View original document

The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.

Capital Planning at
Large Bank Holding Companies:
Supervisory Expectations and
Range of Current Practice
August 2013


Capital Planning at
Large Bank Holding Companies:
Supervisory Expectations and
Range of Current Practice
August 2013


This and other Federal Reserve Board reports and publications are available online at
To order copies of Federal Reserve Board publications offered in print,
see the Board’s Publication Order Form (
or contact:
Publications Fulfillment
Mail Stop N-127
Board of Governors of the Federal Reserve System
Washington, DC 20551
(ph) 202-452-3245
(fax) 202-728-5886



Introduction ............................................................................................................................... 1
Foundational Risk Management

........................................................................................ 5
Risk Identification ....................................................................................................................... 5

Internal Controls ...................................................................................................................... 7
Scope of Internal Controls ........................................................................................................... 7
Internal Audit .............................................................................................................................. 7
Independent Model Review and Validation ................................................................................... 7
Policies and Procedures .............................................................................................................. 8
Ensuring Integrity of Results ........................................................................................................ 8
Documentation ........................................................................................................................... 9


.............................................................................................................................. 11

Board of Directors ..................................................................................................................... 11
Board Reporting ....................................................................................................................... 11
Senior Management .................................................................................................................. 12
Documenting Decisions ............................................................................................................. 12

Capital Policy ........................................................................................................................... 13
Capital Goals and Targets .......................................................................................................... 14
Capital Contingency Plan .......................................................................................................... 14

BHC Scenario Design ........................................................................................................... 17
Scenario Design and Severity .................................................................................................... 17
Variable Coverage ..................................................................................................................... 18
Clear Narratives ........................................................................................................................ 18

Estimation Methodologies for Losses, Revenues, and Expenses ............................ 19
General Expectations ................................................................................................................ 19
Loss-Estimation Methodologies ................................................................................................. 22
PPNR Projection Methodologies ................................................................................................ 31

Assessing Capital Adequacy Impact ................................................................................ 37
Balance Sheet and RWAs .......................................................................................................... 37
Allowance for Loan and Lease Losses (ALLL) ............................................................................. 38
Aggregation of Projections ........................................................................................................ 38

Concluding Observations

.................................................................................................... 41



The Federal Reserve has previously noted the importance of capital planning at large, complex bank
holding companies (BHCs). Capital is central to a
BHC’s ability to absorb unexpected losses and continue to lend to creditworthy businesses and consumers. It serves as the first line of defense against losses,
protecting the deposit insurance fund and taxpayers.
As such, a large BHC’s processes for managing and
allocating its capital resources are critical not only to
its individual health and performance, but also to the
stability and effective functioning of the U.S. financial system. The Federal Reserve’s Capital Plan Rule
and the associated annual Comprehensive Capital
Analysis and Review (CCAR) have emphasized the
importance the Federal Reserve places on BHCs’
internal capital planning processes, and on the supervisory assessment of all aspects of these processes,
which is a key element of a supervisory program that
is focused on promoting resiliency at the largest
These initiatives have focused not just on the amount
of capital that a BHC has, but also on the internal
practices and policies a firm uses to determine the
amount and composition of capital that would be
adequate, given the firm’s risk exposures and corporate strategies as well as supervisory expectations and
regulatory standards. BHCs have long engaged in
some form of capital planning to address the expectations of shareholders, creditors, customers, and
other stakeholders. The Federal Reserve’s interest in
and expectations for effective capital planning reflect
the importance of the ongoing viability of the largest
BHCs even under stressful financial and economic
conditions. Even if current assessments of capital
adequacy suggest that a BHC’s capital level is sufficient to withstand potential economic stress, robust
capital planning helps ensure that this outcome will
continue to hold in the future. Robust internal capital
planning can also help ensure that BHCs have suffi1

See SR Letter 12-17, “Consolidated Supervision Framework for
Large Financial Institutions,” (December 17, 2012), www; 12 CFR

cient capital in a broad range of future macroeconomic and financial market environments by governing the capital actions—including dividend payments,
share repurchases, and share issuance and conversion—a BHC takes in these situations.
The Federal Reserve’s Capital Plan Rule requires all
U.S.-domiciled, top-tier BHCs with total consolidated assets of $50 billion or more to develop and
maintain a capital plan supported by a robust process
for assessing their capital adequacy.2 CCAR is the
Federal Reserve’s supervisory program for assessing
the capital plans. In 2013, CCAR covered 18 BHCs
that participated in the 2009 Supervisory Capital
Assessment Program (SCAP).3 The Federal Reserve’s
assessment of a BHC’s capital planning process
includes an evaluation of the risk-identification,
-measurement, and -management practices that support the BHC’s capital planning and stress scenario
analysis, an assessment of stressed loss and revenue
estimation practices, and a review of the governance
and controls around these practices. The preamble to
the Capital Plan Rule outlines the elements on which
the Federal Reserve evaluates the robustness of a
BHC’s internal capital planning—also referred to as
the capital adequacy process, or “CAP.” These principles are summarized in figure 1.4
This publication describes the Federal Reserve’s
expectations for internal capital planning at the large,
complex BHCs subject to the Capital Plan Rule in
light of the seven CAP principles. It expands on previous articulations of these supervisory expectations
by providing examples of observed practices among
the BHCs participating in CCAR 2013 and by highlighting those practices considered to be stronger or
leading practices at these firms. In addition, it identi2


12 CFR 225.8.
The plans of the remaining BHCs subject to the Capital Plan
Rule have been assessed through a separate process (the Capital
Plan Review). Beginning in 2014, the capital plans of all BHCs
subject to the Capital Plan Rule will be evaluated in a single,
unified process through CCAR.
See 76 Fed. Reg. 74631, 74634 (December 1, 2011).


Capital Planning at Large Bank Holding Companies

Figure 1. Seven principles of an effective capital adequacy process
Principle 1: Sound foundational risk management
The BHC has a sound risk-measurement and risk-management infrastructure that supports the identification, measurement, assessment,
and control of all material risks arising from its exposures and business activities.

Principle 2: Effective loss-estimation methodologies
The BHC has effective processes for translating risk measures into estimates of potential losses over a range of stressful scenarios and
environments and for aggregating those estimated losses across the BHC.

Principle 3: Solid resource-estimation methodologies
The BHC has a clear definition of available capital resources and an effective process for estimating available capital resources (including
any projected revenues) over the same range of stressful scenarios and environments used for estimating losses.

Principle 4: Sufficient capital adequacy impact assessment
The BHC has processes for bringing together estimates of losses and capital resources to assess the combined impact on capital
adequacy in relation to the BHC’s stated goals for the level and composition of capital.

Principle 5: Comprehensive capital policy and capital planning
The BHC has a comprehensive capital policy and robust capital planning practices for establishing capital goals, determining appropriate
capital levels and composition of capital, making decisions about capital actions, and maintaining capital contingency plans.

Principle 6: Robust internal controls
The BHC has robust internal controls governing capital adequacy process components, including policies and procedures; change control;
model validation and independent review; comprehensive documentation; and review by internal audit.

Principle 7: Effective governance
The BHC has effective board and senior management oversight of the CAP, including periodic review of the BHC’s risk infrastructure and
loss- and resource-estimation methodologies; evaluation of capital goals; assessment of the appropriateness of stressful scenarios
considered; regular review of any limitations and uncertainties in all aspects of the CAP; and approval of capital decisions.

fies practices that the Federal Reserve deems to be
weaker, or in some cases unacceptable, and thus in
need of significant improvement. However, practices
identified in this publication as leading or industrybest practices should not be considered a safe harbor.
The Federal Reserve anticipates that leading practices will continue to evolve as new data become
available, economic conditions change, new products
and businesses introduce new risks, and estimation
techniques advance further.
While the supervisory scenarios and supervisory
stress tests that are required under the Dodd-Frank
Act5 play an important role in CCAR,6 they are not
meant to be and should not be viewed as providing
for an all-encompassing assessment of the possible
risks a BHC may face. A robust internal capital planning process should include modeling practices and

12 CFR part 225, subpart F.
See 12 CFR 225.8(d)(2), 225.8(e)(1).

scenario assumptions that reflect BHC-specific factors. In certain instances, these practices and assumptions may differ considerably from those used by the
Federal Reserve. Indeed, designing an internal capital
planning process that simply seeks to mirror the Federal Reserve’s stress testing is a weak practice. Many
lagging practices identified in this publication involve
modeling approaches or BHC stress scenarios that
fail to reflect BHC-specific factors or that rely on
generic assumptions or “standard” modeling techniques, without sufficient consideration of whether
those assumptions or techniques are the most appropriate ones for the BHC.
The supervisory expectations summarized here are
broad and reflect, at a general level, the key characteristics of a sound and robust internal capital planning process. While certain aspects of the detailed
discussion that follows may be less relevant to individual BHCs based on their business mix and risk

August 2013


profile, the core tenets espoused are broadly applicable to all BHCs subject to the Capital Plan Rule.

the importance the Federal Reserve puts on ensuring
that these firms have robust capital resources.

Importantly, the Federal Reserve has tailored expectations for BHCs of different sizes, scope of operations, activities, and systemic importance in various
aspects of capital planning. For example, the Federal
Reserve has significantly heightened supervisory
expectations for the largest and most complex
BHCs—in all aspects of capital planning—and
expects these BHCs to have capital planning practices
that are widely considered to be leading practices. In
addition, the Federal Reserve recognizes the challenges facing BHCs that are new to CCAR and further recognizes that these BHCs will continue to
develop and enhance their capital planning systems
and processes to meet supervisory expectations.

The sections that follow provide greater detail on
supervisory expectations and the range of current
practice across several dimensions of BHCs’ internal
capital planning processes. The first section discusses
foundational risk management, including identification of risk exposures. The next two sections focus on
controls and governance around internal capital
planning processes. The fourth section covers expectations and the range of current practice concerning
BHCs’ capital policies—the internal guidelines governing the capital action decisions made by a BHC
under a range of potential future conditions for the
firm and for the macroeconomic and financial market environments in which it operates. The subsequent three sections focus on the key elements of
BHCs’ internal enterprise-wide scenario analysis:
design of the stress scenarios and modeling the
impact of the scenarios on losses, revenues, balance
sheet composition and size, and capital. The final section summarizes the Federal Reserve’s conclusions
on the current range of practice at BHCs.

The purpose of this publication is two-fold. First, it
is intended to assist BHC management in assessing
their current capital planning processes and in
designing and implementing improvements to those
processes. Second, it is intended to assist a broader
audience in understanding the key aspects of capital
planning practices at large, complex U.S. BHCs and


Foundational Risk Management

BHCs are expected to have effective riskidentification, -measurement, -management, and
-control processes in place to support their internal
capital planning.7 In addition to the assessments of a
BHC’s stress scenario analysis and stressed loss- and
revenue-estimation practices, supervisory assessments
of BHCs’ internal capital planning will continue
to focus on fundamental risk-identification,
-measurement, and -management practices, as well as
on internal controls and governance. Weaknesses in
these areas may contribute to a negative supervisory
assessment of a BHC’s capital planning process that
could lead to an objection to a BHC’s capital plan.8
A key lesson from the recent financial crisis is that
many financial companies simply failed to adequately
identify the potential exposures and risks stemming
from their firm-wide activities. This was in part a failure of information technology and management
information systems (MIS), the often fractured
nature of which made it difficult for some companies
to identify and aggregate exposures across the firm.
But more importantly, many companies failed to
consider the full scale and scope of exposures, and to
analyze how the size and risk characteristics of their
exposures and business activities might evolve as economic and market conditions changed. Combining a
comprehensive identification of a firm’s business
activities and associated positions across the organization with effective techniques for assessing how
those positions and activities may evolve under
stressful economic and market conditions, and
assessing the potential impact of that evolution on
the capital needs of the firm, are critical elements of
capital planning. A robust internal capital adequacy
assessment process relies on the underlying strength
of each of these elements.

12 CFR 225.8(d)(2).
12 CFR 225.8(e)(2).

Risk Identification
BHCs should have risk-identification processes that
ensure that all risks are appropriately accounted for
when assessing capital needs.9 These processes should
evaluate the full set of potential exposures stemming
from on- and off-balance sheet positions, including
those that could arise from provisions of noncontractual support to off-balance-sheet entities, and
risks conditional on changing economic and financial
market conditions during periods of stress. BHCs
should have a systematic and repeatable process to
identify all risks and consider the potential impact to
capital from these risks. In addition, BHCs should
closely assess any assumptions about risk reduction
resulting from risk transfer and/or mitigation techniques, including, for example, analysis of the
enforceability and effectiveness of any guarantees or
netting and collateral agreements and the access to
and valuation of collateral as exposures and asset values are changing rapidly in a stressed market.
Stronger risk-identification practices include standardized processes through which senior management regularly update risk assessments, review risk
exposures and consider how their risk exposures
might evolve under a variety of stressful situations.
For example, many BHCs maintain a comprehensive
inventory of risks to which they are exposed, and
refresh it as conditions warrant (such as changes in
the business mix and the operating environment)
with input from various units across the BHC. Senior
representatives from major lines of business, corporate risk management, finance and treasury, and
other business and risk functions with perspectives
on BHC-wide positions and risks provide input to
the process. Consideration of the risks inherent in
new products and activities should be a key part of

12 CFR 225.8(d)(2).


Capital Planning at Large Bank Holding Companies

risk-identification and -assessment programs, which
should also consider risks that may be associated
with any change in the BHC’s strategic direction.
Risk measures should be able to capture changes in
an institution’s risk profile—whether due to a change
in the BHC’s strategic direction, specific new products, increased volumes, changes in concentration or
portfolio quality, or the overall economic environment—on a timely basis. These risk measures should
support BHCs’ assessments of capital adequacy and
may be helpful in capital contingency plans as early
warning indicators or contingency triggers, where
BHCs should be able to demonstrate how their identified risks are accounted for in their capital planning
processes. If certain risks are omitted from the
enterprise-wide scenario analysis, BHCs should note
how these risks are accounted for in other aspects of
the capital planning process (see box 1 for illustration
of how BHCs identified and captured certain risks
that are more difficult to quantify in their capital
planning process). If a BHC employs risk quantification methodologies in its capital planning that are
not scenario-based, it should identify which risks
each of the methodologies covers, to facilitate comparability and informed decisionmaking with respect
to overall capital adequacy. BHCs with lagging practice did not transparently link their evaluation of
capital adequacy to the full range of identified risks.
These BHCs were not able to show how all their risks
were accounted for in their capital planning processes. In some cases, staff responsible for capital
planning operated in silos and developed standalone
risk inventories not linked to the enterprise-wide risk
inventory or to other risk governance functions
within their BHCs.

