management function must ensure that the
loss data is captured across all material business lines, products types, event types, and from all
significant geographic locations. The institution must be able to capture and aggregate internal
losses that cross multiple business lines or event types. If data is not captured across all business
lines or from all geographic locations, the institution must document and explain the exceptions.
39.
AMA institutions must be able to map operational risk losses into the seven loss event
categories defined in paragraph 10. Institutions will not be required to produce reports or
perform analysis for internal purposes on the basis of the loss event categories, but will be
expected to use the information about the event-type categories as a check on the
comprehensiveness of the institution’s data set.
40.
The institution must have five years of internal loss data, although a shorter range of
historical data may be allowed, subject to supervisory approval. The extent to which an
institution collects operational risk loss event data will, in part, be dependent upon the data
thresholds that the institution establishes. There are a number of standards that an institution
may use to establish the thresholds. They may be based on product types, business lines,
geographic location, or other appropriate factors. The Agencies will allow flexibility in this area,
provided the institution can demonstrate that the thresholds are reasonable, do not exclude
important loss events, and capture a significant proportion of the institution’s operational risk
losses.
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41.
The institution must capture comprehensive data on all loss events above its established
threshold level. Aside from information on the gross loss amount, the institution should collect
information about the date of the event, any recoveries, and descriptive information about the
drivers or causes of the loss event. The level of detail of any descriptive information should be
commensurate with the size of the gross loss amount. Examples of the type of information
collected include:
•
•
•
•
•
•
•
•
•
•
•
42.
Loss amount;
Description of loss event;
Where the loss is reported and expensed;
Loss event type category;
Date of the loss;
Discovery date of the loss;
Event end date;
Management actions;
Insurance recoveries;
Other recoveries; and
Adjustments to the loss estimate.
There are a number of additional data elements that may be captured. It may be
appropriate, for example, to capture data on “near miss” events, where no financial loss was
incurred. These near misses will not factor into the regulatory capital calculation, but may be
useful for the operational risk management process.
43.
Institutions will also be permitted and encouraged to capture loss events in their
operational risk databases that are treated as credit risk for regulatory capital purposes, but have
an underlying element of operational risk failure. These types of events, while not incorporated
into the regulatory capital calculation, may have implications for operational risk management.
It will be essential for institutions that capture loss events that are treated differently for
regulatory capital and management purposes to demonstrate that 1) loss events are being
captured consistently across the institution; 2) the data systems are sufficiently advanced to allow
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for this differential treatment of loss events; and 3) credit, market, and operational risk losses are
being appropriated in the correct manner for regulatory capital purposes.
44.
The Agencies have established a clear boundary between credit and operational risks for
regulatory capital purposes. If a loss event has any element of credit risk, it must be treated as
credit risk for regulatory capital purposes. This would include all credit-related fraud losses. In
addition, operational risk losses with credit risk characteristics that have historically been
included in institutions’ credit risk databases will continue to be treated as credit risk for the
purposes of calculating minimum regulatory capital.
45.
The accounting guidance for credit losses provides that creditors recognize credit losses
when it is probable that they will be unable to collect all amounts due according to the
contractual terms of a loan agreement. Credit losses may result from the creditor’s own
underwriting, processing, servicing or administrative activities along with the borrower’s failure
to pay according to the terms of the loan agreement. While the creditor’s personnel, systems,
policies or procedures may affect the timing or magnitude of a credit loss, they do not change its
character from credit to operational risk loss for regulatory capital purposes. Losses that arise
from a contractual relationship between a creditor and a borrower are credit losses whereas
losses that arise outside of a relationship between a creditor and a borrower are operational
losses.
B. External Data
Supervisory Standards:
S 20.
The institution must have policies and procedures that provide for the use of
external loss data in the operational risk framework.
S 21.
Management must systematically review external data to ensure an
understanding of industry experience.
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46.
External data may serve a number of different purposes in the operational risk
framework. Where internal loss data is limited, external data may be a useful input in
determining the institution’s level of operational risk exposure. Even where external loss data is
not an explicit input to an institution’s data set, such data provides a means for the institution to
understand industry experience, and in turn, provides a means for assessing the adequacy of its
internal data. External data may also prove useful to inform scenario analysis, fit severity
distributions, or benchmark the overall operational risk exposure results.
