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Dodd-Frank Act Stress Test 2013:
Supervisory Stress Test Methodology
and Results
March 2013

BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM

Dodd-Frank Act Stress Test 2013:
Supervisory Stress Test Methodology
and Results
March 2013

BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM

Errata
The Federal Reserve revised this paper on March 14, 2013, to reflect corrected data received from one bank
holding company. The revisions are listed below.
On p. 15, under “Stressed Regulatory Capital Ratios,” the numbers in the third sentence have been revised from
2.0 and 3.9 to 2.1 and 4.0, respectively.
On p. 16, under Table 1.A:
• Tier 1 capital ratio (%), Stressed capital ratios, Q4 2014 has been revised from 9.2 to 9.1.
•
•
•
•
•

Tier 1 capital ratio (%), Stressed capital ratios, Minimum has been revised from 9.0 to 8.9.
Total risk-based capital ratio (%), Stressed capital ratios, Q4 2014 has been revised from 11.8 to 11.7.
Total risk-based capital ratio (%), Stressed capital ratios, Minimum has been revised from 11.7 to 11.6.
Tier 1 leverage ratio (%), Stressed capital ratios, Q4 2014 has been revised from 6.0 to 5.9.
Tier 1 leverage ratio (%), Stressed capital ratios, Minimum has been revised from 6.0 to 5.9.

On p. 17, under Table 2:
• The Goldman Sachs Group, Inc., Tier 1 capital ratio (%), Projected Q4 2014 has been revised from 10.8 to 9.8.
• The Goldman Sachs Group, Inc., Tier 1 capital ratio (%), Projected minimum has been revised from 8.4 to 7.5.
• The Goldman Sachs Group, Inc., Total risk-based capital ratio (%), Projected Q4 2014, has been revised from 13.8 to
12.8.
• The Goldman Sachs Group, Inc., Total risk-based capital ratio (%), Projected minimum has been revised from 11.3 to
10.4.
• The Goldman Sachs Group, Inc., Tier 1 leverage ratio (%), Projected Q4 2014 has been revised from 6.2 to 5.6.
• 18 participating bank holding companies, Tier 1 capital ratio (%), Projected Q4 2014 has been revised from 9.2 to 9.1.
• 18 participating bank holding companies, Tier 1 capital ratio (%), Projected minimum has been revised from 9.0 to 8.9.
• 18 participating bank holding companies, Total risk-based capital ratio (%), Projected Q4 2014 has been revised from 11.8
to 11.7.
• 18 participating bank holding companies, Total risk-based capital ratio (%), Projected minimum has been revised from
11.7 to 11.6.
• 18 participating bank holding companies, Tier 1 leverage ratio (%), Projected Q4 2014 has been revised from 6.0 to 5.9.
• 18 participating bank holding companies, Tier 1 leverage ratio (%), Projected minimum has been revised from 6.0 to 5.9.

On p. 58, under Table C.9:
• Tier 1 capital ratio (%), Stressed capital ratios, Q4 2014 has been revised from 10.8 to 9.8.
•
•
•
•

Tier 1 capital ratio (%), Stressed capital ratios, Minimum has been revised from 8.4 to 7.5.
Total risk-based capital ratio (%), Stressed capital ratios, Q4 2014 has been revised from 13.8 to 12.8.
Total risk-based capital ratio (%), Stressed capital ratios, Minimum has been revised from 11.3 to 10.4.
Tier 1 leverage ratio (%), Stressed capital ratios, Q4 2014 has been revised from 6.2 to 5.6.

This and other Federal Reserve Board reports and publications are available online at
www.federalreserve.gov/publications/default.htm.
To order copies of Federal Reserve Board publications offered in print,
see the Board’s Publication Order Form (www.federalreserve.gov/pubs/orderform.pdf)
or contact:
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(e-mail) Publications-BOG@frb.gov

iii

Contents

Executive Summary ................................................................................................................. 1
Dodd-Frank Act Stress Testing ........................................................................................... 3
Supervisory Stress Tests ............................................................................................................. 3
Company-Run Stress Tests ......................................................................................................... 5

Severely Adverse Scenario ..................................................................................................... 7
Federal Reserve Supervisory Stress Test Framework and Model
Methodology ............................................................................................................................. 9
Analytical Framework .................................................................................................................. 9
Modeling Design and Implementation ........................................................................................ 11

Federal Reserve Supervisory Stress Test Results

......................................................... 15

Stressed Regulatory Capital Ratios ............................................................................................ 15
Projected Losses ...................................................................................................................... 17

Appendix A: Severely Adverse Scenario

........................................................................ 29

Data Notes ............................................................................................................................... 34

Appendix B: Models to Project Net Income and Stressed Capital ........................ 37
Losses on the Accrual Loan Portfolio ......................................................................................... 37
Loan-Loss Provisions for the Accrual Loan Portfolio ................................................................... 42
Other Losses ............................................................................................................................ 42
Pre-Provision Net Revenue ........................................................................................................ 46
Equity Capital and Regulatory Capital ........................................................................................ 47

Appendix C: BHC-Specific Results

................................................................................. 49

Executive Summary

The Federal Reserve expects large, complex bank
holding companies (BHCs) to hold sufficient capital
to continue lending to support real economic activity,
even under adverse economic conditions. Stress testing is one tool that helps bank supervisors measure
whether a BHC has enough capital to support its
operations throughout periods of stress. The Federal
Reserve previously highlighted the use of stress tests
as a means of assessing capital sufficiency under
stress during the 2009 Supervisory Capital Assessment Program (SCAP) and the 2011 and 2012 Comprehensive Capital Analysis and Review (CCAR)
exercises.1
In the wake of the financial crisis, the Congress
enacted the Dodd-Frank Wall Street Reform and
Consumer Protection Act (Dodd-Frank Act),2 which
requires the Federal Reserve to conduct an annual
stress test of large BHCs and all nonbank financial
companies designated by the Financial Stability
Oversight Council (FSOC) for Federal Reserve
supervision to evaluate whether they have sufficient
capital to absorb losses resulting from adverse economic conditions. The Dodd-Frank Act also requires
BHCs and other financial companies supervised by
the Federal Reserve to conduct their own stress tests.
The Federal Reserve adopted rules implementing
these requirements in October 2012. Under the rules,
18 BHCs are part of the Dodd-Frank Act supervisory stress tests this year (DFAST 2013).3
1