Box 1. Incorporating Risks That Are
More Difficult to Quantify
Scenario-based stress testing is a critical element of
robust capital planning. However, stress testing
based on a limited number of discrete scenarios cannot and is not expected to capture all potential risks
faced by a BHC, and therefore, it should serve as one
of several inputs to the capital planning process.
Given the scope of operations at and the associated
breadth of risks facing large, complex BHCs—including the risk of losses from exposures and of reduced
revenue generation—they are often exposed to risks,
other than credit or market risk, that are either difficult to quantify or not directly attributable to any of
the specific integrated firm-wide scenarios that are
evaluated as part of the BHC’s scenario-based stress
testing (“other risks”). Examples of these other risks
include reputational risk, strategic risk, and compliance risk. As noted in the section on risk identification, a BHC should identify and assess all risks as
part of its risk-identification process and should capture the potential effect of all risks in its capital planning process. A BHC’s capital planning process
should assess the potential impact of these other
risks on the BHC’s capital position to ensure that its
capital provides a sufficient buffer against all risks to
which the BHC is exposed.
There is a wide range of practices around how BHCs
account for other risks as part of their capital planning process. Many BHCs used internal capital targets to account for such risks, putting in place an
incremental cushion above their targets to allow for
difficult-to-quantify risks and the inherent uncertainty
represented by any forward-looking capital planning
process. Other BHCs assessed the effect of in terms
of some combination of reduced revenue, added
expenses, or a management overlay on top of loss
estimates. BHCs with lagging practices did not even
attempt to account for other risks in their capital
planning process.
To the extent possible, BHCs should incorporate the
effect of these other risks into their projections of net
income over the nine-quarter planning horizon. BHCs
should clearly articulate and support any relevant
assumptions and the methods used to quantify the
effect of other risks on their revenue, expenses, or
For those BHCs that did not incorporate the potential
impact of these other risks into their capital targets,
stronger practices included a clear articulation of
which risks were being addressed by putting in place
a cushion above the capital target, and how this
cushion is related to identified risks. BHCs should
clearly support the method they used to measure the
potential effect of such risks. Using a simple rule
(such as a percent of capital) or expert judgments to
determine the cushion above the capital target, without providing analysis or support, is a lagging practice.


Internal Controls

As with other aspects of key risk-management and
finance area functions, a BHC should have a strong
internal control framework that helps govern its
internal capital planning processes. These controls
should include (1) regular and comprehensive review
by internal audit; (2) robust and independent model
review and validation practices; (3) comprehensive
documentation, including policies and procedures;
and (4) change controls.

Scope of Internal Controls
A BHC’s internal control framework should address
its entire capital planning process, including the risk
measurement and management systems used to produce input data, the models and other techniques
used to generate loss and revenue estimates; the
aggregation and reporting framework used to produce reports to management and boards; and the
process for making capital adequacy decisions. While
some BHCs may naturally develop components of
their internal capital planning along separate business
lines, the control framework should ensure that BHC
management reconciles the separate components in a
coherent manner. The control framework also should
help assure that all aspects of the capital planning
process are functioning as intended in support of
robust assessments of capital needs.
BHCs with stronger control coverage reviewed the
controls around capital planning on an integrated
basis and applied them consistently. Management
responded quickly and effectively to issues identified
by control areas and devoted appropriate resources
to continually ensure that controls were functioning

not just of the individual components, periodically to
ensure that the entire end-to-end process is functioning in accordance with supervisory expectations and
with a BHC’s board of directors’ expectations as
detailed in approved policies and procedures. Internal
audit should review the manner in which deficiencies
are identified, tracked, and remediated. Audit staff
should have the appropriate competence and influence to identify and escalate key issues, and the internal audit function should report regularly on the status of all aspects of the capital planning process—including any identified deficiencies related to the
BHC’s capital plan—to senior management and the
board of directors.
BHCs with stronger audit practices provided a comprehensive, robust review of all components of the
capital planning process, including all of the control
elements noted earlier.10 BHCs with leading internal
audit practices around internal capital planning had
strong issue identification and remediation tracking
as well. They also ensured that audit staff had strong
technical expertise, elevated stature in the organization, and proper independence from management.11

Independent Model Review
and Validation
BHCs should conduct independent review and validation of all models used in internal capital planning,
consistent with existing supervisory guidance on
model risk management (SR Letter 11-7).12 Validation staff should have the necessary technical compe10

Internal Audit
Internal audit should play a key role in evaluating
internal capital planning and its various components.
Audit should perform a review of the full process,


See 12 CFR 225.8(d)(1)(iii).
See SR Letter 13-1, “Supplemental Policy Statement on the
Internal Audit Function and Its Outsourcing,” (January 23,
for detailed guidance on expectations for the governance and
operational effectiveness of an institution’s internal audit
See SR Letter 11-7, “Supervisory Guidance on Model Risk
Management,” (April 4, 2011),


Capital Planning at Large Bank Holding Companies

addressing any models that had not been validated
(or those that had identified weaknesses) by
restricting their use, or using benchmark or challenger models to help assess the reasonableness of
the primary model output.

tencies, sufficient stature within the organization, and
appropriate independence from model developers
and business areas, so that they can provide a critical
and unbiased evaluation of the models they review.
The model review and validation process should
• an evaluation of conceptual soundness;
• ongoing monitoring that includes verification of
processes and benchmarking; and
• an “outcomes analysis.”
BHCs should maintain an inventory of all models
used in the capital planning process, including all
input or “feeder” models that produce projections or
estimates used by the models that generate the final
loss, revenue or expense projections. Consideration
should be given to the validity of the use of a model
under stressed conditions as models designed for
ongoing business activities may be inappropriate for
estimating net income and capital under stress conditions. BHCs should also maintain a process to incorporate well-supported adjustments to model estimates when model weaknesses and uncertainties are
BHCs continue to face challenges in conducting outcomes analysis of their stress testing models, given
limited realized outcomes against which to assess
loss, revenue, or expense projections under stressful
scenarios. BHCs should attempt to compensate for
the challenges inherent in back-testing stress models
by conducting sensitivity analysis or by using benchmark or “challenger” models. BHCs should ensure
that validation covers all models and assumptions
used for capital planning purposes, including any
adjustments management has made to the model
estimates (management overlay).
Supervisory reviews have found that, in general,
BHCs should give more attention to model risk management, including strengthening practices around
model review and validation. Nonetheless, some
BHCs exhibited stronger practices in their capital
planning, including
• maintaining an updated inventory of all models
used in the process;
• ensuring that models had been validated for their
intended use; and
• being transparent about the validation status of all
models used for capital planning and appropriately

BHCs with lagging practices were not able to identify
all models used in the capital planning process. They
also did not formally review all of the models or
assumptions used for capital planning purposes
(including some high-impact stress testing models).
In addition, they did not have validation staff that
were independent and that could critically evaluate
the models.

Policies and Procedures
BHCs should ensure they have policies and procedures covering the entire capital planning process.13
Policies and procedures should ensure a consistent
and repeatable process for all components of the
capital planning process and provide transparency to
third parties regarding this process. Policies should be
reviewed and updated at least annually and more frequently when warranted. There should also be evidence that management and staff are adhering to
policies and procedures in practice, and there should
be a formal process for any policy exceptions. Such
exceptions should be rare and approved by the
appropriate level of management.

Ensuring Integrity of Results
BHCs should have internal controls that ensure the
integrity of reported results and the documentation,
review, and approval of all material changes to the
capital planning process and its components. A BHC
should ensure that such controls exist at all levels of
the capital planning process. Specific controls should
be in place to
• ensure that MIS are sufficiently robust to support
capital analysis and decisionmaking, with sufficient
flexibility to run ad hoc analysis as needed;
• provide for reconciliation and data integrity processes for all key reports;
• address the presentation of aggregate, enterprisewide capital planning results, which should
describe any manual adjustments made in the

See FR Y-14A reporting form: Summary Schedule Instructions,
pp. 5–7.

August 2013

aggregation process and how those adjustments
compensate for identified weaknesses; and
• ensure that reports provided to senior management
and the board contain the appropriate level of
detail and are accurate and timely. The party
responsible for this reporting should assess and
report whether the BHC is in compliance with its
internal capital goals and targets, and ensure the
rationale for any deviations from stated capital
objectives is clearly documented and obtain any
necessary approvals.14
BHCs with stronger practices in this area ensured
that good information flows existed to support decisions, with significant investment in controls for data
and information. For example, some BHCs had an
internal audit group review the data for accuracy and
ensured that any data reported to the board and
senior management were given extra scrutiny and
cross-checking. In addition, BHCs with stronger
practices had strong MIS in place that enabled them
to collect, synthesize, analyze, and deliver informa-

tion quickly and efficiently. These systems also had
the ability to run ad hoc analysis to support capital
planning as needed without employing substantial
resources. Other BHCs, however, continue to face
challenges with MIS. Many BHCs have systems that
are antiquated and/or siloed and not fully compatible, requiring substantial human intervention to reconcile across systems.

BHCs should have clear and comprehensive documentation for all aspects of their capital planning
processes, including their risk-measurement and riskmanagement infrastructure, loss- and resourceestimation methodologies, the process for making
capital decisions, and efficacy of control and governance functions.15 Documentation should contain
sufficient detail, accurately describe BHCs’ practices,
allow for review and challenge, and provide relevant
information to decisionmakers.16


See id.



See id.
See id.



BHCs should have strong board and senior management oversight of their capital planning processes.17
This includes ensuring periodic review of the BHC’s
risk infrastructure and loss- and resource-estimation
methodologies; evaluation of capital goals and targets; assessment of the appropriateness of stress scenarios considered; regular review of any limitations
in key processes supporting internal capital planning,
such as uncertainty around estimates; and approval
of capital decisions. Together, a BHC’s board and
senior management should establish a comprehensive
capital planning process that fits into broader riskmanagement processes and that is consistent with the
risk-appetite framework and the strategic direction of
the BHC.

Board of Directors
A BHC’s board of directors has ultimate oversight
responsibility and accountability for capital planning
and should be in a position to make informed decisions on capital adequacy and capital actions, including capital distributions.18 The board of directors
should receive sufficient information to understand
the BHC’s material risks and exposures and to
inform and support its decisions on capital adequacy
and planning. The board should receive this information at least quarterly, or when there are material
developments that affect capital adequacy or the
manner in which it is assessed. Capital adequacy
information provided to the board should include
capital measures under current conditions as well as
on a post-stress, pro forma basis and should be
framed against the capital goals and targets established by the BHC.
The information provided to the board should
include sufficient details on scenarios used for the
BHC’s internal capital planning so that the board can
evaluate the appropriateness of the scenarios, given

See 12 CFR 225.8(d)(1)(iii)(A)–(B).
See 12 CFR 225.8(d)(1)(iii)(C).

the current economic outlook and the BHC’s current
risk profile, business activities, and strategic direction. The information should also include a discussion of key limitations, assumptions, and uncertainties within the capital planning process, so that the
board is fully informed of any weaknesses in the process and can effectively challenge reported results
before making capital decisions. The board should
also receive summary information about mitigation
strategies to address key limitations and take action
when weaknesses in internal capital planning are
identified, applying additional caution and conservatism as needed.
BHCs with stronger practices had boards that were
informed of and generally understood the risks,
exposures, activities, and vulnerabilities that affected
the BHC’s capital adequacy. They also understood
the major drivers of loss and revenue changes under
the scenarios used. The boards of BHCs with
stronger practices had sufficient expertise and level of
engagement to understand and critically evaluate
information provided by senior management. Importantly, they recognized that internal capital planning
results are estimates and should be viewed as part of
a range of possible results. In addition, the boards of
BHCs with stronger practices discussed weaknesses
identified in the capital planning process, whether
they needed to take immediate action to address
those weaknesses, and whether the weaknesses were
material enough to alter their view of current capital
planning results. They also discussed whether a sufficient range of potential stress events and conditions
had been considered in assessing capital adequacy.

Board Reporting
The board of directors is required to approve a
BHC’s capital plan under the Capital Plan Rule.19 In
order for boards to carry out this requirement, management should provide adequate reporting on key



Capital Planning at Large Bank Holding Companies

areas of the analysis supporting capital plans. BHCs
with stronger practices included information about
the independent review and validation of models,
information on issues identified by internal audit, as
well as key assumptions underpinning stress test
results and a discussion of the sensitivity of capital
levels to those assumptions. BHCs with stronger
practices also supplied their boards with information
about past capital planning performance to provide a
perspective on how the capital planning process has
functioned over time.
BHCs with weaker practices provided insufficient
information to the board of directors. For example,
at some BHCs, capital distribution recommendations
did not include all relevant supporting information
and appeared to be based on optimistic expectations
about how a given scenario may affect the BHC. In
addition, the information did not specifically identify
and address key assumptions that supported the
capital planning process. In other cases, the board of
directors did not receive information about governance and controls over internal capital planning,
making it difficult to assess the strength of its capital
planning processes and whether results were reliable
and credible.

Senior Management
Senior management is responsible for ensuring that
capital planning activities authorized by the board
are implemented in a satisfactory manner and is
accountable to the board for the effectiveness of
those activities. Senior management should ensure
that effective controls are in place around the capital
planning process—including ensuring that the BHC’s
stress scenarios are sufficiently severe and cover the
material risks and vulnerabilities facing the BHC.20
Senior management should make informed recommendations to the board of directors about the
BHC’s capital, including capital goals and distribution decisions. Senior management also should
ensure that proposed capital goals have sufficient
analytical support and fully reflect the expectations
of important stakeholders, including creditors, counterparties, investors, and supervisors. Senior management should identify weaknesses and potential limitations in the capital planning process and evaluate
them for materiality. In addition, it should develop
remediation plans for any weaknesses affecting the

reliability of internal capital planning results. Both
the specific identified limitations and the remediation
plans should be reported to the board.
Senior management with stronger practices recognized the imprecision and prevalence of uncertainty
in predicting future outcomes when reviewing information and results from enterprise-wide scenario
analysis. At BHCs with stronger practices, senior
management maintained an ongoing assessment of
all capital planning areas, identifying and clearly
documenting any weaknesses, assumptions, limitations, and uncertainties, and did not consider a onetime assessment of the capital planning process to be
sufficient. Furthermore, management developed clear
remediation plans with specific timelines for resolving identified weaknesses. In some cases, based on its
review of the full capital planning process, senior
management made more cautious or conservative
adjustments to the capital plan, such as recommending less aggressive capital actions. Management also
included key assumptions and process weaknesses in
reports and specifically pointed them out to the
board, in some cases providing analysis showing the
sensitivity of capital to alternative outcomes.