47.
To incorporate external loss information into an institution’s framework, the institution
should collect the following information:
•
•
•
•
•
•
48.
External loss amount;
External loss description;
Loss event type category;
External loss event date;
Adjustments to the loss amount (i.e., recoveries, insurance settlements, etc) to the
extent that they are known; and
Sufficient information about the reporting institution to facilitate comparison to its
own organization.
Institutions may obtain external loss data in any reasonable manner. There are many
ways to do so; some institutions are using data acquired through membership with industry
consortia while other institutions are using data obtained from vendor databases or public
sources such as court records or media reports. In all cases, management will need to carefully
evaluate the data source to ensure that they are comfortable that the information being reported is
relevant and reasonably accurate.
C. Business Environment and Internal Control Factor Assessments
Supervisory Standards:
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S 22.
The institution must have a system to identify and assess business environment
and internal control factors.
S 23.
Management must periodically compare the results of their business
environment and internal control factor assessments against actual operational
risk loss experience.
49.
While internal and external loss data provide a historical perspective on operational risk,
it is also important that institutions incorporate a forward-looking element to the operational risk
measure. In principle, an institution with strong internal controls in a stable business
environment will have less exposure to operational risk than an institution with internal control
weaknesses that is growing rapidly or introducing new products. In this regard, institutions will
be required to identify the level and trends in operational risk in the institution. These
assessments must be current, comprehensive across the institution, and identify the critical
operational risks facing the institution.
50.
The business environment and internal control factor assessments should reflect both the
positive and negative trends in risk management within the institution as well as changes in an
institution’s business activities that increase or decrease risk. Because the results of the risk
assessment are part of the capital methodology, management must ensure that the risk
assessments are done appropriately and reflect the risks of the institution. Periodic comparisons
should be made between actual loss exposure and the assessment results.
51.
The framework established to maintain the risk assessments must be sufficiently flexible
to encompass an institution’s increased complexity of activities, new activities, changes in
internal control systems, or an increased volume of information.
D. Scenario Analysis
Supervisory Standards:
292
S 24.
52.
Management must have policies and procedures that identify how scenario
analysis will be incorporated into the operational risk framework.
Scenario analysis is a systematic process of obtaining expert opinions from business
managers and risk management experts to derive reasoned assessments of the likelihood and
impact of plausible operational losses consistent with the regulatory soundness standard. Within
an institution’s operational risk framework, scenario analysis may be used as an input or may, as
discussed below, form the basis of an operational risk analytical framework.
53.
As an input to the institution’s framework, scenario analysis is especially relevant for
business lines or loss event types where internal data, external data, and assessments of the
business environment and internal control factors do not provide a sufficiently robust estimate of
the institution’s exposure to operational risk. In some cases, an institution’s internal loss history
may be sufficient to provide a reasonable estimate of exposure to future operational losses. In
other cases, the use of well-reasoned, scaled external data may itself be a form of scenario
analysis.
54.
The institution must have policies and procedures that define scenario analysis and
identify its role in the operational risk framework. The policy should cover key elements of
scenario analysis, such as the manner in which the scenarios are generated, the frequency with
which they are updated, and the scope and coverage of operational loss events they are intended
to reflect.
VIII. Risk Quantification
A.
Analytical Framework
Supervisory Standards:
S 25.
The institution must have a comprehensive operational risk analytical
framework that provides an estimate of the institution’s operational risk
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exposure, which is the aggregate operational loss that it faces over a one-year
period at a soundness standard consistent with a 99.9 per cent confidence level.
S 26.
Management must document the rationale for all assumptions underpinning its
chosen analytical framework, including the choice of inputs, distributional
assumptions, and the weighting across qualitative and quantitative elements.
Management must also document and justify any subsequent changes to these
assumptions.
S 27.
The institution’s operational risk analytical framework must use a combination
of internal operational loss event data, relevant external operational loss event
data, business environment and internal control factor assessments, and scenario
analysis. The institution must combine these elements in a manner that most
effectively enables it to quantify its operational risk exposure. The institution
can choose the analytical framework that is most appropriate to its business
model.
S 28.