2
3

The CCAR is an annual exercise by the Federal Reserve to
ensure that institutions have robust, forward-looking capital
planning processes that account for their unique risks and sufficient capital to continue operations throughout times of economic and financial stress. As part of the CCAR, the Federal
Reserve evaluates institutions’ capital adequacy, internal capital
adequacy assessment processes, and their plans to make capital
distributions, such as dividend payments or stock repurchases,
and other actions that affect capital.
See 12 USC 5365(i)(1).
The 18 BHCs that participated in the 2013 Dodd-Frank Act
stress test are Ally Financial Inc.; American Express Company;
Bank of America Corporation; The Bank of New York Mellon
Corporation; BB&T Corporation; Capital One Financial Corporation; Citigroup, Inc.; Fifth Third Bancorp; The Goldman
Sachs Group, Inc.; JPMorgan Chase & Co.; KeyCorp; Morgan

This report describes the hypothetical, severely
adverse scenario designed by the Federal Reserve;
provides an overview of the analytical framework
and methods used to generate the projections of revenues, expenses, losses, and the resulting post-stress
capital ratios for each of the 18 BHCs; and discloses
the results of the 2013 Dodd-Frank Act supervisory
stress test. The Federal Reserve believes that disclosure of stress test results provides valuable information to market participants and the public, enhances
transparency, and promotes market discipline. The
projections provide a unique perspective on the
robustness of the capital positions of these firms
because they incorporate detailed information about
the risk characteristics and business activities of each
BHC and because they are estimated using a consistent approach across all the BHCs, providing comparable results across firms. The Federal Reserve also
believes that providing information about the methodology used to produce the results will offer useful
context to interpret those results.
The projections were calculated using input data provided by the 18 BHCs and a set of models developed
or selected by the Federal Reserve,4 based on a hypothetical, severely adverse macroeconomic and financial market scenario developed by the Federal
Reserve. The severely adverse scenario features a
deep recession in the United States, Europe, and
Japan, significant declines in asset prices and
increases in risk premia, and a marked economic
slowdown in developing Asia. The Federal Reserve
also applied a separate global market shock to six
BHCs with large trading, private equity, and counter-

Stanley; The PNC Financial Services Group, Inc.; Regions
Financial Corporation; State Street Corporation; SunTrust
Banks, Inc.; U.S. Bancorp; and Wells Fargo & Company.
Although MetLife, Inc. had participated in the 2009 SCAP and
previous CCAR exercises, it did not participate in the 2013
Dodd-Frank Act stress test because it was in the process of
deregistering as a bank holding company when the exercise
began and has now completed that process.
A list of providers of the proprietary models and data used by
the Federal Reserve in connection with DFAST 2013 is available
in appendix B.

DFAST 2013: Methodology and Results

party exposures from derivatives and financing transactions.5

Figure 1. Historical and stressed tier 1 common ratio
Percent

To make the projections of post-stress capital ratios
more comparable across BHCs, the projections
reflect assumptions about capital distributions prescribed in the Dodd-Frank Act stress test rule. Over
the nine-quarter planning horizon, each BHC maintains its common stock dividend payments at the
same level as the previous year, but repurchases and
issuance of common stock is assumed to be zero
except for common stock issuance associated with
expensed employee compensation.6
The results of these projections suggest that, in the
aggregate, the 18 BHCs would experience substantial
losses under the severely adverse scenario. Over the
nine quarters of the planning horizon, losses at the
18 BHCs under the severely adverse scenario are projected to be $462 billion, including losses across loan
portfolios, losses on securities held in the BHCs’
investment portfolios, trading and counterparty
credit losses from the global market shock, and other
5

The six BHCs subject to the global market shock are Bank of
America Corporation; Citigroup, Inc.; The Goldman Sachs
Group, Inc.; JPMorgan Chase & Co.; Morgan Stanley; and
Wells Fargo & Company. See 12 CFR 252.134(b); see also
12 CFR 252.144(b)(2)(i).
See 12 CFR 252.146(b)(2).

12.0
10.0
8.0
6.0
4.0
2.0

Stressed, Q4 2014

Actual, Q3 2012

Actual, Q4 2011

Actual, Q4 2010

Actual, Q4 2009

0.0
Actual, Q4 2008

The models project revenues, expenses, losses, and the
resulting post-stress capital ratios for each BHC over
a nine-quarter planning horizon extending through
the end of 2014. The Federal Reserve’s projections
should not be interpreted as expected or likely outcomes for these firms, but rather as possible results
under hypothetical, severely adverse conditions. These
projections incorporate a number of conservative
modeling assumptions, but do not make explicit
behavioral assumptions about the possible actions of
a BHC’s creditors and counterparties in the scenario,
except through the severely adverse scenario’s characterizations of financial asset prices and economic
activity.

Note: Aggregate capital ratios for 18 participating bank holding companies (BHCs).
Post-stress estimates are supervisory estimates under the severely adverse
scenario.
The tier 1 common ratio in the fourth quarter of 2008 includes the tier 1 common
capital and risk-weighted assets for Ally Financial Inc. as of the first quarter of
2009, as Ally was not a Y-9C filer in the fourth quarter of 2008.

losses. Projected net revenue before provisions for
loan and lease losses (pre-provision net revenue, or
PPNR) at the 18 BHCs over the nine quarters of the
planning horizon under the severely adverse scenario
is $268 billion, which is net of losses related to
operational-risk events and mortgage repurchases, as
well as expenses related to disposition of owned real
estate of $101 billion. Taken together, the high projected losses and low projected PPNR at the 18
BHCs results in projected net income before taxes of
-$194 billion.
These net income projections result in substantial
projected declines in regulatory capital ratios for
nearly all of the BHCs under the severely adverse scenario. As illustrated in figure 1, the aggregate tier 1
common ratio would fall from an actual 11.1 percent
in the third quarter of 2012 to a post-stress level of
7.7 percent in the fourth quarter of 2014, including
assumed capital actions for the 18 BHCs.