Documenting Decisions
BHCs should document decisions about capital
adequacy and capital actions taken by the board of
directors and senior management, and describe the
information used to reach those decisions.21 Final
decisions regarding capital planning of the board or
of a designated committee thereof should be
recorded and retained in accordance with the company’s policies and procedures.
BHCs with stronger documentation practices had
board minutes that described how decisions were
made and what information was used. Some documentation provided evidence that the board challenged results and recommendations, including
reviewing and assessing how senior management
challenged the same information. BHCs with weaker
documentation practices had board minutes that
were very brief and opaque, with little reference to
information used by the board to make its decisions.
Some BHCs did not formally document key


12 CFR 225.8(d)(2)(i)(A)–(D).

See FR Y-14A reporting form: Summary Schedule Instructions,
p. 6.


Capital Policy

As noted earlier, a capital policy is the principles and
guidelines used by a BHC for capital planning, capital issuance, and usage and distributions. A capital
policy should include internal capital goals; quantitative or qualitative guidelines for dividends and stock
repurchases; strategies for addressing potential capital shortfalls; and internal governance procedures
around capital policy principles and guidelines.22 The
capital policy, as a component of a capital plan, must
be approved by the BHC’s board of directors or a
designated committee of the board.23 It should be a
distinct, comprehensive written document that
addresses the major components of the BHC’s capital planning processes and links to and is supported
by other policies (risk-management, stress testing,
model governance, audit, and others). A capital
policy should provide details on how a BHC manages, monitors, and makes decisions regarding all
aspects of capital planning. The policy should also
address roles and responsibilities of decisionmakers,
process and data controls, and validation standards.
Finally, the capital policy should explicitly lay out
expectations for the information included in the
BHC’s capital plan.
A capital policy should describe targets for the level
and composition of capital and provide clarity about
the BHC’s objectives in managing its capital position.
The policy should explain how the BHC’s capital
planning practices align with the imperative of maintaining a strong capital position and being able to
continue to operate through periods of severe stress.
It should include quantitative metrics such as common stock dividend (and other) payout ratios as
maximums or targets for capital distributions. The
policy should include an explanation of how management concluded that these ratios are appropriate,
sustainable, and consistent with its capital objectives,
business model, and capital plan. It should also
specify the capital metrics that senior management
and the board use to make capital decisions. In addi22

12 CFR 225.8(c)(4).
See 12 CFR 225.8(d)(1)(iii)(C), 225.8(d)(2)(iii).

tion, a capital policy should include governance and
escalation protocols that are clear, credible, and
actionable in the event an actual or projected capital
ratio target is breached.
The policy should describe processes surrounding
how common stock dividend and repurchase decisions are made and how the BHC arrives at its
planned capital distribution amounts. Specifically, the
policy should discuss the following:
• the main factors and key metrics that influence the
size, timing, and form of capital distributions
• the analytical materials used in making capital distribution decisions (e.g., reports, earnings, stress
test results, and others)
• specific circumstances that would cause the BHC
to reduce or suspend a dividend or stock repurchase program
• factors the BHC would consider if contemplating
the replacement of common equity with other
forms of capital
• key roles and responsibilities, including the individuals or groups responsible for producing the
analytical material referenced above, reviewing the
analysis, making capital distribution recommendations, and making the ultimate decisions
BHCs should establish a minimum frequency (at
least annually) and other triggers for when its capital
policy is reevaluated and ensure that these triggers
remain relevant and current. The capital policy
should be reevaluated and revised as necessary to
address changes to organizational structure, governance structure, business strategy, capital goals, regulatory environment, risk appetite, and other factors
potentially affecting a BHC’s capital adequacy. BHCs
should develop a formal process for approvals,
change management, and documentation retention
relating to their capital policies.
Weak capital policies were typically characterized by
a limited scope. They only addressed parts of the


Capital Planning at Large Bank Holding Companies

capital planning process, did not provide sufficient
detail to convey clearly how capital action decisions
will be made, were not well integrated with or supported by other risk and finance policies, and/or did
not contain all of the elements described above (e.g.,
clearly defined capital goals, guidelines for capital distributions and capital composition, etc.). In some
cases, the capital policy was overly generic and not
tailored to the BHC’s unique circumstances. For
example, the policy appeared to be restating supervisory expectations without concrete examples or
BHC-specific considerations. In other cases, the more
detailed procedures were not presented to the board,
thus limiting the board’s ability to understand the
analysis underlying its capital planning decisions.

ability to raise additional capital, including the
potential impact of contingent exposures and
broader market or systemic events, which could cause
risk to increase beyond the BHC’s chosen risktolerance level. BHCs should have contingency plans
for such outcomes.

Capital Goals and Targets

Weak practices observed in this area included establishing capital goals based solely on regulatory minimums and the ratios required to be considered well{
capitalized without consideration of a BHC’s specific
capital needs given its risk profile, financial condition, business model and strategies, overall complexity, and sensitivity to changing conditions. Some
BHCs did not recognize uncertainties and limitations
in capturing all potential sources of loss and in projecting loss and revenue estimates, which reduced the
BHCs’ ability to establish effective capital goals and
targets. Other BHCs were not transparent about how
they determined the capital goals and targets in their
capital policies.

BHCs should establish capital goals aligned with
their risk appetites and risk profiles as well as expectations of internal and external stakeholders, providing specific goals for the level and composition of
capital, both current and under stressed conditions.
Internal capital goals should be sufficient to allow a
BHC to continue its operations during and after the
impact of stressful conditions. As such, capital goals
should reflect current and future regulatory capital
requirements, as well as the expectations of shareholders, rating agencies, counterparties, creditors,
supervisors, and other stakeholders.
BHCs should also establish capital targets above their
capital goals to ensure that capital levels will not fall
below the goals during periods of stress. Capital targets should take into consideration forward-looking
elements related to the economic outlook, the BHC’s
financial condition, the potential impact of stress
events, and the uncertainty inherent in the capital
planning process. The goals and targets should be
specified in the capital policy and reviewed and
approved by the board.24

Additionally, BHCs should calculate and use several
capital measures that represent both leverage and
risk, including quarterly estimates of regulatory capital ratios (including tier 1 common ratio) under both
baseline and stress conditions. BHCs with weaker
practices in this area did not clearly link decisions
regarding capital distributions to capital adequacy
metrics or internal capital goals.

Capital Contingency Plan

In developing their capital goals and targets, particularly with regard to setting the levels of capital distributions, BHCs should explicitly take into account
general economic conditions and their plans to grow
their on{ and off{balance{sheet size and risks organically or through acquisitions. BHCs should consider
the impact of external conditions during both normal
and stressed economic and market environments and
other factors on their overall capital adequacy and

BHCs should outline in their capital policies specific
capital contingency actions they would consider to
remedy any current or prospective deficiencies in
their capital position.25 In particular, a BHC’s policy
should include a detailed explanation of the circumstances—including deterioration in the economic
environment, market conditions, or the financial condition of the BHC—in which it will reduce or suspend a dividend or repurchase program or not
execute a previously planned capital action. The
policy also should define a set of capital triggers and
events that would correspond with these circumstances. These triggers should be established for both
baseline and stress scenarios and measured against
the BHC’s capital targets in those scenarios. These
triggers and events should be used to guide the frequency with which board and senior management
will revisit planned capital actions as well as review



12 CFR 225.8(c)(4).


August 2013

and act on contingency capital plans. The capital
contingency plan should be reviewed and updated as
conditions warrant, such as where there are material
changes to the BHC’s organizational structure or
strategic direction or to capital structure, credit quality, and/or market access.
Capital triggers should provide an “early warning” of
capital deterioration and should be part of a management decisionmaking framework, which should
include target ranges for a normal operating environment and threshold levels that trigger management
action. Such action should include escalation to the
board, potential suspension of capital actions, and/or
activation of a capital contingency plan. Triggers
should also be established for other metrics and
events that measure or affect the financial condition
or perceived financial condition of the firm—for
example, liquidity, earnings, debt and credit default
swap spreads, ratings downgrades, stock performance, supervisory actions, or general market stress.
Contingency actions should be flexible enough to
work in a variety of situations and be realistic for
what is achievable during periods of stress. The capital plan should be prepared recognizing that certain
capital-raising and capital-preserving activities may


not be feasible or effective during periods of stress.
BHCs should have an understanding of market
capacity constraints when evaluating potential capital
actions that require accessing capital markets, including debt or equity issuance and also contemplated
asset sales. Contingency actions should be ranked
according to ease of execution and their impact and
should incorporate the assessment of stakeholder
reactions (e.g., impacts on future capital-raising
Weak capital contingency plans provided few options
to address contingency situations and/or did not consider the feasibility of options under stressful conditions. Plans with overly optimistic assumptions or
excessive reliance on past history (in terms of both
possible contingency situations and options to
address those situations) were also considered weak,
as were plans that lacked support for the feasibility
and availability of possible contingency actions.
Other weak practices included establishing triggers
based on actual results but not on projected results,
or based on minimum regulatory capital ratios only
with no consideration of the expectations of other
stakeholders including counterparties, creditors and
investors, or of other metrics or market indicators.


BHC Scenario Design

Under the Capital Plan Rule, a BHC is required to
use a BHC-developed stressed scenario that is appropriate for its business model and portfolios.26
Accordingly, BHCs should have a process for designing scenarios for enterprise-wide scenario analysis
that reflects the BHC’s unique business activities and
associated vulnerabilities.
The range of observed practice for developing BHC
stress scenarios was broad. Some BHCs designed
stress scenarios using internal models and expertise.
Other BHCs used vendor-defined macroeconomic
scenarios or used vendor models to define customized macroeconomic scenarios. For BHCs with internally developed scenarios, those with stronger
scenario-design practices used internal models in
combination with expert judgment rather than relying solely on either models or expert judgment to
define scenario conditions and variables. Among
BHCs that used third-party scenarios, those with
stronger practices tailored third-party-defined scenarios to their own risk profiles and unique
Regardless of the method used to develop the scenario, BHCs should have a scenario-selection process
that engages a broad range of internal stakeholders
such as risk experts, business managers, and senior
management. Although they are required to submit
only one BHC stress scenario for CCAR, BHCs
should develop a suite of scenarios that collectively
capture their material risks and vulnerabilities under
a variety of stressful circumstances and should incorporate them into their overall capital planning

unique vulnerabilities to factors that affect its firmwide activities and risk exposures, including macroeconomic, market-wide, and firm-specific events.”27
Thus, BHC stress scenarios should reflect macroeconomic and financial conditions that are tailored specifically to stress a BHC’s key vulnerabilities and
idiosyncratic risks, based on factors such as its particular business model, mix of assets and liabilities,
geographic footprint, portfolio characteristics, and
revenue drivers. A BHC stress scenario that simply
features a generic weakening of macroeconomic conditions similar in magnitude to the supervisory
severely adverse scenario does not meet these
BHCs with stronger scenario-design practices clearly
and creatively tailored their BHC stress scenarios to
their unique business-model features, emphasizing
important sources of risk not captured in the supervisory severely adverse scenario. Examples of such
risks observed in practice included a significant
counterparty default; a natural disaster or other
operational-risk event; and a more acute stress on a
particular region, industry, and/or asset class as compared to the stress applied to general macroeconomic
conditions in the supervisory adverse and severely
adverse scenarios.

Scenario Design and Severity

At the same time, BHC stress scenarios should not
feature assumptions that specifically benefit the
BHC. For example, some BHCs with weaker
scenario-design practices assumed that they would be
viewed as strong compared to their competitors in a
stress scenario and would therefore experience
increased market share. Such assumptions are contrary to the supervisory expectations for and the
intent of a stress testing exercise that informs capital

As indicated in the preamble to the Capital Plan
Rule, “the bank holding company-designed stress
scenario should reflect an individual company’s

While a broad-based recession adversely affects a
wide range of most BHCs’ business activities, BHCs
may have business models or important business



12 CFR 225.8(d)(2)(i)(A).

See 77 Fed. Reg. 74631, 74636 (December 1, 2011).


Capital Planning at Large Bank Holding Companies

activities that generate vulnerabilities that are not
particularly well captured by scenario analysis based
on a stressed macroeconomic environment (or for
which even a severe recession is not the primary
source of potential vulnerability). These BHCs
should incorporate into their stress scenarios elements that address the key revenue vulnerabilities
and sources of loss for their specific businesses and
activities. In combination, the recession incorporated
into the BHC stress scenario and any additional elements intended to address specific businesses or
activities should result in a substantial stress for the
organization, including a significant reduction in
capital ratios relative to baseline projections. However, a BHC stress scenario that produces post-stress
capital ratios lower than those under the supervisory
severely adverse scenario is not, in and of itself, a safe
harbor. The stress scenario included in a BHC’s capital plan should place substantial strains on its ability
to generate revenue and absorb losses, consistent with
its unique risks and vulnerabilities.

Variable Coverage
The set of variables that a BHC includes in its stress
scenario should be sufficient to address all material
risks arising from its exposures and business activities. A business line could face significant stress from
multiple sources, requiring more than one risk factor
or macroeconomic variable. The scenario should generally contain the relevant variables to facilitate pro
forma financial projections that capture the impact
of changing conditions and environments. BHCs
should have a consistent process for determining the
final set of variables and provide this rationale as
part of the scenario narrative.

Overall, BHCs with stronger scenario-design practices generated scenarios in which the link between
the variables included in the scenario and sources of
risk to the BHC’s financial outlook were transparent
and straightforward. Clear narratives helped make
these links more transparent. BHCs with weaker
scenario-design practices developed stress scenarios
that excluded some variables relevant to the BHC’s
risk profile and idiosyncratic vulnerabilities. For
example, some BHCs with significant trading activities and revenues included a limited set of relevant
financial variables. Other BHCs with significant
regional and/or industry concentrations did not
include relevant geographic or industry variables.

Clear Narratives
The scenario should be supported by a clear narrative describing how the scenario addresses the particular vulnerabilities and material risks facing the
BHC. BHCs with stronger scenario-design practices
provided narratives describing how the scenario variables related to the risks faced by a BHC’s significant
business lines and, in some cases, how the scenario
variables corresponded to variables in the BHC’s
internal risk-management models. The narratives also
provided explanations of how a scenario stressed a
BHC’s unique vulnerabilities specific to its business
model and how the paths of the scenario variables
related to each other in an economically intuitive
way. Weaker practices included scenario narratives
that did not provide any context for the variable
paths as well as scenario narratives that described
features that were not reflected in any variables considered in a BHC’s internal capital planning.