The institution’s capital requirement for operational risk will be the sum of
expected and unexpected losses unless the institution can demonstrate, consistent
with supervisory standards, the expected loss offset.
55.
The industry has made significant progress in recent years in developing analytical
frameworks to quantify operational risk. The analytical frameworks, which are a part of the
overall operational risk framework, are based on various combinations of an institution’s own
operational loss experience, the industry’s operational loss experience, the size and scope of the
institution’s activities, the quality of the institution’s control environment, and management’s
expert judgment. Because these models capture specific characteristics of each institution, such
models yield unique risk-sensitive estimates of the institutions’ operational risk exposures.
56.
While the Agencies are not specifying the exact methodology that an institution should
use to determine its operational risk exposure, minimum supervisory standards for acceptable
approaches have been developed. These standards have been set so as to assure that the
regulation can accommodate continued evolution of operational risk quantification techniques,
yet remain amenable to consistent application and enforcement across institutions. The Agencies
will require that the institution have a comprehensive analytical framework that provides an
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estimate of the aggregate operational loss that it faces over a one-year period at a soundness
standard consistent with a 99.9 percent confidence level, referred to as the institution’s
operational risk exposure. The institution will multiply the exposure estimate by 12.5 to obtain
risk weighted assets for operational risk, and add this figure to risk-weighted assets for credit and
market risk to obtain total risk-weighted assets. The final minimum regulatory capital number
will be 8 percent of total risk-weighted assets.
57.
The Agencies expect that there will be significant variation in analytical frameworks
across institutions, with each institution tailoring its framework to leverage existing technology
platforms and risk management procedures. These approaches may only be used, provided they
meet the supervisory standards and include, as inputs, internal operational loss event data,
relevant external operational loss event data, assessments of business environment and internal
control factors, and scenario analysis. The Agencies do expect that there will be some
uncertainty and potential error in the analytical frameworks because of the evolving nature of
operational risk measurement and data capture. Therefore, a degree of conservatism will need to
be built into the analytical frameworks to reflect the evolutionary status of operational risk and
its impact on data capture and analytical modeling.
58.
A diversity of analytical approaches is emerging in the industry, combining and
weighting these inputs in different ways. Most current approaches seek to estimate loss
frequency and loss severity to arrive at an aggregate loss distribution. Institutions then use the
aggregate loss distribution to determine the appropriate amount of capital to hold for a given
soundness standard. Scenario analysis is also being used by many institutions, albeit to
significantly varying degrees. Some institutions are using scenario analysis as the basis for their
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analytical framework, while others are incorporating scenarios as a means for considering the
possible impact of significant operational losses on their overall operational risk exposure.
59.
The primary differences among approaches being used today relate to the weight that
institutions place on each input. For example, institutions with comprehensive internal data may
place less emphasis on external data or scenario analysis. Another example is that some
institutions estimate a unique loss distribution for each business line/loss type combination
(bottom-up approach) while others estimate a loss distribution on a firm-wide basis and then use
an allocation methodology to assign capital to business lines (top-down approach).
60.
The Agencies expect internal loss event data to play an important role in the institution’s
analytical framework, hence the requirement for five years of internal operational risk loss data.
However, as footnote 5 makes clear, five years of data is not always required for the analytical
framework. For example, if a bank exited a business line, the institution would not be expected
to make use of that business unit’s loss experience unless it had relevance for other activities of
the institution. Another example would be where a bank has made a recent acquisition where the
acquired firm does not have internal loss event data. In these cases, the Agencies expect the
institution to make use of the loss data available at the acquired institution and any internal loss
data from operations similar to that of the acquired firm, but the institution will likely have to
place more weight relevant external loss event data, results from scenario analysis, and factors
reflecting assessments of the business environment and internal controls.
61.
Whatever analytical approach an institution chooses, it must document and provide the
rationale for all assumptions embedded in its chosen analytical framework, including the choice
of inputs, distributional assumptions, and the weighting of qualitative and quantitative elements.
296
Management must also document and justify any subsequent changes to these assumptions. This
documentation should:
•
•
•
•
•
•
•
•
62.
Clearly identify how the different inputs are combined and weighted to arrive at the
overall operational risk exposure so that the analytical framework is transparent. The
documentation should demonstrate that the analytical framework is comprehensive and
internally consistent. Comprehensiveness means that all required inputs are incorporated
and appropriately weighted. At the same time, there should not be overlaps or double
counting.