Dodd-Frank Act Stress Testing

The Dodd-Frank Act requires the Federal Reserve to
conduct an annual supervisory stress test of BHCs
with $50 billion or more in total consolidated assets
and nonbank financial companies designated by the
FSOC for Federal Reserve supervision (collectively,
“covered companies”). The Dodd-Frank Act also
requires covered companies to conduct their own
stress tests (company-run stress tests) semiannually.7
Together, the Dodd-Frank Act supervisory stress
tests and the company-run stress tests are intended to
provide BHC management and boards of directors,
the public, and supervisors with forward-looking
information to help identify downside risks and the
potential effect of adverse conditions on capital
adequacy of these large banking organizations. The
Federal Reserve adopted rules implementing these
requirements in October 2012.
Under the implementation phase-in provisions of the
Federal Reserve’s Dodd-Frank stress test rules, only
the 18 BHCs that previously participated in the
SCAP are required to conduct company-run stress
tests during the current stress test cycle that began in
October 2012.8 Similarly, the Federal Reserve has
conducted supervisory stress tests on only these 18
BHCs for DFAST 2013. Both sets of stress tests are
also integrated into the Federal Reserve’s assessment
7

The Dodd-Frank Act requires all financial companies that have
more than $10 billion in total consolidated assets and are regulated by a Federal financial regulatory agency to conduct capital
stress tests at least annually. The Federal Reserve finalized those
requirements for BHCs with between $10 billion and $50 billion
in assets and state member banks and savings and loan holding
companies with over $10 billion in assets on October 9, 2012.
See 12 CFR part 225, subpart H.
Six state member bank subsidiaries of BHCs that participated
in SCAP are also required to conduct stress tests this year under
the Federal Reserve’s “Annual Company-Run Stress Test
Requirements for Banking Organizations with Total Consolidated Assets over $10 Billion Other Than Covered Companies”
(12 CFR part 252, subpart H). Those banks are Bank of New
York Mellon; Fifth Third Bank; Goldman Sachs Bank USA;
Regions Bank; State Street Bank and Trust Company; and SunTrust Bank.

of capital adequacy under CCAR. Important differences between the Dodd-Frank Act supervisory
stress tests and the CCAR post-stress capital analysis
are outlined in box 1.
To provide context to the Federal Reserve’s DoddFrank Act supervisory stress test results, the following sections contain an overview of the Federal
Reserve’s Dodd-Frank Act stress test rules, focusing
on the process for the supervisory stress tests and the
requirements for company-run stress tests for covered
companies.

Supervisory Stress Tests
Under the Dodd-Frank Act stress test rules, the Federal Reserve conducts annual supervisory stress tests
to evaluate whether a covered company has the capital, on a total consolidated basis, necessary to absorb
losses and continue its operations by maintaining
ready access to funding, meeting its obligations to
creditors and other counterparties, and continuing to
serve as a credit intermediary under adverse economic and financial conditions. As part of this supervisory stress test for each covered company, the Federal Reserve projects revenue, expenses, losses, and
resulting post-stress capital levels, regulatory capital
ratios, and the tier 1 common ratio under three scenarios (baseline, adverse, and severely adverse), using
data as of September 30.
The Federal Reserve generally uses a common set of
scenarios for all covered companies in the supervisory stress test. However, the Federal Reserve may
use additional scenarios or components of scenarios
for all or a subset of the covered companies to capture salient sources of risk, and these scenarios may
use data from dates other than the end of the third
quarter. In DFAST 2013, large, complex BHCs with
significant trading activities are subject to a global

DFAST 2013: Methodology and Results

Box 1. Dodd-Frank Act Supervisory Stress Tests and
the CCAR Post-Stress Capital Analysis
While closely related, there are some important differences between the Dodd-Frank Act supervisory
stress tests and the CCAR post-stress capital analysis. The projections of pre-tax net income from the
Dodd-Frank Act supervisory stress tests are direct
inputs to the CCAR post-stress capital analysis. The
primary difference between the Dodd-Frank Act
supervisory stress tests and the CCAR post-stress
capital analysis is the capital action assumptions
that are combined with these projections to estimate
post-stress capital levels and ratios.
Capital Action Assumptions for the Dodd-Frank
Act Supervisory Stress Tests
To project post-stress capital ratios for the DoddFrank Act supervisory stress tests, the Federal
Reserve uses a standardized set of capital action
assumptions that are specified in the Dodd-Frank
Act stress test rules.1 Common stock dividend payments are assumed to continue at the same level as
the previous year. Scheduled dividend, interest, or
principal payments on any other capital instrument
eligible for inclusion in the numerator of a regulatory
capital ratio are assumed to be paid. The assumptions are that repurchases of common stock are
zero. The capital action assumptions do not include
issuance of new common stock, preferred stock, or
other instrument that would be included in regulatory
capital, except for common stock issuance associated with expensed employee compensation.2
1

Capital Actions for CCAR
In contrast, for the CCAR post-stress capital analysis, the Federal Reserve uses BHCs’ planned capital actions, and assesses whether a BHC would be
capable of meeting supervisory expectations for
minimum capital ratios even if stressful conditions
emerged and the BHC did not reduce planned capital distributions.
As a result, post-stress capital ratios projected for
the Dodd-Frank Act supervisory stress tests should
be expected to differ significantly from those for the
CCAR post-stress capital analysis. For example, if a
BHC includes a dividend cut in its planned capital
actions, its post-stress capital ratios projected for the
CCAR capital analysis could be higher than those
projected for the Dodd-Frank Act supervisory stress
tests. Conversely, if a BHC includes significant dividend increases, repurchases, or other actions that
deplete capital in its planned capital actions, the
post-stress capital ratios for the CCAR could be
lower.

adjustment, market conditions, or other regulatory approvals will
not be reflected in a company’s projected regulatory capital for
the purpose of the company-run stress tests because of the
uncertainty of these actions. Accordingly, under the rule, a company must assume in the second through ninth quarters of the
planning horizon no redemption or repurchase of any capital
instrument eligible for inclusion in the numerator of a regulatory
capital ratio. See 12 CFR 252.146(b)(2)(iii). The Federal
Reserve clarified in subsequent guidance that, for similar reasons, a company should assume that it will not issue any new
common stock, preferred stock, or other instrument that would
be included in regulatory capital in the second through ninth
quarters of the planning horizon, except for common stock issuances associated with expensed employee compensation.

In order to make the results of its supervisory stress test comparable to the company-run stress tests, the Federal Reserve uses
the same capital action assumptions as those required for the
company-run stress tests, outlined in the Dodd-Frank stress test
rules. See 12 CFR 252.146(b)(2).
The Dodd-Frank Act stress test rule for covered companies
assumes that future capital actions that are subject to future

market shock that reflects general market stress and
heightened uncertainty, which affects trading positions and elevates counterparty credit risk.
The Dodd-Frank Act codified the Federal Reserve’s
practice of disclosing a summary of the results of its
supervisory stress test. In this paper, the Federal
Reserve is disclosing the results of the 2013 DoddFrank Act supervisory stress tests conducted under
the severely adverse scenario, including firm-specific
results based on the projections made by the Federal

444

Reserve of each BHC’s revenues, expenses, losses,
and post-stress capital ratios over the planning horizon.9

For DFAST 2013, similar to the public disclosure following
CCAR in early 2012, the Federal Reserve is only disclosing
results under the severely adverse scenario for each company. As
the Federal Reserve implements the Dodd-Frank Act stress testing requirements, it intends to evaluate whether public disclosure of the results of the adverse and baseline would assist in
informing the company and market participants about the condition of the banking organization.