Estimation Methodologies for Losses,
Revenues, and Expenses

A BHC’s capital plan must include estimates of projected revenues, expenses, losses, reserves, and pro
forma capital levels, including any minimum regulatory capital ratios, the tier 1 common ratio and any
additional capital measures deemed relevant by the
BHC, over the planning horizon under expected conditions and under a range of stressed scenarios.28

General Expectations
Projections of losses, revenues, and expenses under
hypothetical stressed conditions serve as the fundamental building blocks of the pro forma financial
analysis supporting enterprise-wide scenario analysis.
BHCs should have stress testing methodologies that
generate credible estimates that are consistent with
assumed scenario conditions. It is important for
BHCs to understand the uncertainties around their
estimates, including the sensitivity of the estimates to
changes in inputs and key assumptions. Overall,
BHCs’ estimates of losses, revenues, and expenses
under each of the scenarios should be supported by
empirical evidence, and the entire estimation process
should be transparent and repeatable. The Federal
Reserve generally expects BHCs to use models or
other quantitative methods as the basis for their estimates; however, there may be instances where a management overlay or other qualitative approaches may
be appropriate due to data limitations, new products
or businesses, or other factors. In such instances,
BHCs should ensure that such processes are well supported, transparent, and repeatable over time.

Establishing a Quantitative Basis for
Enterprise-Wide Scenario Analysis
Generally, BHCs should develop and use internal
data to estimate losses, revenues, and expenses as part
of enterprise-wide scenario analysis.29 However, in

12 CFR 225.8(d)(1).
BHCs are required to collect and report a substantial amount of
risk information to the Federal Reserve on FR Y-14 schedules.

certain instances, it may be more appropriate for
BHCs to use external data to make their models more
robust. For example, BHCs may lack sufficient, relevant historical data due to factors such as systems
limitations, acquisitions, or new products. When
using external data, BHCs should take care to ensure
that the external data reasonably approximate underlying risk characteristics of their portfolios, and make
adjustments to modeled outputs to account for identified differences in risk characteristics and performance reflected in internal and external data.
BHCs can use a range of quantitative approaches to
estimate losses, revenues, and expenses, depending on
the type of portfolio or activity for which the
approach is used, the granularity and length of available time series of data, and the materiality of a
given portfolio or activity. While the Federal Reserve
does not require BHCs to use a specific estimation
method, each BHC should estimate its losses, revenues, and expenses at sufficient granularity so that it
can identify common, key risk drivers and capture
the effect of changing conditions and environments.
For example, loss models should be estimated at a
sufficiently granular subportfolio or segment level so
that they can capture observed variations in risk
characteristics and performance across the subportfolios or segments and across time, and account for
changing exposure or portfolio characteristics over
the planning horizon.
While BHCs often segment their portfolios and
activities along functional areas, such as by line of
business or product type, the leading practice is to
determine segments based on common risk characteristics (e.g., credit score ranges or loan-to-value
ratio ranges) that exhibit meaningful differences in
historical performance. The granularity of segments
typically depends on the type, size, and composition
of the BHC’s portfolio. For example, a more diverse
portfolio—both in terms of borrower risk characterThese data may help to support the BHCs’ enterprise-wide scenario analysis.


Capital Planning at Large Bank Holding Companies

istics and performance—would generally require a
greater number of segments to account for the heterogeneity of the portfolio. However, when segmenting portfolios, it is important to ensure that each risk
segment has sufficient data observations to produce
reliable model estimates.
As a general practice, BHCs should separately estimate losses, revenues, or expenses for portfolios or
business lines that are sensitive to different risk drivers or sensitive to risk drivers in a markedly different
way. For instance, losses on commercial and industrial loans and commercial real estate (CRE) loans
are, in part, driven by different factors, with the path
of property values having a more pronounced effect
on CRE loan losses. Similarly, although falling property value affects both income-producing CRE loans
and construction loans, the effect often differs materially due to structural differences between the two
portfolios. Such differences can become more pronounced during periods of stress. BHCs with leading
practices have demonstrated clearly the rationale for
selecting certain risk drivers over others. BHCs with
lagging practices used risk drivers that did not have a
clear link to results, either statistically or
Many models used for stress testing require a significant number of assumptions to implement. Further,
the relationship between macroeconomic variables
and losses, revenues, or expenses could differ considerably in the hypothetical stress scenario from what is
observed historically. As a result, while traditional
tools for evaluating model performance (such as
comparing projections to historical out-of-sample
outcomes) are still useful, the Federal Reserve expects
BHCs to supplement them with other types of analysis. Sensitivity analysis is one tool that some BHCs
have used to test the robustness of models and to
help model developers, BHC management, the board
of directors, and supervisors identify the assumptions and parameters that materially affect outcomes.
Sensitivity analysis can also help ensure that core
assumptions are clearly linked to outcomes. Using
results from different estimation approaches (challenger models) as a benchmark is another way BHCs
can gain greater comfort around their primary model
estimates, as the strengths of one approach could
potentially compensate for the weaknesses of
another. When using multiple approaches, however, it
is important that BHCs have a consistent framework
for evaluating the results of different approaches and
supporting rationale for why they chose the methods
and estimates they ultimately used.

In certain instances, BHCs may need to rely on thirdparty models—for example, due to limitations in
internal modeling capacity. In using these third-party
models (vendor models or consultant-developed
models), BHCs should ensure that their internal staff
have working knowledge and a good conceptual
understanding of the design and functioning of the
models and potential model limitations so that management can clearly communicate them to those governing the process. An off-the-shelf vendor model
often requires some level of firm-specific analysis and
customization to demonstrate that it produces estimates appropriate for the BHC and consistent with
scenario conditions. Sensitivity analysis can be particularly helpful in understanding the range of possible results of vendor models with less transparent
or proprietary elements. Importantly, all vendor and
consultant-developed models should be validated in
accordance with SR 11-7 guidelines.30
Some BHCs generated annual projections for certain
loss, revenue, or expense items and then evenly distributed them over the four quarters of each year.
This practice does not reflect a careful estimate of
the expected quarterly path of losses, net revenue,
and capital, and thus is only acceptable when a BHC
can clearly demonstrate that the projected item is
highly uncertain and the practice likely results in a
conservative estimate.

Qualitative Projections, Expert Judgment,
and Adjustments
While quantitative approaches are important elements of enterprise-wide scenario analysis, BHCs
should not rely on weak or poorly specified models
simply to have a modeled approach. In fact, most
BHCs use some forms of expert judgment for some
purposes—generally as a management adjustment
overlay to modeled outputs. And BHCs can, in limited cases, use expert judgment as the primary
method to produce an estimate of losses, revenue, or
expenses. BHCs may use a management overlay to
account for the unique risks of certain portfolios that
are not well captured in their models, or otherwise to
compensate for specific model and data limitations.
Material changes in BHCs’ businesses or limitations
in relevant data may lead some BHCs to rely wholly
on expert judgment for certain loss, revenue, or
expense projections. In using expert judgment, BHCs

See SR Letter 11-7, “Supervisory Guidance on Model Risk
Management,” (April 4, 2011),

August 2013

should ensure that they have a transparent and
repeatable process, that management judgments are
well supported, and that key assumptions are consistent with assumed scenario conditions.
As with quantitative methods, the assumptions and
processes that support qualitative approaches should
be clearly documented so that an external reviewer
can follow the logic and evaluate the reasonableness
of the outcomes.31 Any potential shortcomings
should be investigated and communicated to decisionmakers. In addition, any management overlay or
qualitatively derived projections should be subject to
effective review and challenge. BHCs should evaluate
a range of potential estimates and conduct sensitivity
analysis for key assumptions used in the estimation
process. For example, if a BHC makes extensive
adjustments to its modeled estimates of losses, revenue, and expenses, the impact of such adjustments
should be quantified relative to unadjusted estimates,
and these results should be documented and made
available to BHC management and the board of
directors. Finally, extensive use of management judgment to adjust modeled estimates should trigger
review and discussion as to whether new or improved
modeling approaches are needed. In reporting to the
board of directors, management should always provide both the initial results and the results after any
judgmental adjustments.


In the context of CCAR loss and revenue estimates,
BHCs should generally include all applicable loss
events in their analysis, unless a BHC no longer
engages in a line of business or its activities have
changed such that the BHC is no longer exposed to a
particular risk. BHCs should not selectively exclude
losses based on arguments that the nature of the
ongoing business or activity has changed—for
example, because certain loans were underwritten to
standards that no longer apply or were acquired and,
therefore, differ from those that would have been
originated by the acquiring institution.
Similarly, BHCs should not rely on favorable
assumptions that cannot be reasonably assured to
occur in stressed environments given the high level of
uncertainty around market conditions. BHCs should
also not assume any foresight of scenario conditions
over the projection horizon beyond what would reasonably be knowable in real-life situations. For
example, some BHCs have used the path of stress
scenario variables to make optimistic assumptions
about possible management actions ex ante in anticipation of stressful conditions, such as preemptively
rebalancing their portfolios or otherwise adjusting
their risk profiles to mitigate the expected impact. In
the event of a downturn, the future path or progression of economic and market conditions would not
be clearly known, and this uncertainty should be
reflected in the capital plans.

Conservatism and Credibility
Documentation of Estimation Practices
Given the uncertainty inherent in a forward-looking
capital planning exercise, the Federal Reserve expects
BHCs to apply generally conservative assumptions
throughout the stress testing process to ensure appropriate tests of the BHCs’ resilience to stressful conditions. In particular, BHCs should ensure that models
are developed using data that contain sufficiently
adverse outcomes. If a BHC experienced better-thanaverage performance during previous periods of
stress, it should not assume that those prior patterns
will remain unchanged in the stress scenario. BHCs
should carefully review the applicability of key
assumptions and critically assess how historically
observed patterns may change in unfavorable ways
during a period of severe stress for the economy, the
financial markets, and the BHC.

The Federal Reserve expects BHCs to clearly document their key methodologies and assumptions used
to estimate losses, revenues, and expenses.32 BHCs
with stronger practices provided documentation that
concisely explained methodologies, with relevant
macroeconomic or other risk drivers, and demonstrated relationships between these drivers and estimates. Documentation should clearly delineate
among model outputs, qualitative overlays to model
outputs, and purely qualitative estimates.33 BHCs
with weaker practices often had limited documentation that was poorly organized and that relied heavily
on subjective management judgment for key model
inputs with limited empirical support for and documentation of these adjustments.



See FR Y-14A reporting form: Summary Schedule Instructions,
pp. 5–6.


See id.
See id.


Capital Planning at Large Bank Holding Companies

Loss-Estimation Methodologies
As noted earlier, a BHC’s internal stress testing processes should be designed to capture risks inherent in
its own exposures and business activities. Consistent
with any good modeling practices, when developing
loss-estimation methodologies, BHCs should first
determine whether there is a sound theoretical basis
for macroeconomic and other explanatory variables
(risk drivers) used to estimate losses, and then empirically demonstrate that a strong relationship exists
between those variables and losses. For example,
most BHCs’ residential-mortgage loss models used
some measure of unemployment and a house price
index as explanatory variables, which affect a borrower’s ability and incentive to repay.
Beyond the core set of macroeconomic variables that
typically represents a given scenario, such as gross
domestic products (GDP), unemployment rate,
Treasury yields, credit spreads, and various price
indices, BHCs often project additional variables that
have a more direct link to particular portfolios or
exposures. Some examples of these variables include
regional macroeconomic variables that better capture
the BHC’s geographic exposures and sector-specific
variables, such as office vacancy rates and corporate
profits. Using these additional variables to estimate
the model can enhance the sensitivity of loss estimates to a given scenario and also improve the overall fit of the model. Any models used to produce
additional risk drivers are key components of the
loss-estimation process and, therefore, should be
included in BHCs’ model inventories and receive the
same model risk-management treatment as core lossestimation models.
Generally, BHCs sum up losses from various portfolios and activities to produce aggregate losses for the
enterprise-wide scenario analysis. BHCs should have
a repeatable process to aggregate losses, particularly
when they transform model estimates to combine disparate risk measures (such as accounting-based and
economic loss concepts), different measurement horizons, or otherwise dissimilar loss estimates.
BHCs with leading practices used automated processes that showed a clear audit trail from source
data to loss estimation and aggregation, with full reconcilement to source systems and regulatory reports
and mechanisms requiring approval and logging of
judgmental adjustments and overrides. These systems
often leveraged existing enterprise-wide financial and
regulatory consolidation processes.

BHCs with lagging practices exhibited a high degree
of manual intervention in the aggregation process,
and applied aggregate-level management adjustments
that were not transparent or well supported.

Retail and Wholesale Credit Risk
BHCs used a range of approaches to produce loss
estimates on loans to retail and corporate customers,
often using different estimation methods for different
portfolios. This section describes the observed range
of practice for the methods used to project losses on
retail and wholesale loan portfolios.
Data and Segmentation
Sources of data used for loss estimation have often
differed between retail and wholesale portfolios. Due
to availability of a richer set of retail loss data, particularly from the most recent downturn, BHCs generally used internal data to estimate defaults or losses
on retail portfolios and only infrequently used external data with longer history to benchmark estimated
losses on portfolios that had more limited loss experience in the recent downturn. For wholesale portfolios, some BHCs supplemented internal data with
external data or used external data to calibrate their
models due to a short time series (5–10 years) that
included only a single downturn cycle.
BHCs with stronger practices accounted for dynamic
changes in their portfolios, such as loan modifications or changes in portfolio risk characteristics, and
made appropriate adjustments to data or estimates to
compensate for known data limitations (including
lack of historical periods of stress).
BHCs with weaker practices failed to compensate for
data limitations or adequately demonstrate that
external data reasonably reflect the BHC’s actual
exposures, often failing to capture geographic, industry, or lending-type concentrations.
The level of segmentation used for modeling varied
depending on the type and size of portfolio and estimation methods used. For example, BHCs often segmented the retail portfolio based on some combinations of product; lien position; risk characteristics
such as credit score, loan-to-value ratio, and collateral; and underlying collateral information (e.g.,
single-family home versus condominium), though
some models were estimated at the loan-level and
others at the portfolio level.