Clearly identify the quantitative assumptions embedded in the methodology and provide
explanation for the choice of these assumptions. Examples of quantitative assumptions
include distributional assumptions about frequency and severity, the methodology for
combining frequency and severity to arrive at the overall loss distribution, and
dependence assumptions between operational losses across and within business lines.
Clearly identify the qualitative assumptions embedded in the methodology and provide
explanations for the choice of these assumptions. Examples of qualitative assumptions
include the use of business environment and control factors as well as scenario analysis in
the approach.
Where feasible, provide results based purely on quantitative methods separately from
results that incorporate qualitative factors. This will provide a transparent means of
determining the relative importance of quantitative versus qualitative inputs.
Where feasible, provide results based on alternative quantitative and qualitative
assumptions to gauge the overall model’s sensitivity to these assumptions.
Provide a comparison of the operational risk exposure estimate generated by the
analytical framework with actual loss experience over time, to assess the reasonable of
the framework’s outputs.
Clearly identify all changes to assumptions, and provide explanations for such changes.
Clearly identify the results of an independent verification of the analytical framework.
The regulatory capital charge for operational risk will include both expected losses (EL)
and unexpected losses (UL). The Agencies have considered two approaches that might allow for
some recognition of EL; these approaches are reserving and budgeting. However, both
approaches raise questions about their ability to act as an EL offset for regulatory capital
purposes. The current U.S. GAAP treatment for reserves (or liabilities) is based on an incurredloss (liability) model. Given that EL is looking beyond current losses to losses that will be
incurred in the future, establishing a reserve for operational risk EL is not likely to meet US
accounting standards. While reserves are specific allocations for incurred losses, budgeting is a
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process of generally allocating future income for loss contingencies, including losses resulting
from operational risk. Institutions will be required to demonstrate that budgeted funds are
sufficiently capital-like and remain available to cover EL over the next year. In addition, an
institution will not be permitted to recognize EL offsets on budgeted loss contingencies that fall
below the established data thresholds; this is relevant as many institutions currently budget for
low severity, high frequency events that are more likely to fall below most institutions’
thresholds.
63.
An institution’s analytical framework complements but does not substitute for prudent
controls. Rather, with improved risk measurement, institutions are finding that they can make
better-informed strategic decisions regarding enhancements to controls and processes, the
desired scale and scope of the operations, and how insurance and other risk mitigation tools can
be used to offset operational risk exposure.
B. Accounting for Dependence
Supervisory Standards:
S 29.
64.
Management must document how its chosen analytical framework accounts for
dependence (e.g., correlations) among operational losses across and within
business lines. The institution must demonstrate that its explicit and embedded
dependence assumptions are appropriate, and where dependence assumptions
are uncertain, the institution must use conservative estimates.
Management must document how its chosen analytical framework accounts for
dependence (e.g., correlation) between operational losses across and within business lines. The
issue of dependence is closely related to the choice between a bottom-up or a top-down modeling
approach. Under a bottom-up approach, explicit assumptions regarding cross-event dependence
are required to estimate operational risk exposure at the firm-wide level. Management must
demonstrate that these assumptions are appropriate and reflect the institution’s current
298
environment. If the dependence assumptions are uncertain, the institution must choose
conservative estimates. In so doing, the institution should consider the possibility that crossevent dependence may not be constant, and may increase during stress environments.
65.
Under a top-down approach, an explicit assumption regarding dependence is not
required. However, a parametric distribution for loss severity may be more difficult to specify
under the top-down approach, as it is a statistical mixture of (potentially) heterogeneous business
line and event type distributions. Institutions must carefully consider the conditions necessary
for the validity of top-down approaches, and whether these conditions are met in their particular
circumstances. Similar to bottom-up approaches, institutions using top-down approaches must
ensure that implicit dependence assumptions are appropriate and reflect the institution’s current
environment. If historic dependence assumptions embedded in top-down approaches are
uncertain, the institution must be conservative and implement a qualitative adjustment to the
analysis.
IX. Risk Mitigation
Supervisory Standards:
S 30.
66.