March 2013

Company-Run Stress Tests
As required by the Dodd-Frank Act, the Federal
Reserve’s stress test rules require covered companies
to conduct two company-run stress tests each year. In
conducting the “annual” test, a covered company
uses data as of September 30 and reports its stress
test results to the Federal Reserve by January 5. In
addition, a covered company must conduct a “midcycle” test and report the results to the Federal
Reserve by July 5. The Dodd-Frank Act stress test
rules align the timing of annual company-run stress
tests with the annual supervisory stress tests of covered companies.
In their annual stress tests, covered companies subject
to the Dodd-Frank Act stress test rules must use the
scenarios provided by the Federal Reserve. Each year,
the Federal Reserve will provide at least three scenarios—baseline, adverse, and severely adverse—that
are identical to the scenarios the Federal Reserve uses
in the annual supervisory stress tests of covered com-

panies.10 By providing a common set of scenarios to
all firms, the results of company-run and supervisory
stress tests for all 18 BHCs will be based on comparable underlying assumptions. To further enhance
comparability, the supervisory stress tests and
company-run stress tests conducted under the DoddFrank stress test rules use the same set of capital
action assumptions. According to these assumptions,
over the nine-quarter planning horizon, each BHC
maintains its common stock dividend payments at
the same level as the previous year; scheduled dividend, interest or principal payments on any other
capital instrument eligible for inclusion in the
numerator of a regulatory capital ratio are assumed
to be paid; but repurchases of such capital instruments and issuance of stock is assumed to be zero.
Finally, each covered company must publicly disclose
a summary of the results of its company-run stress
test under the severely adverse scenario provided by
the Federal Reserve.

Under the stress test rules, the Federal Reserve will provide the
scenarios to companies no later than November 15 each year.
See 12 CFR 252.144(b)(1); 12 CFR 252.154(b)(1).

Severely Adverse Scenario

4.0

2.0

Q3 2015

Q1 2015

Q3 2014

Q1 2014

Q3 2013

Q1 2013

Q3 2012

-8.0
Q1 2012

-6.0

-8.0
Q3 2011

-4.0

-6.0
Q1 2011

-4.0

Q3 2010

-2.0

Q1 2010

0.0

-2.0

Q3 2009

0.0

Source: Bureau of Economic Analysis and Federal Reserve assumptions in the
severely adverse scenario.

Figure 3. Unemployment rate in the severely adverse
scenario, Q1 2009–Q4 2015
Percent

Percent

Q3 2015

Q1 2015

6.0
Q3 2014

6.0
Q1 2014

9.0

Q3 2013

9.0

Q1 2013

12.0

Q3 2012

12.0

Q1 2012

15.0

Q3 2011

15.0

Q1 2011

See Board of Governors of the Federal Reserve System (2012),
“2013 Supervisory Scenarios for Annual Stress Tests Required
under the Dodd-Frank Act Stress Testing Rules and the Capital
Plan Rule” (Washington: Board of Governors, November 15),
www.federalreserve.gov/newsevents/press/bcreg/20121115a.htm
for additional information and for the details of the supervisory
baseline and supervisory adverse scenarios.

6.0

4.0

Q3 2010

Percent
Q/Q seasonally adjusted growth rates annualized

Q1 2010

Figures 2 through 6 illustrate the hypothetical trajectories for some of the key variables describing U.S.
economic activity and asset prices as well as global
economic growth under the severely adverse scenario.
As the figures show, real GDP declines nearly 5 percent between the third quarter of 2012 and the end of
2013; over this period, the unemployment rate rises
to 12 percent, and the four-quarter percent change in
the consumer price index (CPI) decelerates to 1 percent. Equity prices fall more than 50 percent over the

Percent

6.0

Q1 2009

The severely adverse scenario includes trajectories for
26 variables. These include 14 variables that capture
economic activity, asset prices, and interest rates in
the U.S. economy and financial markets and three
variables (real GDP growth, inflation, and the U.S./
foreign currency exchange rate) in each of four countries or country blocks (the euro area, the United
Kingdom, developing Asia, and Japan).

Figure 2. Real GDP growth rate in the severely adverse
scenario, Q1 2009–Q4 2015

Q3 2009

It is important to note that the severely adverse scenario is not a forecast, but rather a hypothetical scenario designed to assess the strength of banking organizations and their resilience to an adverse economic
environment. The severely adverse scenario represents
an outcome in which the U.S. economy experiences a
significant recession and financial market stress, and
economic activity in other major economies also contracts significantly.

course of the recession and, correspondingly, the
equity market volatility index jumps from about 21 in
the third quarter of 2012 to more than 70 at the start
of the scenario. House prices decline more than
20 percent by the end of 2014, and commercial real
estate prices fall by a similar amount. The international component of the severely adverse scenario

Q1 2009

On November 15, 2012, the Federal Reserve released
three supervisory stress test scenarios: baseline,
adverse, and severely adverse.11 This section describes
the severely adverse scenario that is the basis for the
projections contained in this report.

Source: Bureau of Labor Statistics and Federal Reserve assumptions in the
severely adverse scenario.

DFAST 2013: Methodology and Results

Q3 2015

Q1 2015

Q3 2014

Q1 2014

Q3 2013

Q1 2013

Q3 2012

Q1 2012

100.0

Source: CoreLogic (seasonally adjusted by Federal Reserve) and Federal Reserve
assumptions in the severely adverse scenario.

Figure 6. Real GDP growth in four country/country block
areas in the severely adverse scenario, Q1 2009–Q4 2015
Percent

20
15
10
5
0
-5
-10
-15
-20

Percent

20
15
10
5
0
-5
-10
-15
-20

Q/Q seasonally adjusted growth rates annualized

Euro area real GDP growth
Japan real GDP growth

Q3 2015

Q1 2015

Q3 2014

Q1 2014

Q3 2013

Q1 2013

Q3 2012

U.K. real GDP growth
Developing Asia real GDP growth

Q1 2012

Q3 2011

The Federal Reserve CCAR 2012 macroeconomic scenarios
were included in the “Federal Reserve System Comprehensive
Capital Analysis and Review: Summary Instructions and Guidance,” published November 22, 2011; see www.federalreserve
.gov/newsevents/press/bcreg/20111122a.htm.
See 12 CFR 252.144(b)(2)(i).
See Board of Governors of the Federal Reserve System (2013),
“Federal Reserve Board Announces Release Dates for Results
from Supervisory Stress Tests and from the Comprehensive
Capital Analysis and Review (CCAR),” press release (Washing-

ton: Board of Governors, January 28), www.federalreserve.gov/
newsevents/press/bcreg/20130128a.htm.