August 2013

BHCs with stronger practices had segmentation
schemes that were well supported by the BHC’s data
and analysis, with sufficient granularity to capture
exposures that react differently to risk drivers under
stressed conditions.
BHCs with weaker practices used a single model for
multiple portfolios, without sufficiently adjusting
modeling assumptions to capture the unique risk
drivers of each portfolio. For example, in estimating
losses on wholesale portfolios, these BHCs did not
adequately allow for variation in loss rates commonly
attributed to industry, obligor type, collateral, lien
position, or other relevant information.
Common Credit Loan Loss-Estimation
BHCs have used a wide range of methods to estimate
credit losses, depending on the type and size of portfolios and data availability. These methods can be
based on either an accounting-based loss approach
(that is, charge-off and recovery) or an economic loss
approach (that is, expected losses). BHCs have flexibility in selecting a specific loss or estimation
approach; however, it is important for BHCs to
understand differences between the two loss
approaches, particularly in terms of the timing of
loss recognition, and to account for the differences in
setting the appropriate level of reserves at the end of
each quarter.
Expected Loss Approaches

Under the expected loss approach, losses are estimated as a function of three components—probability of default (PD), loss given default (LGD), and
exposure at default (EAD). PD, LGD, and EAD can
be estimated at a segment level or at an individual
loan level, and using different models or assumptions. In general, BHCs used econometric models to
estimate losses under a given scenario, where the estimated PDs were conditioned on the macroeconomic
environment and portfolio or loan characteristics.
Some BHCs used other approaches, such as rating
transition models, to estimate stressed default rates as
part of an expected loss framework.
BHCs with leading practices were able to break down
losses into PD, LGD, and EAD components, separately identifying key risk drivers for each of those
components, though they typically did not demonstrate this level of granularity consistently across all
portfolios. For certain wholesale portfolios, some


BHCs used long-run average PD, LGD, and EAD for
a particular segment, such as a rating grade, to estimate losses. By design, estimates based on long-run
average behavior over a mix of conditions, including
periods of economic expansion and downturn, are
not appropriate for projecting losses under stress and
should not be used for these purposes.
BHCs with leading practices clearly tied LGD to
underlying risk drivers, accounted for collateral and
guarantees, and also incorporated the likelihood of a
decline in collateral values under stress. However,
most BHCs have more limited data on LGD and, as
a result, BHCs often applied a simple, conservative
assumption (e.g., 100 percent LGD for credit cards),
based stressed LGD on their experience during the
crisis, or scaled up the historical average LGD using
expert judgment. In using such methods, it is important for BHCs to ensure that the process is well supported and transparent in line with the Federal
Reserve’s general expectation for expert judgmentbased estimates. Wherever possible, BHCs should
benchmark their estimates with external data or
research and analysis.
BHCs with lagging practices modeled LGD using a
weighted-average approach at an aggregate portfolio
level, without some level of segmentation (e.g., by
lending product, priority of claim, collateral type,
geography, vintage, or LTV). Or, they failed to demonstrate that LGD estimates were consistent with the
severity of the scenario.
Although some BHCs found a relationship between
EAD and credit quality, most BHCs did not model
EADs to vary according to the macroeconomic environment, in large part due to data limitations. Rather,
many BHCs applied a static assumption to estimate
stressed EAD.
BHCs with stronger practices included the use of
loan equivalent calculations (i.e., estimated additional
drawdowns as a percentage of unused commitments,
which are added to the outstanding or drawn balance) and credit-conversion factors (i.e., additional
drawdowns during the period leading up to default—
usually one year prior—as a percentage of both
drawn and undrawn commitments) to capture losses
associated with undrawn commitments.
BHCs with weaker practices did not project stressed
exposures associated with undrawn commitments
and/or relied on the assumption that they can


Capital Planning at Large Bank Holding Companies

actively manage down committed lines during stress
Rating Transition Models

Many BHCs have used a rating transition-based
approach to produce a stressed rating transition
matrix for each quarter, which is then used to estimate losses for their wholesale portfolios under stress.
These approaches used credit ratings applied to individual loans by the BHC and projected how these
ratings would change over time given the macroeconomic scenario. Although the details of techniques
used to link rating transitions to scenario conditions
varied across firms, the process usually involved the
following steps: (1) converting the rating transition
matrix into a single summary measure; (2) estimating
a time-series model linking the summary measure to
scenario variables; (3) projecting the summary measure over the nine-quarter planning horizon, using the
parameter estimates from the time-series model; and
(4) converting the projected summary measure into a
full set of quarterly transition matrices. BHCs using
such an approach should be able to demonstrate that
the summary measure responds to changes in economic conditions as expected (that is, worsens as the
economic condition deteriorates) and results in projected rating transition matrices that are consistent
with the severity of scenario. Judgmentally selecting
transition matrices from past stress periods is a weak
practice, as it may produce loss estimates that are not
consistent with a given scenario and fails to recognize
that conditions in the future may not precisely mirror
conditions observed by the BHC in the past.
Sound rating transition models require two fundamental building blocks: a robust time series of data
and well-calibrated, granular-risk rating systems. The
Federal Reserve expects BHCs that use rating transition models to have robust time series of data that
include a sufficient number of transitions, which
allows BHCs to establish a statistically significant
relationship between the transition behavior and
macroeconomic variables. Data availability has been
a widespread constraint inhibiting the development
of granular transition models because a sufficient
number of upgrades and downgrades are necessary
to preclude sparse matrices. In order to overcome
these data limitations, BHCs have often relied on
third-party data to develop rating transition models.
Consistent with the Federal Reserve’s general expectations, when using third-party data, BHCs should be

able to demonstrate that the transition matrices estimated with external data are a reasonable proxy for
the migration behavior of their portfolios. Rating
transition models also require granular ratings systems that capture differences in the potential for
defaults and losses for a given set of exposures in
various economic environments. BHCs that lack
well-calibrated, granular credit-risk rating systems
are often unable to produce useful transition
BHCs with stronger practices typically had more
granular ratings system and accounted for limitations
in their data and/or credit rating systems by making
adjustments to model assumptions or estimates, or
by supplementing internal data with external data.
BHCs with weaker practices often failed to demonstrate that supplemented external data adequately
reflected the ratings performance of the BHC’s portfolio. BHCs with weaker practices also sometimes
relied on a risk rating process that historically
resulted in lumpiness in rating upgrades and downgrades or material concentrations in one or two rating categories. As a result, these BHCs often produced transition matrices with limited sensitivity to
scenario variables, and resulting estimates were more
consistent with long-term average default rates than
with default rates that would be experienced under
severe economic stress.
Roll-Rate Models

Many BHCs have used roll-rate models to estimate
losses for various retail portfolios. Roll-rate models
generally estimate the rate at which loans that are
current or delinquent in a given quarter roll into
delinquent or default status in the next period. As a
result, they are conceptually similar to rating transition models. The Federal Reserve expects BHCs that
use roll-rate models to have a robust time series of
data with sufficient granularity. The robust time
series data allow the BHC to establish a strong relationship between roll rates and scenario variables,
while the availability of granular data enables BHCs
to model all relevant loan transitions and to segment
the portfolio into subportfolios that exhibit meaningful variations in performance, particularly during the
period of stress. In general, BHCs should estimate
roll rates using models that are conditioned on scenario variables. For certain transition states where
statistical relationships between roll rates and sce-

August 2013

narios are weak (such as late stage loan delinquency),
BHCs should incorporate conservative assumptions
rather than relying solely on statistical relationships.
While roll-rate models have some advantages, including transparency and ease of use, they often have a
weak predictive power outside the near future, particularly if they are not properly conditioned on scenario variables. As a result, some roll-rate models
have limited usefulness for stress testing over a longer
horizon, such as the nine-quarter planning horizon
required in CCAR. Some BHCs have used roll-rate
models in conjunction with other estimation
approaches (such as a vintage model described
below) that project losses for later periods. In general,
it is a weaker practice to combine two different models, as it can introduce unexpected jumps in estimated
losses over the planning horizon, though some BHCs
have judgmentally weighed two different estimation
methods to smooth projected losses. If BHCs combine two models, they should be able to demonstrate
that such an approach is empirically warranted based
on output analysis, including sensitivity analysis, and
that the process of transitioning from one set of
results to the other is consistent, well supported, and


average years, rather than during the period of stress.
In using vintage models, it is important for a BHC to
be able to demonstrate that the approach appropriately reflects its portfolio composition and history,
and that modeled outputs are consistent with stressed
Charge-Off Models

A minority of BHCs have used net charge-off (NCO)
models as either a primary loss-estimation model or a
benchmark model. Typically, the NCO models BHCs
used estimated a statistical relationship between
charge-off rates and macroeconomic variables at a
portfolio level, and often included autoregressive
terms (lagged NCO rates). While some BHCs also
incorporated variables that describe the underlying
risk characteristics of the portfolio, NCO models
that BHCs used for capital planning generally did not
capture variation in sensitivities to risk drivers across
important portfolio segments nor accounted for
changes in portfolio risk characteristics over time. As
a matter of general practice, BHCs should not use
models that do not capture changes in portfolio risk
characteristics over time and in scenarios used for
stress testing as part of their internal capital

Vintage Loss Models

Some BHCs use vintage loss models, also known as
age-cohort-time models, to estimate losses for certain
retail portfolios. BHCs that use vintage loss models
generally segment their retail portfolios by vintage
and collateral- or credit-quality-based segments.
Losses are estimated using a multistep process—developing a baseline seasoning curve for each segment
and using a regression model to estimate sensitivity
of losses to macroeconomic variables at each seasoning level (e.g., four quarters after origination). This
technique is commonly used in several vendor models, but BHCs also have developed and used proprietary models using this technique.
These models have several advantages (such as natural segmentation of portfolio by cohort and maturity) and ease of application to credit products (such
as auto loans) that exhibit lifecycle effects. However,
vintage models can be very challenging to construct,
calibrate, and validate. In particular, it may be difficult to separately identify vintage effects from the
effects of macroeconomic variables, which can result
in poorly specified models. These models also assume
that different cohorts will experience similar losses
over time, generating results that are representative of

NCO models often exhibit lower explanatory power
than models that consider distinct portfolio risk drivers. In addition, NCO models implicitly assume that
historical charge-off performance is a good predictor
of future performance; however, the historical relationship between charge-offs and macro variables
may not be realized under very stressful scenarios
that fall outside the portfolio’s actual historical experience. Accordingly, a NCO model that is estimated
without using sufficient segmentation or does not
account for current or changing portfolio composition is unlikely to produce robust loss estimates.
Thus, BHCs should avoid using such a NCO model
as the primary loss-estimation approach for a material portfolio.
Scalar Adjustments

Some BHCs have used simple scalars to adjust portfolio loss estimate under a baseline scenario upward
for stress scenarios. Scalars have been calibrated
based on some combination of historical performance, the ratio of modeled stressed losses to baseline losses estimated for other portfolios, and expert
judgment. Scalar adjustments are easy to develop,
implement, and communicate; however, the approach


Capital Planning at Large Bank Holding Companies

has significant shortcomings, including lack of transparency and lack of sensitivity to changes in portfolio composition and scenario variables. Consequently, the use of these types of approaches should
be, at most, limited to immaterial portfolios.

Available-for-Sale (AFS) and
Held-to-Maturity (HTM) Securities
BHCs should test all credit-sensitive AFS and HTM
securities for potential other-than-temporary impairment (OTTI) regardless of current impairment status. The threshold for determining OTTI for structured products should be based on cash-flow analysis
and credit analysis of underlying obligors. Most
BHCs used a ratings-based approach to determine
OTTI of direct obligations such as corporate bonds,
based on the projection of ratings migration under a
stress scenario and a ratings-based OTTI threshold.
However, some BHCs with weaker practice used a
ratings-based approach that kept the ratings static
over the scenario horizon.
BHCs should have quantitative methods that capture
appropriate risk drivers and explicitly translate
assumed scenario conditions into estimated losses.
Estimation methods should generate results that conform to standard accounting treatment, are consistent with scenario conditions, and are appropriately
sensitive to changes in key variables. Any assumptions (e.g., assumptions related to loss recognition)
should be consistent with the intent of a stress testing
exercise. Additionally, models should be independently validated for their use in projecting OTTI
losses for specific classes of securities.
OTTI processes for AFS and HTM securities portfolios varied in sophistication across BHCs. BHCs with
leading practices used estimation methods that capture both security-specific and country-specific performance data for relevant portfolios. For securitized
products, they modeled the credit risk of underlying
exposures (e.g., commercial real estate loans) to estimate potential losses. Where BHCs used management judgment, it was limited and well supported in
the methodology documentation.
In addition, BHCs with leading practices chose conservative approaches and assumptions for OTTI loss
estimation, such as recognizing losses in early quarters rather than over the entire scenario horizon.
Though, under current accounting rules, OTTI losses
are recognized only up to the amount of unrealized
losses, some BHCs have taken a conservative

approach to allow OTTI losses to exceed projected
unrealized losses.
BHCs with lagging practices did not test all creditsensitive securities for potential OTTI; rather, they
tested only currently impaired positions or securities
that met a certain criteria (e.g., only securities rated
below investment grade) for OTTI. BHCs should not
rely solely on a ratings-based threshold to determine
OTTI for structured products. BHCs with lagging
practices had OTTI loss-estimation methodologies
that did not capture appropriate risk drivers or scenario conditions and/or were not applied at a sufficiently granular level. In some cases, BHCs excluded
key explanatory variables for certain asset classes.
For example, the unemployment rate was used to
project OTTI losses for non-agency residential
mortgage-backed securities (RMBS), but the housing
price index (HPI) was excluded even though the
theory and empirical evidence points to a strong relationship between mortgage losses and housing prices.
As a result of these methodology deficiencies, these
BHCs projected OTTI losses that were inconsistent
with the risk characteristics of the portfolio and
assumed scenario conditions.

Operational Risk
Best practices in operational-risk models are still
evolving, and the Capital Plan Rule does not require
BHCs to use advanced measurement approach
(AMA) models for stressed operational-risk loss estimation.34 However, BHCs that have developed a rich
set of data to support the AMA should consider
leveraging the same data and risk-management tools
to estimate operational losses under a stress scenario,
regardless of a particular methodology they choose
to estimate losses.
Most operational-risk models use historical data on
operational-risk loss “events”—incidences in which a
BHC has experienced a loss or been exposed to loss
due to inadequate or failed internal processes, people,
or systems or from external events. Generally,
operational-risk events are grouped into one of several event-type categories, such as internal fraud,
external fraud, or damage to physical assets.35 In general, BHCs should use internal operational-loss data

12 CFR part 225, appendix G.
For example, the seven event-type categories used for AMA are
internal fraud; external fraud; employment practices and workplace safety; clients, products, and business practices; damage to
physical assets; business disruption and system failures; and
execution, delivery, and process management.