Institutions may reduce their operational risk exposure results by no more than
20% to reflect the impact of risk mitigants. Institutions must demonstrate that
mitigation products are sufficiently capital-like to warrant inclusion in the
adjustment to the operational risk exposure.
There are many mechanisms to manage operational risk, including risk transfer through
risk mitigation products. Because risk mitigation can be an important element in limiting or
reducing operational risk exposure in an institution, an adjustment is being permitted that will
directly impact the amount of regulatory capital that is held for operational risk. The adjustment
is limited to 20% of the overall operational risk exposure result determined by the institution
using its loss data, qualitative factors, and quantitative framework.
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67.
Currently, the primary risk mitigant used for operational risk is insurance. There has
been discussion that some securities products may be developed to provide risk mitigation
benefits; however, to date, no specific products have emerged that have characteristics sufficient
to be considered capital-replacement for operational risk. As a result, securities products and
other capital market instruments may not be factored in to the regulatory capital risk mitigation
adjustment at this time.
68.
For an institution that wishes to adjust its regulatory capital requirement as a result of the
risk mitigating impact of insurance, management must demonstrate that the insurance policy is
sufficiently capital-like to provide the cushion that is necessary. A product that would fall in this
category must have the following characteristics:
•
•
•
•
•
69.
The policy is provided through a third party6 that has a minimum claims paying
ability rating of A7;
The policy has an initial term of one year8;
The policy has no exclusions or limitations based upon regulatory action or for
the receiver or liquidator of a failed bank;
The policy has clear cancellation and non-renewal notice periods; and
The policy coverage has been explicitly mapped to actual operational risk
exposure of the institution.
Insurance policies that meet these standards may be incorporated into an institution’s
adjustment for risk mitigation. An institution should be conservative in its recognition of such
policies, for example, the institution must also demonstrate that insurance policies used as the
basis for the adjustment have a history of timely payouts. If claims have not been paid on a
timely basis, the institution must exclude that policy from the operational risk capital adjustment.
6
Where operational risk is transferred to a captive or an affiliated insurer such that risk is retained within the group
structure, recognition of such risk transfer will only be allowed for regulatory capital purposes where the risk has
been transferred to a third party (e.g., an unaffiliated reinsurer) that meets the standards set forth in this section.
7
Rating agencies may use slightly different rating scales. For the purpose of this supervisory guidance, the insurer
must have a rating that is at least the equivalent of A under Standard and Poor’s Insurer Financial Strength Ratings
or an A2 under Moody’s Insurance Financial Strength Ratings.
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In addition, the institution must be able to show that the policy would actually be used in the
event of a loss situation; that is, the deductible may not be set so high that no loss would ever
conceivably exceed the deductible threshold.
70.
The Agencies will not specify how institutions should calculate the risk mitigation
adjustment. Nevertheless, institutions are expected to use conservative assumptions when
calculating adjustments. An institution should discount (i.e., apply its own estimates of haircuts)
the impact of insurance coverage to take into account factors, which may limit the likelihood or
size of claims payouts. Among these factors are the remaining terms of a policy, especially
when it is less than a year, the willingness and ability of the insurer to pay on a claim in a timely
manner, the legal risk that a claim may be disputed, and the possibility that a policy can be
cancelled before the contractual expiration.
X. Data Maintenance
Supervisory Standards:
S 31.
71.
Institutions using the AMA approach for regulatory capital purposes must use
advanced data management practices to produce credible and reliable
operational risk estimates.
Data maintenance is a critical factor in an institution’s operational risk framework.
Institutions with advanced data management practices should be able to track operational risk
loss events from initial discovery through final resolution. These institutions should also be able
to make appropriate adjustments to the data and use the data to identify trends, track problem
areas, and identify areas of future risk. Such data should include not only operational risk loss
event information, but also information on risk assessments, which are factored into the
operational risk exposure calculation. In general, institutions using the AMA should have the
8
Institutions must decrease the amount of the adjustment if the remaining term is less than one year. The institution
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same data maintenance standards for operational risk as those set forth for A-IRB institutions
under the credit risk guidance.
72.
Operational risk data elements captured by the institution must be of sufficient depth,
scope, and reliability to:
•
•
•
•
73.