Q1 2011

On November 19, 2012, the Federal Reserve provided
six BHCs with large trading, private equity, and
counterparty exposures from derivatives and financing transactions with a global market shock to
include in their severely adverse scenario.13 The
global market shock is a set of one-time, hypothetical
shocks to a broad range of risk factors. Generally,
these shocks involve large and sudden changes in
asset prices, rates, and spreads, reflecting general
market stress and heightened uncertainty.14

The global market shock is generally based on the
price and rate movements that occurred in the second
half of 2008, a period that featured severe market
stress and the failure of a major, globally active
financial institution. In addition, this global market
shock incorporates hypothetical euro-zone-based
shocks, including sharp increases in certain government yields, widening corporate spreads and sovereign credit default swap (CDS) spreads, and large
depreciation of the euro against major currencies.
Although these shocks are felt across the euro zone in
the scenario, the severity of the shocks varies across
countries within the euro zone, with more pronounced effects experienced by periphery countries.

Q3 2010

The severely adverse scenario is similar in severity to
the 2012 CCAR supervisory stress scenario.12 The
main qualitative difference between this year’s
severely adverse scenario and last year’s supervisory
stress scenario is a much more substantial slowdown
in developing Asia.

110.0

100.0

Q1 2010

features recessions in the euro area, the United Kingdom, and Japan and below-trend growth in developing Asia.

120.0

110.0

Q3 2009

Source: Dow Jones and Federal Reserve assumptions in the severely adverse
scenario.

130.0

120.0

Q3 2015

Q1 2015

Q3 2014

Q1 2014

Q3 2013

Q1 2013

Q3 2012

Q1 2012

Q3 2011

5000.0
Q1 2011

5000.0
Q3 2010

7500.0

Q1 2010

7500.0

Q3 2009

10000.0

Q1 2009

10000.0

130.0

Q3 2011

12500.0

140.0

Q1 2011

12500.0

150.0

140.0

Q3 2010

15000.0

160.0

150.0

Q1 2010

15000.0

160.0

Q3 2009

17500.0

Figure 5. National House Price Index in the severely
adverse scenario, Q1 2009–Q4 2015

Q1 2009

Figure 4. Dow Jones Stock Market Index, end of quarter in
the severely adverse scenario, Q1 2009–Q4 2015

Q1 2009

Source: Federal Reserve calculations based on official sector sources and Federal
Reserve assumptions in the severely adverse scenario. Q3 2012 data based on
Federal Reserve calculations using available data as of November 13, 2012.

Federal Reserve Supervisory Stress Test
Framework and Model Methodology

Analytical Framework
The effect of the severely adverse scenario on the
regulatory capital ratios of the 18 BHCs is estimated
by projecting the net income for each BHC over a
nine-quarter planning horizon ending in the fourth
quarter of 2014. Projected net income is combined
with the capital action assumptions prescribed in the
Federal Reserve’s Dodd-Frank Act stress test rules to
project changes in equity capital, which in turn determine changes in regulatory capital measures. This
approach is consistent with U.S. generally accepted
accounting principles (GAAP) and regulatory capital
rules, and provides a perspective on the capital of the
BHCs and on the primary determinants of the projected changes in capital over time: earnings and
capital actions.
Projected net income for the 18 BHCs is generated
from individual projections of revenue, expenses, and
various types of losses and provisions that flow into
pre-tax net income, including loan losses and changes
in the allowance for loan and lease losses (ALLL);
losses on investment securities; losses generated by
operational-risk events; expenses related to the disposition of foreclosed properties; expenses related to
demands by mortgage investors to repurchase loans
deemed to have breached representations and warranties or related to litigation (“mortgage repurchase/
put-back losses”); and, for BHCs with large trading
operations, losses on trading and counterparty positions resulting from the global market shock.
Projected pre-tax net income, in turn, flows into a
calculation of regulatory capital measures that
accounts for taxes and deductions that limit the recognition of certain intangible assets and impose
other restrictions, as specified in current U.S. regulatory capital guidelines.15 Figure 7 illustrates the
framework used to calculate changes in net income
and regulatory capital.
15

See generally 12 CFR part 225, appendix A.

The framework begins with a projection of PPNR,
which equals projected net interest income plus noninterest income minus non-interest expense. Consistent with U.S. GAAP, the PPNR projection incorporates projected losses generated by operational-risk
events such as fraud, computer system or other operating disruptions, or employee lawsuits; mortgage
repurchase losses; and expenses related to the disposition of foreclosed properties (other real estate
owned (OREO) expenses).
The PPNR projection flows into the projection of
pre-tax net income, which equals the PPNR projection, plus other revenue, minus provisions to the
ALLL, losses on securities, and losses on trading and
counterparty positions from the global market shock
(for the six BHCs with large trading operations), and
losses on loans held for sale and measured under the
fair-value option. Net income projections also incorporate extraordinary items, goodwill impairment,

Figure 7. Projecting net income and regulatory capital
Net interest income + non-interest income - non-interest expense
= pre-provision net revenue (PPNR)
Note: PPNR includes income from mortgage servicing rights and losses from
operational-risk events, mortgage put-back losses, and OREO expenses

PPNR + other revenue - provisions - AFS/HTM securities losses trading and counterparty losses - other losses (gains)
= pre-tax net income
Note: Change in the allowance for loan and lease losses + net charge-offs
= provisions

Pre-tax net income - taxes + extraordinary items net of taxes
= after-tax net income

After-tax net income - net distributions to common and preferred shareholders
and other net reductions to shareholder’s equity from DFAST assumptions
= change in equity capital

Change in equity capital - deductions from regulatory capital + other additions
to regulatory capital
= change in regulatory capital

DFAST 2013: Methodology and Results

income attributable to minority interests, and other
losses under the severely adverse scenario.
Provisions for loan and lease losses equal projected
loan losses for the quarter plus the amount needed
for the ALLL to be at an appropriate level at the end
of the quarter, which is a function of projected future
loan losses. The amount of provisions over and
above loan losses may be negative, representing a
drawdown of the ALLL (an ALLL release, increasing net income), or positive, representing a need to
build the ALLL (an additional provision, decreasing
net income) during the quarter.
Projected loan losses for the quarter are estimated
separately for different categories of loans based on
the type of obligor (e.g., consumer or commercial
and industrial), collateral (e.g., residential real estate,
commercial real estate), loan structure (e.g., revolving
credit lines), and accounting treatment (accrual or
fair value). These categories generally follow the
major regulatory report classifications, though some
loss projections are made for more granular loan categories than those included on BHC regulatory
reports.16
These loss projections follow U.S. GAAP and regulatory guidelines and thus incorporate any differences
in the way these guidelines recognize income and
losses based upon where assets are held on the BHCs’
balance sheets. As a result, losses projected for similar or identical assets held in different portfolios can
sometimes differ. For example, losses on loans held in
accrual portfolios equal credit losses due to failure to
pay obligations (cash flow losses resulting in net
charge-offs). For similar loans that are held for sale,
projected losses represent the change in the market
value on the underlying asset under the severely
adverse scenario.
Losses on securities held in the available-for-sale
(AFS) or held-to-maturity (HTM) accounts are projected other-than-temporary impairments (OTTI) for
these positions. Consistent with U.S. GAAP, OTTI
projections incorporate other-than-temporary differences between book value and fair value due to credit
impairment, but not differences reflecting changes in
liquidity or market conditions.
16

See Consolidated Financial Statements for Bank Holding Companies (FR Y-9C).