August 2013

as a starting point to provide historical perspective,
and then incorporate forward-looking elements, idiosyncratic risks, and tail events to estimate losses.
Most BHCs have supplemented their internal loss
data with external data when modeling operationalrisk loss estimates and scaled the losses to make the
external loss data more commensurate with their
individual risk profiles. The Federal Reserve expects
such scaling approaches to be well supported. Few
BHCs have incorporated business environment and
internal control factors such as risk control selfassessments and other risk indicators into their
operational-risk methodology. While the Federal
Reserve does not expect BHCs to use these qualitative tools as direct inputs in a model, they can help
identify areas of potential risk and help BHCs select
appropriate scenarios that stress those risks.
Internal Data Collection and Data Quality
The Federal Reserve expects BHCs to have a robust
and comprehensive internal data-collection method
that captures key elements, such as critical dates (i.e.,
occurrence, discovery, and accounting), event types,
and business lines. In general, BHCs should use complete data sets of internal losses when modeling, and
not judgmentally exclude certain loss data.
Data quality and comprehensiveness have varied considerably across BHCs. BHCs with lagging practices
often excluded certain internal loss data from model
input for various reasons. Examples include
• excluding large items such as legal reserves and tax/
compliance penalties;
• omitting losses from merged or acquired institutions mergers or acquisitions due to complications
in collection and aggregation; and
• excluding loss data from discontinued business
lines, even though the loss events were reasonably
generic and applicable to remaining business lines
within the organization.
Some BHCs have addressed observed outliers by
omitting them from the data set, modeling them
separately, or applying an add-on based on scenario
analysis or management input. If BHCs do not have
the data from potential mergers and acquisitions, one
way to account for this limitation is to scale existing
internal data using the size of operations and apply
an add-on to applicable business lines or units of
measure. If a BHC excludes data or uses datasmoothing techniques, especially as they affect large
losses, it should have a well-supported rationale for


doing so, and clearly document the rationale and the
The Federal Reserve expects BHCs to segment their
loss data into units of measure that are granular
enough to capture similar losses while balancing it
with the availability of data. Most BHCs have segmented datasets by event type; however, some BHCs
have segmented the loss data by consolidated business lines, event types, or some combination of
the two.
Correlation with Macroeconomic Factors
Most BHCs have attempted to identify correlation
between macroeconomic factors and operational-risk
losses, but some have struggled to identify a clear
relationship for some types of operational-risk loss
events. BHCs that did not identify a significant correlation typically developed other methodologies, such
as scenario analysis layered onto modeled results, to
project stressed operational-risk losses. These
approaches can be reasonable alternatives if BHCs
can demonstrate that their approach results in sufficiently conservative loss estimates that are consistent
with the stress scenario.
BHCs that identified correlations between macroeconomic factors and operational-risk elements typically
had large data sets and often used external loss data
to supplement internal data. These BHCs often identified correlations between loss frequency and macroeconomic factors for certain event types and adjusted
the frequency distributions for the respective event
type accordingly.
Common Operational-Loss-Estimation
Most BHCs have used their annual budgeting or
forecasting process to estimate operational losses in
the baseline scenario. The process typically uses a
combination of historical loss data and management
input at a business-line level. Some BHCs have used
historical averages from internal loss data to estimate
losses in the baseline scenario.
BHCs with stronger practices used a combination of
approaches to incorporate historical loss experience,
forward-looking elements, and idiosyncratic risks
into their stressed loss projections. Using a combination of approaches can help address model and data

See FR Y-14A reporting form: Summary Schedule Instructions,
p. 5.


Capital Planning at Large Bank Holding Companies

limitations. Some BHCs used separate models for
certain events types such as fraud or litigation, and
used other approaches (e.g., using historical averages)
for event types where no correlation with macroeconomic factors was identified. A simple approach may
be acceptable depending on the size and complexity
of the BHC as well as data and sophistication of
models available to them. Very few BHCs have yet
developed benchmarks to either challenge or further
support the projections provided by their main
Regression Models

Most BHCs have used a regression model, either by
itself or with another approach described below, to
estimate operational-risk losses for stress scenarios.
Some BHCs also have used a regression model for the
baseline scenarios, albeit with different parameters.
Operational-risk regression models are generally used
to estimate two variables: loss frequency (i.e., the
number of operational-risk losses) and loss severity
(i.e., the loss amount).
BHCs that were able to identify significant correlation between macroeconomic variables and
operational-risk losses have used regression models to
stress the loss frequency or total operational-risk
losses. Some macroeconomic variables were adjusted
for the purpose of correlation analysis or to reflect
time-lag assumptions. Most BHCs judgmentally
chose time periods for estimation and model specification rather than justifying them with statistical
Most BHCs were not able to find meaningful correlation between macroeconomic variables and
operational-risk loss severity. As a result, BHCs that
used a regression model to estimate loss frequency
typically applied the loss-severity assumption (e.g.,
static or four-quarter moving average) based on the
most recent crisis period to estimate operational
Modified Loss-Distribution Approach (LDA)

The LDA is an empirical modeling technique commonly used by BHCs subject to the AMA to estimate
annual value-at-risk (VaR) measures for operationalrisk losses based on loss data and fitted parametric
distributions. The LDA involves estimating probability distributions for the frequency and the severity of
operational loss events for each defined unit of measure, whether it is a business line, an event type, or

some combination of the two. The estimated frequency and severity distributions are then combined,
generally using a Monte Carlo simulation, to estimate the probability distribution for annual
operational-risk losses at each unit of measure.
For purposes of CCAR, LDA models have generally
been used in one of two ways: (1) by using a lower
confidence interval than the 99.9th percentile used by
the AMA, or (2) by adjusting the frequency based on
outcomes of correlation analysis. BHCs that modified the LDA by using a lower confidence interval
typically have used either the mean or median for the
baseline estimates and higher confidence intervals—
typically ranging from 70th percentile to 98th percentile—for the stressed estimates. Additionally, some
BHCs have used different confidence intervals for different event types. The Federal Reserve does not
require BHCs to use a particular percentile to produce stressed estimates. However, it expects BHCs to
implement a credible, transparent process to select
a percentile; be able to demonstrate why the percentile is an appropriate choice given the specific scenario under consideration; and perform sensitivity
analyses around the selection of a percentile to test
the impact of this assumption on model outputs.
Some BHCs modified the LDA by adjusting frequency distributions based on the observed correlation between macroeconomic variables and
operational-risk losses.
Scenario Analysis

Scenario analysis is a systematic process of obtaining
opinions from business managers and riskmanagement experts to assess the likelihood and loss
impact of plausible severe operational-loss events.
Some BHCs have used this process to determine a
management overlay that is added to losses estimated
using a model-based approach. BHCs have used this
overlay to incorporate idiosyncratic risks (particularly for event types where correlation was not identified) or to capture potential loss events that the BHC
had not previously experienced. BHCs should be able
to demonstrate the quantitative effect of the management overlay on final loss estimates.
Scenario analysis, if used effectively, can help compensate for data and model limitations, and allows
BHCs to capture a wide range of risks, particularly
where limited data are available. The Federal Reserve
expects BHCs using scenario analysis to have a
clearly defined process and provide an appropriate
rationale for the specific scenarios included in their

August 2013

loss estimate. The process for choosing scenarios
should be credible, transparent, and well supported.
Historical Averages

Some BHCs used historical averages of operationalrisk losses, in combination with other approaches
noted above, to estimate operational-risk losses under
stress scenarios. For example, BHCs have used historical averages for event types where no correlation
between macroeconomic factors and operational-risk
losses was identified but used a regression model for
event types where correlations were identified. A
small number of BHCs have used historical averages
as the sole approach to develop stressed loss estimates. When used alone, this approach is backwardlooking and excludes potential risks the BHCs have
not experienced. When using historical averages,
BHCs should support the chosen time periods,
thresholds, and any excluded or adjusted outliers and
demonstrate that loss estimates are consistent with
what are expected in the stress scenario.
Legal Exposures

Since legal exposure represents a significant portion
of operational losses for many BHCs, a number of
BHCs have analyzed and projected legal losses separately from non-legal losses. The Federal Reserve
expects BHCs to include all legal reserves and settled
legal losses in their total loss estimate for operational
risk. BHCs have used various methods to estimate
legal losses, such as applying a judgment-based
add-on for significant losses; using legal reserves;
using historical averages; or creating separate regression models for the clients, products, and business
practices event type. To estimate litigation losses
resulting from representations and warranties liabilities related to mortgage underwriting activities, some
BHCs have developed hazard-rate models based on
historical loan performance to estimate default rates
and then estimated repurchase claim rates.

Market Risk and Counterparty Credit Risk
BHCs that have sizeable trading operations may
incur significant losses from such operations under a
stress scenario due to valuation changes stemming
from credit and/or market risk, which may arise as a
result of moves in risk factors such as interest rates,
credit spreads, or equity and commodities prices, and
counterparty credit risk owing to potential deterioration in the credit quality or outright default of a trad-


ing counterparty.37 BHCs use different techniques for
estimating such potential losses. These techniques
can be broadly grouped into two approaches: probabilistic approaches that generate a distribution of
potential portfolio-level profit/loss (P/L) and deterministic approaches that generate a point estimate of
portfolio-level losses under a specific stress scenario.
Both approaches have different strengths and weaknesses. A probabilistic approach can provide useful
insight into a range of scenarios that generate stress
losses in ways that a deterministic stress testing
approach may not be able to do. However, the probabilistic approach is complex and often lacks transparency, and as a result, it can be difficult to communicate the relevant scenarios to senior managers and
the board of directors. In addition, the challenges
inherent in tying probabilistic loss estimates to specific underlying scenarios can make it difficult for
management and the board of directors to readily
discern what actions could be taken to mitigate portfolio losses in a given scenario. Combined, these factors complicate the use of probabilistic approaches as
the primary element in an active capital planning
process that reflects well-informed decisions by senior
management and the board of directors. The Federal
Reserve expects BHCs using a probabilistic approach
to provide evidence that such an approach can generate scenarios that are potentially more severe than
what was historically experienced, and also to clearly
explain how BHCs use the scenarios associated with
tail losses to identify and address their idiosyncratic
By comparison, a deterministic approach generally
produces scenarios that are easier to communicate to
senior management and the board of directors. However, a deterministic approach often uses a limited set
of scenarios, and may miss certain scenarios that may
result in large losses. The Federal Reserve expects
BHCs using a deterministic approach to demonstrate
that they have considered a range of scenarios that
sufficiently stress their key exposures.
For CCAR, most BHCs generally relied on a deterministic approach. BHCs using deterministic
approaches often relied on statistical models—for

Under the Federal Reserve’s stress testing rules, BHCs with
greater than $500 billion in total consolidated assets who are
subject to the market risk rule (12 CFR part 225, appendix E)
are required to apply the global market shock as part of their
annual Dodd-Frank Act company-run stress tests.


Capital Planning at Large Bank Holding Companies

example, to inform the magnitude of risk-factor
movements and covariances between risk factors—
and also considered multiple scenarios as part of the
broader internal stress testing supporting their capital
planning process. BHCs using deterministic
approaches used a three-step process to generate P/L
losses under a stress scenario:

aware that such an approach may omit significant
risks that are unique to their positions, and that such
omissions could lead to a negative assessment of a
firm’s capital planning process. BHCs should clearly
document the process they use to select stress scenarios, with sufficient justification and clear articulation of key aspects of the scenarios.38

1. Design and selection of stress scenarios

Translating Scenarios to Risk Factor Shocks

2. Construction and implementation of the scenario
(that is, translation to risk-factor moves)
3. Revaluation (and aggregation) of position and
portfolio-level P&L under the stress scenarios
The Federal Reserve expects BHCs to have robust
operational and implementation practices in all areas,
including position inclusion, risk-factor representations, and revaluation methods.
Stress Scenarios
Most BHCs using deterministic approaches developed a set of broad narratives and considered a number of market shock scenarios that address the
breadth of the BHCs’ risks before selecting the scenario included in their capital plans. In general, these
BHCs used some combination of historical events
and hypothetical projections to inform and develop
the market shock scenarios. They also developed certain core themes or narratives for each scenario,
which was sometimes supplemented with an overlay
to capture additional nuances. BHCs generally developed the overlays using expert judgment based on the
knowledge of their positions and market
The Federal Reserve expects BHCs to consider multiple market shock scenarios as part of their internal
stress testing. BHCs should develop and use stress
scenarios that severely stress BHCs’ mark-to-market
positions and account for BHCs’ idiosyncratic risks,
in the event of a market-wide or firm-specific stress.
In developing scenarios, BHCs should ensure that
stress scenarios appropriately stress positions or
products in which the BHC has a large market share
(net or gross) or is a dominant player and should also
consider more unusual basis risks arising from complex interlocking and interdependent positions, if
such moves could result in large losses. BHCs that
only use a scenario that closely mirrors the Federal
Reserve’s global market shock component of the
severely adverse and adverse scenarios should be

Once broad scenarios were developed, BHCs translated these scenarios into concrete specification of
individual risk factors that were the actual inputs to
pricing models, typically using the existing risk infrastructures and processes used for risk management,
such as VaR and credit valuation adjustment (CVA).
Most BHCs used instantaneous market shocks for
stress testing, which assumed highly stressful outcomes that have typically occurred over a period of
time (days, weeks, or months) will occur instantaneously. Given the uncertainty surrounding a firm’s
ability to exit or manage positions during a period of
severe market stress, this is an appropriate practice
and suitably conservative for capital planning. Consistent with general supervisory expectations around
risk-measurement processes, BHCs should clearly
document the approximations and assumptions used
as part of their measurement of risks under stress,
assess the potential impacts, and address any deficiencies identified.39
The size of shocks assumed in the stress scenario is
often quite large. As a result, mechanical application
of such shocks to current levels of risk factors could
result in implausible outcomes such as negative riskfree rates or negative forward rates. BHCs should
ensure that the proposed shocks produce results that
are plausible. In particular, BHCs should take care in
modeling dislocations and discordant moves of risk
factors that normally move similarly. Additionally,
while dislocations and discordant moves are expected
under stress, BHCs should have a process to assess
that the resulting joint moves of risk factors are reasonable. Also, the dislocations and discordant moves
implied by a stress scenario may require risk-factor
mappings that deviate from the normal mappings.
BHCs should clearly document instances of such
deviation and provide support.40


See FR Y-14A reporting form: Summary Schedule Instructions,
pp. 5–6.
See id., p. 6.
See id., pp. 5–6.