Track and identify operational risk loss events across all business lines, including
when a loss event impact multiple business lines.
Calculate capital ratios based on operational risk exposure results. The institution
must also be able to factor in adjustments related to risk mitigation, correlations,
and risk assessments.
Produce internal and public reports on operational risk measurement and
management results, including trends revealed by loss data and/or risk
assessments. The institution must also have sufficient data to produce exception
reports for management.
Support risk management activities.
The data warehouse9 must contain the key data elements needed for operational risk
measurement, management, and verification. The precise data elements may vary by institution
and also among business lines within an institution. An important element of ensuring consistent
reporting of the data elements is to develop comprehensive definitions for each data element
used by the institution for reporting operational risk loss events or for the risk assessment inputs.
The data must be stored in an electronic format to allow for timely retrieval for analysis,
verification and testing of the operational risk framework, and required disclosures.
74.
Management will need to identify those responsible for maintaining the data warehouse.
In particular, policies and processes will need to be developed for delivering, storing, retaining,
and updating the data warehouse. Policies and procedures must also cover the edit checks for
data input functions, as well as the requirements for the testing and verification function to verify
data integrity. Like other areas of the operational risk framework, it is critical that management
must have a clear policy in place that links the remaining term to the adjustment factor.
9
In this document, the terms “database” and “data warehouse” are used interchangeably to refer to a collection of
data arranged for easy retrieval using computer technology.
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ensure accountability for ongoing data maintenance, as this will impact operational risk
management and measurement efforts.
XI. Testing and Verification
Supervisory Standards:
S 32.
The institution must test and verify the accuracy and appropriateness of the
operational risk framework and results.
S 33.
Testing and verification must be done independently of the firm-wide
operational risk management function and the institution’s lines of business.
75.
The operational risk framework must provide for regular and independent testing and
verification of operational risk management policies, processes and measurement systems, as
well as operational risk data capture systems. For most institutions, operational risk verification
and testing will primarily be done by the audit function. Internal and external audits can provide
an independent assessment of the quality and effectiveness of the control systems’ design and
performance. However, institutions may use other independent internal units (e.g. quality
assurance) or third parties. The testing and verification function, whether internally or externally
performed, should be staffed by qualified individuals who are independent from the firm-wide
operational risk management function and the institution’s lines of business.
76.
The verification of the operational risk measurement system should include the testing of:
•
•
•
•
•
Key operational risk processes and systems;
Data feeds and processes associated with the operational risk measurement
system;
Adjustments to empirical operational risk capital estimates, including operational
risk exposure;
Periodic certification of operational risk models used and their underlying
assumptions; and
Assumptions underlying operational risk exposure, data decision models, and
operational risk capital charge.
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77.
The operational risk reporting processes should be periodically reviewed for scope and
effectiveness. The institution should have independent verification processes to ensure the
timeliness, accuracy, and comprehensiveness of operational risk reporting systems, both at the
firm-wide and the line of business levels.
78.
Independent verification and testing should be done to ensure the integrity and
applicability of the operational risk framework, operational risk exposure/loss data, and the
underlying assumptions driving the regulatory capital measurement process. Appropriate
reports, summarizing operational risk verification and testing findings for both the independent
firm-wide risk management function and lines of business should be provided to appropriate
management and the board of directors or a designated board committee.
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Appendix A
Supervisory Standards for the AMA
S 1.
The institution’s operational risk framework must include an independent firmwide operational risk management function, line of business management
oversight, and independent testing and verification functions.
S 2.
The board of directors must oversee the development of the firm-wide
operational risk framework, as well as major changes to the framework.
Management roles and accountability must be clearly established.
S 3.
The board of directors and management must ensure that appropriate resources
are allocated to support the operational risk framework.
S 4.
The institution must have an independent operational risk management function
that is responsible for overseeing the operational risk framework at the firm
level to ensure the development and consistent application of operational risk
policies, processes, and procedures throughout the institution.
S 5.
The firm-wide operational risk management function must ensure appropriate
reporting of operational risk exposures and loss data to the board of directors
and senior management.
S 6.
Line of business management is responsible for the day-to-day management of
operational risk within each business unit.
S 7.
Line of business management must ensure that internal controls and practices
within their line of business are consistent with firm-wide policies and
procedures to support the management and measurement of the institution’s
operational risk.