As with the accrual loan portfolio, loss projections
for different categories of securities are made based
on obligor, collateral or underlying cash flow, and
security structure. These categories include various
types of securitized obligations (e.g., commercial and
residential mortgage-backed securities), corporate
bonds, municipal bonds, and sovereign bonds.
For the six BHCs with large trading operations,
losses on trading, private equity positions, and counterparty exposures from derivatives and financing
transactions are projected assuming an instantaneous
re-pricing of positions under a global market shock.
The global market shock presumes a set of severe,
instantaneous changes in market rates, prices, and
volatilities that are in effect layered over the losses
from changes in financial market variables contained
elsewhere in the severely adverse scenario. Losses
related to the global market shock are assumed to
occur in the first quarter of the planning horizon.
These losses include mark-to-market losses on each
of the six BHCs’ trading and private equity positions,
changes in credit valuation adjustments (CVA) for
counterparty exposures, and incremental defaultrelated losses on trading and counterparty exposures
that may result from the global market shock. No
subsequent recoveries on these positions are
assumed, nor are there offsetting changes such as
reductions in compensation or other expenses in
reaction to the global market shock.
The Federal Reserve’s forward-looking projections of
income and losses may include the effects of planned
mergers, acquisitions, or divestitures. The inclusion
of the effects of such planned actions does not—and
is not intended to—express a view on the merits of
such proposals and is not an approval or nonobjection to them.
After-tax net income (or loss) is calculated by applying a consistent tax rate to pre-tax net income (or
loss) for all BHCs; the effect of changing this tax rate
assumption on the post-stress tier 1 common ratio is
discussed in box 2. Along with each BHC’s assumed
capital actions under the Federal Reserve’s DoddFrank Act stress test rules, after-tax net income is the
primary determinant of projected changes in equity
capital, which in turn determines projected changes
in the regulatory capital measures. Capital ratios are
calculated using average total assets and riskweighted assets that are based on projections made
by the BHCs under the severely adverse scenario.

March 2013

Box 2. Tier 1 Common Results Not Materially Sensitive to Tax Rates
After-tax net income (or loss) is calculated by applying a consistent tax rate to pre-tax net income (or
loss) for all BHCs. This assumed tax rate is also
used to determine certain aspects of the allowable
deferred tax asset (DTA) included in regulatory
capital.
Changing the tax rate assumption has a limited
effect on minimum projected capital levels. As
shown in figure A, adjusting the assumed tax rate
Figure A. Ending aggregate tier 1 common levels using
different tax rates

by 15 percentage points in either direction leads to
only a small change in aggregate tier 1 common
capital at the end of the planning horizon. In addition, the minimum post-stress tier 1 common ratio
changed less than 10 basis points for most BHCs
(figure B). The effect of changing the tax rate
assumption is limited because nearly all BHCs participating in DFAST 2013 are in a cumulative net
loss position over the planning horizon. Net losses
are reduced by the tax rate, but these “tax benefits”
are largely reversed due to restrictions on deferred
tax assets under current regulatory capital rules.

$600

Figure B. Change in minimum tier 1 common ratio
when tax rate is adjusted by 15 pps

Billions of dollars

Number of BHCs

+2%

Decrease tax rate
by 15 pps
Increase tax rate
by 15 pps

-2%

8
5

4
2
0

$450
Decrease tax rate
by 15 pps

Supervisory tax rate

Increase tax rate
by 15 pps

Decline
> 25 bps

Decline
10 - 25 bps

Decline
0 - 10 bps

Increase
0 - 10 bps

3
1
Increase
> 10 bps

Source: Federal Reserve projections in the severely adverse scenario.

“Pps” is percentage points.

“Bps” is basis points; “pps” is percentage points.

Modeling Design and
Implementation
The Federal Reserve’s projections of revenue,
expenses, and various types of losses and provisions
that flow into pre-tax net income are based on data
provided by the 18 BHCs participating in DFAST
2013 and on models developed or selected by Federal
Reserve staff and reviewed by an independent group
of Federal Reserve economists and analysts and academics.17 The models are intended to capture how
the revenues, expenses, and losses of each BHC are
affected by the macroeconomic and financial conditions described in the severely adverse scenario and
by characteristics of the BHCs’ loans and securities
portfolios; trading, private equity, and counterparty

exposures from derivatives and financing transactions; business activities; and other relevant factors.18

The FR Y-14 Report
The Federal Reserve collects extensive data on
PPNR, loans, securities, trading and counterparty
risk, and losses related to operational-risk events on
the FR Y-14 report, which includes a set of schedules
collected in monthly, quarterly, or annual frequencies
(FR Y-14M, FR Y-14Q, and FR Y-14A schedules).19
Each of the 18 BHCs submitted FR Y-14M and FR
Y-14Q schedules (as of September 30, 2012) in October and November of 2012 and submitted FR Y-14A
schedules on January 7, 2013. These data, along with
data collected in other regulatory reports and other

18
17

For more, see Board of Governors of the Federal Reserve
System (2012), “Federal Reserve Announces the Formation of
the Model Validation Council,” press release (Washington:
Board of Governors, April 20), www.federalreserve.gov/
newsevents/press/bcreg/20120420a.htm.

444

In some cases, the loss models estimated the effect of local-level
macroeconomic data, which were projected based on their historical covariance with national variables included in the
severely adverse scenario.
The FR Y-14 schedules are available at www.federalreserve.gov/
apps/reportforms/default.aspx.