August 2013

Revaluation Methodologies and P/L Estimates
In principle, revaluation for stress testing can be carried out using the same infrastructure and calculators
as conventional risk-measurement tools. However,
practical revaluation methods may embed a number
of approximations, which could introduce mismeasurement into the stress test results. In particular,
VaR methodologies often use approximation methods for a number of reasons—for example, to economize on computational costs related to running a
large number of scenarios daily. Although approximation methods may perform adequately for the
risk-factor moves that are considered in normal conditions (for a small number of scenarios), BHCs
should generally use “full-revaluation” methods for
stress testing, given the very large risk-factor moves,
especially for nonlinear positions with value dependent on multiple risk factors. BHCs can use approximation methods on a limited basis if extensive tests
and analyses suggest that the potential mismeasurement from using such methods is not significant.
BHCs should clearly support the process they use to
ascertain the extent of such mismeasurements. Also,
for certain parameters that are not easily “marketobservable” and, therefore, cannot be inferred from
traded instruments (e.g., correlations for creditdefault baskets and correlations for certain interestrate and exchange-rate pairs), BHCs should consider
suitably perturbed values of the model parameters.
In addition, BHCs should ensure that P/L estimates
under the stress scenario are relatively easy to interpret and explain. For example, BHCs with leading
practices easily identified key P&L drivers in terms of
positions, asset classes, and risk types. BHCs should
also conduct sensitivity analysis to ensure that P/L
estimates under the stress scenario are robust, without being unduly sensitive to small changes in inputs,
assumptions, and modeling choices.
Counterparty and Issuer Defaults
Defaults of counterparties or issuers and/or reference
entities are typically not embedded directly within the
instantaneous market shock scenario. BHCs often
use a model similar to that used for the incremental
risk regulatory capital charge—a probabilistic
approach based on some measure of PD, LGD, and
EAD of counterparties or issuers—to estimate losses
from possible defaults over some future horizon (e.g.,
to the typical margin period of risk). BHCs with
leading practices also considered for their internal
stress testing an explicit default scenario of one or


more of their largest counterparties and/or customers. This approach has the benefit of allowing the
BHC to consider targeted defaults of counterparties
and customers to which the BHC has large
Risk Mitigants and Other Assumptions
Some BHCs have incorporated management
responses to the stress, assuming, for example, some
positions would be sold or hedged over time under
the stress scenario. The Federal Reserve expects any
assumptions about risk mitigation to be conservative.
Where BHCs assume management actions that have
the effect of reducing losses under the scenario, they
should be able to demonstrate that such actions are
consistent with established policy, supported by historical experience, and executable with high confidence in the market environment contemplated by
the scenario. BHCs should recognize that their ability
to take mitigating actions may be more limited in the
stress scenario. For example, it may not be reasonable
to assume that BHCs can easily sell their positions to
other BHCs under the stress scenario. In addition,
BHCs should avoid making unrealistic assumptions
about their ability to foresee precisely how a scenario
would play out, and take action on the basis of that

PPNR Projection Methodologies
The Capital Plan Rule requires BHCs to estimate revenue and expenses over the nine-quarter planning
horizon.41 Accordingly, BHCs should have effective
processes for projecting PPNR and its revenue and
expense subcomponents over the same range of
stressful scenarios and environments used for estimating losses. In projecting these amounts, BHCs
should consider not only their current positions, but
also how their activities and business focus may
evolve over time under the varying circumstances and
operating environments reflected in the scenarios
being used.

General Considerations for Robust
PPNR Projections
As part of a comprehensive enterprise-wide scenario
analysis program, BHCs should have methodologies
that generate robust projections of PPNR consistent
with the current and projected paths of on-and off41

12 CFR 225.8(d)(2)(i).


Capital Planning at Large Bank Holding Companies

balance-sheet exposures, risk-weighted assets (RWA),
and other exposure assumptions used for related loss
estimation. PPNR projections should also be consistent with assumed scenario conditions and be projected in accordance with the same accounting basis
that would be used to calculate relevant capital ratios.
BHCs should project all key elements of PPNR at a
level of granularity consistent with the materiality of
revenue and expense components and sufficient to
capture differing drivers of revenue and expenses
across the organization. Finally, BHCs should consider the effects that regulatory changes (e.g., changes
in deposit insurance coverage limits) may have on
their ability to replicate historical performance or
achieve stated goals.
Key assumptions that may materially affect PPNR
estimates should be consistent with assumed scenario
conditions and internally consistent within each scenario, particularly assumptions related to the business model and strategy (e.g., deposit growth, pricing
assumptions, expense reductions, and other management actions). Management is expected to evaluate
the reasonableness and timing of projected strategies,
including mitigating actions taken in a stressful scenario, to ensure that the assumptions reflect realistic
and achievable outcomes for a given scenario. Where
possible, assumptions should be supported by quantitative analysis or empirical evidence.
In all cases, BHCs should ensure that projections
(including those of PPNR, loss, balance sheet size
and composition, and RWA) present a coherent story
within each scenario. BHCs should clearly establish a
relationship among revenue, expenses, the balance
sheet, and any applicable off-balance-sheet items and
document how their process generates a consistent
and coherent evolution of these items over the course
of the scenario.42 For example, origination assumptions should be the same for projecting loan balances,
related loan fees, origination costs, and loan losses.
Similarly, there should be coherence among trading
revenue projections, trading assets, trading liabilities,
and trading RWA projections. Management should
document the relationships among these items and
avoid cases where outcomes move in counterintuitive



See 12 CFR 225.8(d)(i)–(ii); FR Y-14A reporting form: Summary Schedule Instructions, pp. 5–6.
See id.

Observed PPNR Projection Practices
The translation of macroeconomic assumptions into
projections of PPNR over a range of stressful scenarios and environments can take many forms, and
BHCs used a variety of approaches and models to
make these projections. BHCs with stronger practices
demonstrated strong interactions among central
planning functions, business lines, and the treasury
group, with an open flow of information and a
robust challenge process. At these BHCs, the role of
the central group was not just to aggregate components of PPNR projections. In some cases, the corporate planning areas also provided independent projections that were compared to the aggregated business
line results as a part of the challenge process. At
other BHCs, the corporate planning group derived
the PPNR projections, which were then discussed
and challenged by business lines. Both approaches
resulted in better-supported assumptions and projections than approaches in which the central group
simply aggregated projections made by others.
In addition, BHCs with stronger practices made projections based on a full exploration of the most relevant relationships between assumed scenario conditions and revenues and expenses. At these BHCs,
business-line expertise was leveraged in the development of methodologies. A key part of this exploration was determining the way that revenues and
expenses were segmented for projection purposes.
BHCs with stronger practices did not rely exclusively
on the line-item definitions in regulatory reports,
though these BHCs often established a process to
clearly map internal BHC reporting conventions to
the various line items on the FR Y-14 schedules.
In contrast, BHCs with lagging practices lacked clear
processes for translating assumed scenario conditions
into revenue and expense projections. Frequently, it
was observed that one or more material components
of their projections appeared inconsistent with scenario conditions. In some cases, projections of certain revenue and expense components relied heavily
on management judgment, which was not transparent, well supported, or subject to a robust challenge
process. In other cases, revenue estimates varied from
historical experience and conventional expectations,
and management provided no documented support
or analysis around the reasonableness and sensitivity
of modeling assumptions. Overall, data limitations,
unclear or unsubstantiated management assumptions, and poor documentation were the problems
most prevalent across the BHCs.

August 2013

Another commonly observed practice for estimating
PPNR under stressed conditions was the adjustment
of budget or baseline estimates, with budget estimates largely qualitatively derived through input
from a variety of business lines and/or stakeholders
across the BHC. Although a process of adjusting
baseline estimates is not problematic in itself, some
BHCs relied heavily on baseline estimates to develop
stress scenario outcomes without considering favorable strategic actions and assumptions incorporated
into baseline results that might not be realistic or feasible under stressed conditions. If a BHC derives
stressed estimates by applying a stress overlay to
baseline estimates, it should demonstrate the link
between baseline estimates and baseline conditions,
demonstrate the appropriateness of the overlay based
on the differing conditions between the scenarios,
and appropriately consider changes in management
actions or other related assumptions under a stress
BHCs with weaker practices used models with low
predictive power, in part due to data limitations.
BHCs should not use weak models just for the sake
of using a modeled approach to PPNR. Some BHCs
used weak models either as a frame of reference or a
starting point to translate economic factors into estimates of key PPNR components, but then adjusted
the results using expert judgment. In such cases,
BHCs should thoroughly explain and document why
results, once adjusted, are consistent with the scenario conditions.44 In cases where models have low
predictive power, BHCs with stronger practices found
other ways to compensate, such as using industrylevel models with BHC-specific market share
assumptions to project revenue. In all cases, BHCs
with stronger practices provided supplemental analysis describing why the approach was appropriate.
In cases where BHC-specific data were limited,
BHCs with stronger practices used external data to
augment and extend their internal data. BHCs with
weaker practices relied on models that were overly
influenced by limited data covering a single economic
cycle. This approach is particularly problematic if the
BHC also experienced favorable conditions, such as a
significant recovery, during the single cycle, which
might not recur in future downturns. In some cases,
data were limited to as few as 10 quarters, which
would not encompass a period of economic weaken44

See id.


ing or be sufficient to estimate a robust model, and
thus would not be appropriate for considering potential results in a downturn. Many BHCs cited challenges due to systems mergers or changes that limited
data availability, but failed to adequately compensate
for these limitations by supplementing internal data
with external industry data, where appropriate, or by
considering whether longer time series of available
aggregate data would be preferable to a shorter time
series of more granular data.
Some BHCs with weaker practices made business
model and strategy assumptions (e.g., new business,
expense reductions, the assumption of mitigating
actions) that were not consistent with stressed scenario conditions and the intent of a capital planning
and stress testing exercise. For example, management
assumed it would be able to drastically reduce loan
origination activity, cut expenses, or take other mitigating actions in a severely adverse scenario without
considering the longer-term consequences on the
BHC’s strategy and operating structure.
The following sections provide specific expectations
for projecting key components of PPNR, as well as
summary points on observed range of practice.

Net Interest Income
Net interest income projections are closely linked to
many other elements of a BHC’s capital plan. Balance sheet assumptions used to project net interest
income should be consistent with balance sheet
assumptions considered as part of loss estimation as
well as with other asset and liability management
assumptions. Loan pricing should be consistent with
both scenario conditions and competitive and strategic factors, including projected changes to the size of
the portfolio. Deposit projections should incorporate
the impact of strategic plans and pricing on deposit
growth or decline, in addition to scenario factors.
Net interest income projections are expected to incorporate the balances and contractual terms of current
portfolio holdings as well as the behavioral characteristics of these portfolios. The methods BHCs use to
project their net interest income should be able to
capture dynamic conditions for both current and
projected balance sheet positions. Such conditions
include but are not limited to prepayment rates, new
business spreads, re-pricing rates due to changes in
yield curves, behavior of embedded optionality such


Capital Planning at Large Bank Holding Companies

as caps or floors, call options, and/or changes in loan
performance (that is, transition to nonperforming or
default status) consistent with loss estimates.
Some BHCs specified product characteristics and
conducted analysis around these characteristics (e.g.,
repricing behavior, line utilizations) both for current
assets and new originations in order to understand
the variance in behaviors under the different scenarios considered. They also attempted to capture
the product mix changes that would occur as a result
of customer and market conditions (e.g., changes in
domestic deposit mix due to anticipated growth in
demand for time deposits for a specified scenario).
BHCs with stronger documentation practices provided detailed tables explaining underlying assumptions such as balance drivers and spread and growth
assumptions by product.
Some BHCs partially integrated loss projections into
net interest income projections but did not
adequately align all projection-related assumptions.
For example, these BHCs might take the full loan
loss projections and allocate them across the portfolios based on the current mix of nonperformance
across those loan portfolios, without considering the
changing relative performance of those portfolios
over the course of the scenario. Other BHCs were
unable to demonstrate coherence between net interest
income projections and loss projections, generally
because one or both modeling approaches did not
fully capture the behavioral characteristics of the
loan portfolio.
BHCs with stronger practices had net interest income
projection methodologies that captured adjustments
in the amortization of discounts or premiums for
assets held at a value other than par that would occur
under various scenarios. Under FASB Statement
No. 91,45 yields would adjust under varying scenarios
as amortization schedules change due to changes in
expected payment speeds.
For pricing, many BHCs assumed a constant spread
to a designated index. BHCs with stronger practices
considered whether this assumption was consistent
with historical experience and assumed scenario conditions as well as the BHC’s strategy as reflected in

Financial Accounting Standards Board, “Accounting for Nonrefundable Fees and Costs Associated with Originating or
Acquiring Loans and Initial Direct Costs of Leases—an
Amendment of FASB Statements No. 13, 60, and 65 and a
Rescission of FASB Statement No. 17 (Issued 12/86),” FASB
Statement No. 91.

the balance sheet projections. Some BHCs recognized
that new business pricing could differ as a result of
tightening or widening of spreads and documented
these assumptions.

Non-Interest Income
BHCs are expected to produce stressed projections of
non-interest income that are consistent with assumed
scenario conditions, as well as with stated business
strategies. Due to inherent challenges in estimating
certain non-interest income components, some BHCs
used more than one method and/or employed benchmark analysis to inform estimates. Stronger methodologies estimated non-interest income at a granularenough level to capture key risk factors or characteristics specific to an activity or product. For example,
for asset management, many BHCs used different
methods to project revenue from brokerage activities
and fund management activities.
Like all aspects of PPNR, internal consistency
between non-interest income and other assumptions
such as projected paths for the balance sheet and
RWA is important. BHCs should establish relationships between material components of non-interest
income and the balance sheet for components that
are highly correlated with the path of the balance
sheet, such as some kinds of loan-related fee income.
BHCs with trading assets should document how
trading revenue projections are linked to trading
assets, trading liabilities, and trading RWA and how
all these elements are consistent with conditions in
the stress scenario.46 BHCs with business profiles
driven by off-balance-sheet items should document
how revenue projections are linked to on- and offbalance-sheet behavior.47 Although relationships
between revenue and trading assets or off-balancesheet items may be weak over short periods, BHCs
should nevertheless establish a procedure for projecting relevant balance sheet and RWA categories in
support of those revenues and test for the reasonableness of the implied return on assets (ROA). If a BHC
estimates trading or private equity revenue by tying
balance changes to changes in broad indices, the
BHC should establish the level of sensitivity of its
positions relative to the indices and not automatically
assume a perfect correlation between the two.



See FR Y-14A reporting form: Summary Schedule Instructions,
p. 5.
12 CFR 225.8(d)(3)(iii); see also FR Y-14A reporting form:
Summary Schedule Instructions, pp. 5–6.