S 8.
The institution must have policies and procedures that clearly describe the
major elements of the operational risk management framework, including
identifying, measuring, monitoring, and controlling operational risk.
S 9.
Operational risk management reports must address both firm-wide and line of
business results. These reports must summarize operational risk exposure, loss
experience, relevant business environment and internal control assessments, and
must be produced no less often than quarterly.
S 10.
Operational risk reports must also be provided periodically to senior
management and the board of directors, summarizing relevant firm-wide
operational risk information.
S 11.
An institution’s internal control structure must meet or exceed minimum
regulatory standards established by the Agencies.
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S 12.
The institution must demonstrate that it has appropriate internal loss event
data, relevant external loss event data, assessments of business environment and
internal controls factors, and results from scenario analysis to support its
operational risk management and measurement framework.
S 13.
The institution must include the regulatory definition of operational risk as the
baseline for capturing the elements of the AMA framework and determining its
operational risk exposure.
S 14.
The institution must have clear standards for the collection and modification of
the elements of the operational risk AMA framework.
S 15.
The institution must have at least five years of internal operational risk loss
data10 captured across all material business lines, events, product types, and
geographic locations.
S 16.
The institution must be able to map internal operational risk losses to the seven
loss-event type categories.
S 17.
The institution must have a policy that identifies when an operational risk loss
becomes a loss event and must be added to the loss event database. The policy
must provide for consistent treatment across the institution.
S 18.
The institution must establish appropriate operational risk data thresholds.
S 19.
Losses that have any characteristics of credit risk, including fraud-related credit
losses, must be treated as credit risk for regulatory capital purposes. The
institution must have a clear policy that allows for the consistent treatment of
loss event classifications (e.g., credit, market, or operational risk) across the
organization.
S 20.
The institution must have policies and procedures that provide for the use of
external loss data in the operational risk framework.
S 21.
Management must systematically review external data to ensure an
understanding of industry experience.
S 22.
The institution must have a system to identify and assess business environment
and internal control factors.
S 23.
Management must periodically compare the results of their business
environment and internal control factor assessments against actual operational
risk loss experience.
10
With supervisory approval, a shorter initial historical observation period is acceptable for banks newly authorized
to use an AMA methodology.
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S 24.
Management must have policies and procedures that identify how scenario
analysis will be incorporated into the operational risk framework.
S 25.
The institution must have a comprehensive operational risk analytical
framework that provides an estimate of the institution’s operational risk
exposure, which is the aggregate operational loss that it faces over a one-year
period at a soundness standard consistent with a 99.9 per cent confidence level.
S 26.
Management must document the rationale for all assumptions underpinning its
chosen analytical framework, including the choice of inputs, distributional
assumptions, and the weighting across qualitative and quantitative elements.
Management must also document and justify any subsequent changes to these
assumptions.
S 27.
The institution’s operational risk analytical framework must use a combination
of internal operational loss event data, relevant external operational loss event
data, business environment and internal control factor assessments, and scenario
analysis. The institution must combine these elements in a manner that most
effectively enables it to quantify its operational risk exposure. The institution
can choose the analytical framework that is most appropriate to its business
model.
S 28.
The institution’s capital requirement for operational risk will be the sum of
expected and unexpected losses unless the institution can demonstrate, consistent
with supervisory standards, the expected loss offset.
S 29.
Management must document how its chosen analytical framework accounts for
dependence (e.g., correlations) among operational losses across and within
business lines. The institution must demonstrate that its explicit and embedded
dependence assumptions are appropriate, and where dependence assumptions
are uncertain, the institution must use conservative estimates.
S 30.
Institutions may reduce their operational risk exposure results by no more than
20% to reflect the impact of risk mitigants. Institutions must demonstrate that
mitigation products are sufficiently capital-like to warrant inclusion in the
adjustment to the operational risk exposure.
S 31.
Institutions using the AMA approach for regulatory capital purposes must use
advanced data management practices to produce credible and reliable
operational risk estimates.
S 32.
The institution must test and verify the accuracy and appropriateness of the
operational risk framework and results.
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S 33.
Testing and verification must be done independently of the firm-wide
operational risk management function and the institution’s lines of business.
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