DFAST 2013: Methodology and Results

proprietary third-party data, were used in the supervisory models of revenues, expenses, and losses.
Quarterly loan losses are projected using information
collected on the FR Y-14 about the BHCs’ loan portfolios, including borrower characteristics, collateral
characteristics, characteristics of the loans or credit
facilities, amounts outstanding and yet to be drawn
down (for credit lines), payment history, and current
payment status. Loan portfolio data are reported
either at a monthly frequency (for domestic retail
credit card and residential mortgages) or at a quarterly frequency (all other retail and wholesale portfolios). Data are collected on individual loans or credit
facilities for wholesale loan, domestic retail credit
card, and residential mortgage portfolios and are collected on segments of the loan portfolios for other
domestic and international retail portfolios (for
example, segments defined by loan-to-value (LTV)
ratio, geographic location, and borrower credit
score). BHC-projected balances reported on the FR
Y-14 are also used to project loan losses, and where
applicable, incremental loan balances were calculated
based on these projected balances.
Over the past year, several changes have been made
to the FR Y-14 report, which have allowed the Federal Reserve to estimate expected loan losses using
more granular, loan-specific information. For
example, in mid-2012, the Federal Reserve began collecting monthly loan-level data on credit card
accounts and on first- and second-lien mortgages on
the FR Y-14M. The FR Y-14M replaced a quarterly,
segment-level data collection and allows the Federal
Reserve to estimate expected losses on each loan in
the BHC’s portfolio, based on the individual characteristics of the loan.
Losses on securities held in the AFS and HTM portfolios are estimated using securities data collected
quarterly at the individual security (CUSIP) level,
including the amortized cost, market value, and any
OTTI taken on the security to date.
BHCs were required to submit detailed loan and
securities information for all material portfolios,
where the portfolio is deemed to be “material” if it
exceeds either 5 percent of tier 1 capital or $5 billion.
The portfolio categories are defined in the FR
Y-14M and Y-14Q instructions. For portfolios falling
below these thresholds, the BHCs had the option to
submit or not submit the detailed data.

Portfolios for which the Federal Reserve did not
receive detailed data were assigned a loss rate equal
to a high percentile of the loss rates projected for
BHCs that did submit data for that category of loan
or security. The Federal Reserve made considerable
efforts to validate BHC-reported data, and requested
multiple resubmissions as needed. However, in certain instances, BHC-reported data were still not sufficient or were deemed unreliable to produce supervisory estimates. In such instances, the BHC received a
loss rate at or near the 90th percentile of the loss
rates projected for the relevant loan type at the BHCs
that did provide reliable data. In some instances
where certain data elements were reported as missing
values, these missing data were assigned conservative
values (e.g., high LTV values or low credit scores)
based on the remainder of the portfolio.20 These
assumptions are intended to reflect a conservative
view of the risk characteristics of the portfolios,
given insufficient information to make more risksensitive projections.
Losses related to the global market shock, including
losses related to derivatives and other counterparty
exposures, are projected using information on trading, financing, and derivatives positions, private
equity holdings, and certain other assets subject to
fair-value accounting held by BHCs with large trading operations. The FR Y-14 schedules collect BHCestimated sensitivities of these positions to the set of
risk factors specified by the Federal Reserve, including changes in a wide range of U.S. and global market rates and asset prices as well as volatilities of
those rates and prices. The specific risk factors are
those judged to be most relevant to the positions held
by the BHCs. The schedules also collect information
on the BHC’s counterparty exposures revalued with
respect to these risk factors, both for segments of
counterparties and for individual large counterparties. These data, which are collected for positions in
the trading and private equity portfolios held by the
BHCs and counterparty exposures, are as of market
close November 14, 2012.
Most components of PPNR are projected using data
on historical revenues and operating and other noncredit-related expenses reported on the FR Y-9C
20

The method of applying conservative assumptions to certain
risk segments was used only in cases in which the data-related
issues were isolated in such a way that the remainder of the
portfolio could be readily modeled using the existing supervisory framework.

March 2013

report, which contains consolidated income statement and balance sheet information for each BHC,
including components of interest income, noninterest income, and non-interest expenses.21 Separate data are collected on the FR Y-14 about mortgage loans that were sold or securitized and the
BHCs’ historical losses related to operational-risk
events to project losses from mortgage repurchase
and operational-risk events under the severely
adverse scenario.
Finally, changes in regulatory capital ratios over the
planning horizon are calculated using data collected
on the BHCs’ projections of risk-weighted assets and
balance sheet composition.

Loss, Revenue, and Expense Models
The data collected from the BHCs, along with data
collected in other regulatory reports; proprietary
industry data; and the variables defining the severely
adverse scenario, are inputs into a series of models
used to project losses, revenues, and expenses for each
BHC over the planning horizon. These models were
either developed by Federal Reserve analysts and
economists or are third-party models used by Federal
Reserve staff. In some cases, the severely adverse scenario projections of certain types of losses made by
the Federal Reserve use as an input sensitivities generated by the BHCs using their internal riskmeasurement models.
In general, the models were developed using pooled
historical data from many financial institutions,
either supervisory data collected by the Federal
Reserve or proprietary industry data. As a result, the
estimated parameters reflect the typical or industryaverage response to variation in the macroeconomic
and financial market variables and portfolio-specific
and instrument-specific characteristics.
This approach reflects not only the difficulty of estimating separate, statistically robust models for each
of the 18 BHCs, but also the desire not to assume
that historical BHC-specific results will prevail in the
future when those results cannot be explained by
consistently observable variables incorporated into a
robust statistical model. Thus, BHC-specific factors
are incorporated through the detailed portfolio and
business activity data that are inputs to the models,
but the estimated relationships between these vari21

The FR Y-9C report is available at www.federalreserve.gov/
apps/reportforms/default.aspx.

ables, the macroeconomic and financial market factors defined in the severely adverse scenario, and revenue or losses are the same for all BHCs. This means
that the severely adverse scenario projections made
by the Federal Reserve will not necessarily match or
mirror similar projections made by individual BHCs,
which will incorporate diverse approaches to capturing the effect of portfolio characteristics and economic factors.
The Federal Reserve deviated from the industry-wide
modeling approach only in a very limited number of
cases where the historical data used to estimate the
model were not sufficiently granular to reliably capture cross-firm differences in loss, expense, or
revenue-generating characteristics. In these cases,
BHC-specific indicator variables (“fixed effects”)
were included in the models.
The models developed internally by the Federal
Reserve draw on economic research and analysis and
industry practice in modeling the impact of borrower, instrument, and collateral characteristics and
macroeconomic factors on revenue, expenses, and
losses. The approaches build on work done by the
Federal Reserve in the SCAP and the CCAR in 2011
and 2012. But in some cases, they represent significant refinement and advancement of that work,
reflecting advances in modeling technique, richer and
more detailed data over which to estimate the models, and longer histories of performance in both
adverse and more benign economic settings. In a few
cases, these efforts resulted in new models that were
implemented in DFAST 2013. These new models and
other models used are described in greater detail in
appendix B. Overall, the Federal Reserve continues to
move toward an overall modeling framework that is
increasingly independent of BHC projections.
The models were reviewed by an independent model
review team comprised of economists and analysts
from across the Federal Reserve System, with a focus
on the design and estimation of the models. Model
reviewers were primarily Federal Reserve subject
matter experts who were not involved in model development and who reported to a different oversight
group than model developers. In addition, Federal
Reserve analysts developed industry-wide loss and
PPNR projections capturing the potential revenue
and losses of the banking industry as a whole in a
stressed macroeconomic environment, for use as reference points in assessing model outputs across the
18 BHCs.