August 2013

BHCs with mortgage servicing right (MSR) assets
should ensure that delinquency, default, and voluntary prepayment assumptions are robust and
scenario-dependent. These models should capture
macroeconomic variables, especially home prices. For
those BHCs that routinely hedge MSR exposure,
hedge assumptions and results for enterprise-wide
scenario analysis should reflect the stress scenario.
Some BHCs assumed a perfect or near-perfect hedge
relationship between changes in the value of their
MSR and hedge portfolio, and captured the ineffectiveness of the hedge under the stress scenario
through the net carry, transaction costs, and/or bidask spread components. BHCs with stronger practices used an optimization routine that dynamically
rebalanced the hedge portfolio each quarter.
BHCs with stronger practices considered individual
business models and client profiles when projecting
revenue and fee income from various business activities. BHCs with stronger practices also considered
capacity constraints when estimating mortgage loan
production and loan sales over the scenario horizon,
whereas BHCs with weaker practices assumed significant increases in volume without regard to market
saturation or other factors. Other weaker practices
observed included using the same strategic business
assumptions in both the baseline and stress scenarios
and making favorable assumptions around new business and/or market share gains. For example, some
BHCs assumed that all baseline initiatives would be
implemented in stress scenarios without interruption
or changes to the outcomes.
In addition, BHCs with weaker practices did not
show sufficiently stressed declines in revenue relative
to assumed scenario conditions, despite stated correlations to macroeconomic and other drivers. For
example, while many BHCs showed significant
declines in credit card gross-interchange fee revenue
due to declines in consumer spending, some BHCs
also assumed that significant declines in marketing
expenses recorded as contra-revenue would more
than offset the declines in gross interchange revenue,
resulting in an increase in net revenue. Other BHCs
assumed revenue components, such as fees or trading
revenue, could not fall below historical levels.
Further, BHCs with weaker practices considered only
a very limited set of scenario variables and/or drivers
in establishing relationships, which resulted in estimates that appeared inconsistent with the scenario.
For example, some BHCs used interest rates only to
project origination activity or solely used asset bal-


ances (instead of the number of accounts) to estimate account fees. Other BHCs simply regressed
high-level revenue items against scenario factors
rather than considering how scenario conditions
would affect the key drivers of those line items (such
as volume). For instance, modeling interchange revenues or asset management fees is likely to be less
effective than modeling customer spending or assets
under management, respectively, given the scenario
being used, and then considering fee and/or rate

Non-Interest Expense
BHCs should fully consider the various impacts of
the assumed scenario conditions on their non-interest
expense projections, including costs that are likely to
increase during a downturn. For example, items such
as other real estate owned or credit-collection costs
may spike, whereas management may have some ability to control other expenses. Like other projections,
non-interest expense projections should be consistent
with balance sheet and revenue estimates and should
reflect the same strategic business assumptions.
BHCs with weaker practices did not account for
additional headcount needs in certain areas, nor for
any corresponding changes to compensation expense
associated with increased collections activity resulting from declines in portfolio quality and/or
increased underwriting activity to support any
assumed portfolio growth.
To the extent the projections assume mitigating
actions to offset revenue declines, BHCs should demonstrate that such actions are attainable in the scenario, given assumed asset levels and the resources
necessary to support operations. If the projections
embed material expense reductions, such assumptions should be supported with analysis of historical
data or empirical evidence and subject to challenge
and review. BHCs with weaker practices assumed
mitigating actions consistent with past actions but
failed to consider how differences in the business
environment and the severity of the economic conditions might affect their ability to execute such
actions. BHCs are expected to evaluate the timing of
projected strategies and their impact on future revenue, expenses, and operating structure.
BHCs with stronger practices had estimation methodologies that considered the drivers of individual
expense items and the sensitivity of those drivers to
changing scenario conditions and business strategies.
They considered the timing of non-interest expense


Capital Planning at Large Bank Holding Companies

cuts and recognized that the BHC might not be able
to react to a developing stressful scenario immediately or might be subject to existing contractual obligations that could not be altered. BHCs with weaker
practices generated non-interest expense estimates
that appeared unrealistic in light of assumed scenario
conditions. Some BHCs assumed that they could
immediately reduce costs through dramatic cuts in
marketing and rewards programs, compensation, or
other discretionary expenses. Projecting sizeable

reductions in key expense components without providing sufficient support as to the reasonableness of
the cuts, how management intends to realize the cuts,
and how the cuts will affect future revenue is not
acceptable. Additionally, such assumptions imply
perfect knowledge of the conditions as they unfold,
rather than a series of independent decisions that
would be made by management as the scenario


Assessing Capital Adequacy Impact

Balance Sheet and RWAs
BHCs should have a well-documented process for
generating projections of the size and composition of
on- and off-balance sheet positions and RWA over
the scenario horizon.48 Balance projections are a key
input to enterprise-wide scenario analysis given their
direct impact on the estimation of losses, PPNR, and
RWA. Estimating the evolution of balance sheet size
and composition under stress integrates many interrelated features. For example, loan balances and the
stock of AFS securities at a point in time will depend
upon origination, purchase, and sale activity from
period to period, as well as maturities, prepayments,
and defaults. Due to complexities related to dynamically projecting and integrating various components
(e.g., originations, prepayments and defaults), most
BHCs made direct projections of balances for each
major segment of the balance sheet (e.g., loans,
deposits, trading assets and liabilities, and other
assets) for each quarter of the scenario horizon.
BHCs often faced challenges in integrating the ultimate balance projections with other aspects—for
example, borrower or depositor behavior. BHCs with
stronger practices separately considered the drivers of
change to asset and funding balances, such as contractual paydowns, modeled prepayments, nonperformance, and new business activity for assets, rather
than simply projecting targeted balances directly. At
these BHCs, each element was separately assessed for
consistency with scenario conditions and other management assumptions. BHCs with stronger practices
also either directly considered the impact of these
various factors in their balance projections or had
procedures to evaluate the reasonableness of any
implied behavior by including input from businessline leaders in the process and iterating to reasonable
estimates in a well-supported and transparent

12 CFR 225.8(d)(2)(i)(A); see also FR Y-14A reporting form:
Summary Schedule Instructions, p. 6.

BHCs should clearly establish and incorporate into
their scenario analysis the relationships among and
between revenue, expense, and on- and off-balancesheet items under stressful conditions. Most BHCs
used asset-liability management (ALM) software as a
part of their enterprise-wide scenario-analysis toolkit, which helps integrate these items. BHCs that do
not use ALM software must have a process that integrates balance sheet projections with revenue, loss,
and new business projections. BHCs with more
tightly integrated procedures were better able to
ensure appropriate relationships among the scenario
conditions, losses, expenses, revenue, and balances.
As noted above, BHCs should not rely on favorable
assumptions that cannot be reasonably assured in
stress scenarios given the high level of uncertainty
around market conditions. Examples of aggressive or
favorable balance sheet assumptions include (1) large
changes in asset mix that serve to decrease BHCs’
risk weights and improve post-stress capital ratios but
that are not adequately supported or reflected in
PPNR or loss estimates; (2) “flight-to-quality”
assumptions and funding mix changes that increase
deposits and reduce the dollar cost of funding;
(3) significant balance sheet shrinkage with no consideration of the potential losses associated with
reducing positions in periods of market stress; and
(4) operating margin improvement. BHCs that make
favorable assumptions should have sufficient evidence that they can be reasonably assured in the
assumed stress scenario.
BHCs’ RWA projections should be based on corresponding projections of on- and off-balance-sheet
exposures and their risk attributes and should be
consistent with the severity of the stress conditions
under each scenario. For general credit-risk exposures, BHCs should project balances for material
asset categories with sufficient granularity to facilitate application of regulatory risk-weighting
approaches associated with different asset categories.
For trading exposures, BHCs should translate
changes in scenario variables into risk-parameter


Capital Planning at Large Bank Holding Companies

estimates that drive RWA calculations (e.g., the
potential for RWA per dollar of some trading book
positions to increase in periods of higher levels of
general market volatility). Where RWA projections
are based on internal risk models, BHCs should not
assume any RWA reductions from potential data or
model enhancements to RWA calculation methodologies over the projection period. In all cases, BHCs
should document any assumptions made as part of
the balance sheet and RWA projection process and
perform independent reviews and validations of balance sheet and RWA projection methodologies and
resulting estimates.49

Allowance for Loan and Lease Losses
BHCs should maintain an adequate ALLL along the
scenario path and at the end of the scenario horizon.
Reserve adequacy should be assessed against projected size, composition, and risk characteristics of
the loan portfolio throughout the scenario horizon.
In general, the ALLL build and release should be
consistent with the scenario path, portfolio credit
quality, loss recognition approach, loan loss estimates, and loan portfolio balance projections (including any portfolio growth assumptions). If BHCs use
estimation approaches that implicitly delay the recognition of losses, such as net charge-off models, they
should adequately build reserves to account for losses
not recognized during the scenario horizon. If the
approach relies on top-down coverage levels, BHCs
should compare coverage ratios and loss-emergence
periods to historical stress environments and to internal policies and explain the differences if material differences exist.

Aggregation of Projections
BHCs should have a well-established and consistently
executed process for aggregating loss, revenue and
expense, and on- and off-balance sheet and RWA
estimates, as part of enterprise-wide scenario analysis, to assess the post-stress impact of those estimates
on capital ratios. BHCs that are more effective at
implementing such a process have established centralized groups with responsibility for
• combining loss, revenue, balance sheet, and RWA

See id.

• providing strong governance and controls around
the process;
• ensuring coherence of component estimates and
aggregate results; and
• applying and documenting any adjustments.50
These centralized groups have been able to source
estimates from a range of internal parties involved in
enterprise-wide scenario analysis and develop consolidated pro forma financial results that are internally consistent and conform to accounting
BHCs should develop a governance structure around
the enterprise-wide scenario analysis process that
provides for a robust analysis and challenge of the
coherence of the aggregate results and determine
whether any adjustments need to be made based on
the analysis. In particular, BHCs should assess
whether the paths of individual loss and revenue
components are consistent with the paths of balance
sheet and RWA estimates and the overall scenario
path. For example, an increase in PPNR amid declining balances would appear generally inconsistent and
should warrant further investigation. In assessing
consolidated financial results, BHCs should account
for any potential changes in relationships between
losses and financial performance drivers during periods of stress.
BHCs should have good understanding of instances
when exposures with similar underlying risk characteristics that are part of different portfolios or business lines exhibit different sensitivities to scenario
conditions. BHCs should identify instances where the
differences are due to inconsistent assumptions or
modeling approaches that require management attention, rather than differences in accounting treatment.
In addition, if a BHC’s enterprise-wide scenario
analysis results in post-stress outcomes that are more
favorable than those under baseline conditions,
BHCs should critically evaluate the reasonableness
and consistency of assumptions across portfolios,
business lines, and other areas of loss and revenue
BHCs that had an effective aggregation process leveraged their business planning and financial and regulatory reporting systems as part of that process.
Using standalone tools or spreadsheets in the aggregation process is a weak process. If a BHC needs to

See id.

August 2013

use standalone tools or spreadsheets due to systems
limitation, management should ensure robust controls are in place, including access and change controls, and should maintain an audit trail and document all approvals for any adjustments made. BHCs
should also have reconciliation procedures and dataquality and logic checks in place to ensure that the
results from the enterprise-wide scenario analysis reconcile to both management reporting and regulatory
reports, with a transparent mapping between various
reporting taxonomies.


BHCs with weaker practices had limited or no reconciliation procedures or other controls in place to
ensure the integrity, completeness, and accuracy of
the consolidated post-stress capital metrics. BHCs
with weaker practices also had no process to ensure
consistency in the BHC-wide application of scenario
assumptions and management adjustments, and had
weak governance and documentation standards.


Concluding Observations

The goal of this publication is to outline the Federal
Reserve’s expectations for internal capital planning at
large BHCs and to highlight the range of current
practice as observed during the 2013 CCAR. This
discussion is intended to provide a more comprehensive set of criteria to assist BHC management in
assessing their current capital planning processes and
in designing and implementing improvements to
those processes, as well as to provide insight to a
broader audience about the key aspects of BHCs’
capital planning practices.
Internal capital planning practices have evolved considerably since the financial crisis and the implementation of the Federal Reserve’s Capital Plan Rule in
2011. BHCs have made advances in the identification
and measurement of the risks to their capital and in
the integration of stress testing and capital planning
into their broader strategic planning processes. The
fundamental insight governing the Federal Reserve’s
expectations about capital planning is the importance
of having a forward-looking perspective on the risks
to a BHC’s capital resources under severely stressful
conditions. In particular, a forward-looking perspective involves understanding how a BHC’s revenuegenerating capacity and potential losses could be
affected in stressed economic and financial market
conditions; understanding the particular vulnerabilities arising from its business model and activities;
and having a capital policy in place that governs the
BHC’s capital actions under both “normal” and
stressed economic conditions. These elements represent substantial conceptual and operational improvements in capital planning that go well beyond simple
consideration of current and expected future capital
While many of the large BHCs subject to the Capital
Plan Rule have made substantial improvements in
capital planning, there is still considerable room for
advancement across a number of dimensions. Areas
where some BHCs continue to fall short of leading
practice include

• not being able to show how all their risks were
accounted for in their capital planning processes;
• using stress scenarios and modeling techniques that
did not address the particular vulnerabilities of the
BHC’s business model and activities;
• generating projections for at least some components of loss, revenue, or expenses using
approaches that were not robust, transparent,
and/or repeatable, or that did not fully capture the
impact of stressed conditions;
• having capital policies that did not clearly articulate
a BHC’s capital goals and targets, did not provide
analytical support for how these goals and targets
were determined to be appropriate, and/or were not
comprehensive or detailed enough to provide clear
guidance about how the BHC would respond as its
capital position changed in different economic circumstances; and
• having less-than-robust governance or controls
around the capital planning process, including
around fundamental risk-identification,
-measurement, and -management practices that are
among the critical elements that support robust
capital planning.
All the BHCs that participated in CCAR faced challenges across one or more of these areas. And
although many BHCs demonstrated leading practices
in several dimensions of capital planning, the leading
capital planning practices identified in this paper will
continue to evolve as new data become available, economic conditions change, new products and businesses introduce new risks, and estimation techniques
advance further. As the frontier of capital planning
practice advances, the Federal Reserve’s expectations
for how BHCs implement the requirements of the
Capital Plan Rule and the related company-run stress
testing required under the Dodd-Frank Act will also
evolve.51 Such advances in capital planning practices
will enhance the health and stability of individual
BHCs and of the overall banking system.

12 CFR part 252, subpart G.