Federal Reserve Supervisory
Stress Test Results

This section describes the Federal Reserve’s severely
adverse scenario projections of losses, revenue,
expenses, and capital positions for the 18 BHCs participating in DFAST 2013. The projections presented
in this section are based on the severely adverse scenario developed by the Federal Reserve.
The results include projections of post-stress capital
ratios for each of the 18 BHCs over the nine-quarter
planning horizon spanning the fourth quarter of
2012 to the end of 2014. These ratios include the
ratio of the common equity component of tier 1
capital to risk-weighted assets (the tier 1 common
ratio), the ratio of tier 1 capital to risk-weighted
assets (the tier 1 capital ratio), the ratio of total regulatory capital to risk-weighted assets (the total riskbased capital ratio), and the ratio of tier 1 capital to
average assets (the tier 1 leverage ratio).22 The results
also include projections of the components of net
income before taxes, including revenues, provisions,
and losses, as well as components of loan losses.
The Federal Reserve’s projections assume the capital
actions prescribed in the Dodd-Frank stress test
rules. According to these assumptions, over the ninequarter planning horizon, each BHC maintains its
common stock dividend payments at the same level
as the previous year; scheduled dividend, interest, or
principal payments on any other capital instrument
eligible for inclusion in the numerator of a regulatory
capital ratio are assumed to be paid; but repurchases
22

Tier 1 capital, as defined in the Federal Reserve's Risk-Based
Capital Adequacy Guidelines, is composed of common and
non-common equity elements, some of which are subject to limits on their inclusion in tier 1 capital. See 12 CFR part 225,
appendix A, section II.A.1. These elements include common
stockholders' equity, qualifying perpetual preferred stock, certain minority interests, and trust preferred securities. Certain
intangible assets, including goodwill and deferred tax assets, are
deducted from tier 1 capital or are included subject to limits. See
12 CFR part 225, appendix A, section II.B. Total regulatory
capital consists of tier 1 capital plus certain subordinated debt
instruments and the allowance for loan and lease losses, subject
to certain limits.

of such capital instruments and issuance of stock is
assumed to be zero. As a result, the Federal Reserve’s
projections do not incorporate any changes in capital
actions that BHCs might undertake in reaction to
stressed financial conditions. The assumed capital
actions also do not incorporate any increases in distributions that BHCs might be planning to make over
the nine-quarter planning horizon.
These results are presented both in the aggregate for
the 18 BHCs and for individual BHCs. The aggregate
results provide a sense of the stringency of the
severely adverse scenario projections and the sensitivity of these BHCs as a group to the stressed economic and financial market conditions contained in
that scenario. The range of results across individual
BHCs reflects differences in business focus, asset
composition, revenue and expense sources, as well as
differences in portfolio risk characteristics. In addition, the post-stress capital ratio projections reflect
differences in capital actions across the BHCs prescribed in the Dodd-Frank stress test final rules. The
comprehensive results for individual BHCs are
reported in appendix C.

Stressed Regulatory Capital Ratios
The projections suggest significant declines in regulatory capital ratios for nearly all the BHCs under the
severely adverse scenario. Overall, the total amount
of tier 1 common capital held by the 18 BHCs is estimated to fall by more than $240 billion, or about 31
percent, from the third quarter of 2012 to the fourth
quarter of 2014 under the severely adverse scenario
and with prescribed capital actions over this period.
As shown in table 1, in the aggregate each of the four
capital ratios decline over the course of the planning
horizon, with year-end 2014 levels ranging from
2.1 percentage points to 4.0 percentage points lower
than at the start of the planning horizon. Table 2
presents these ratios for each of the 18 BHCs.

DFAST 2013: Methodology and Results

Table 1.A. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes, and loan losses, by type of loan:
18 participating bank holding companies
Federal Reserve estimates in the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

11.1
12.9
15.7
8.0

7.7
9.1
11.7
5.9

7.4
8.9
11.6
5.9

Table 1.B. Projected losses, revenue, and net income before
taxes through Q4 2014 under the severely adverse
scenario: 18 participating bank holding companies

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1

Billions of
dollars

Percent of
average assets1

267.8
1.2

2.4

317.2
12.9
97.0
36.0
-194.1

-1.7

Average assets is the nine-quarter average of total assets.
2
Pre-provision net revenue includes losses from operational-risk events,
mortgage put-back expenses, and OREO costs.
3
Other revenue includes one-time income and (expense) items not included in
pre-provision net revenue.
4
Trading and counterparty losses includes mark-to-market losses, changes in
credit valuation adjustments, and incremental default losses.
5
Other losses/gains includes projected change in fair value of loans held for sale
and loans held for investment measured under the fair-value option, and
goodwill impairment losses.
Source: Federal Reserve estimates in the severely adverse scenario.

Table 1.C. Projected loan losses by type of loans for Q4
2012–Q4 2014 under the severely adverse scenario:
18 participating bank holding companies

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

316.6
60.1
37.2
60.5
32.9
87.1
26.8
11.9

7.5
6.6
9.6
6.8
8.0
16.7
6.1
1.8

Commercial and industrial loans include small and medium enterprise loans
and corporate cards. Other loans include international real estate loans.
Average loan balances used to calculate portfolio loss rates exclude loans held
for sale and loans held for investment under the fair-value option, and are
calculated over nine quarters.
Source: Federal Reserve estimates in the severely adverse scenario.

March 2013

Table 2. Dodd-Frank Act stress testing 2013
Projected regulatory capital ratios and tier 1 common ratios through Q4 2014 under the severely adverse scenario
Federal Reserve estimates in the severely adverse scenario
Tier 1 common ratio (%)
Bank holding company

Ally Financial Inc.1
American Express Company
Bank of America Corporation
The Bank of New York Mellon
Corporation
BB&T Corporation2
Capital One Financial Corporation
Citigroup Inc.
Fifth Third Bancorp
The Goldman Sachs Group, Inc.
JPMorgan Chase & Co.
KeyCorp
Morgan Stanley
The PNC Financial Services
Group, Inc.
Regions Financial Corporation
State Street Corporation
SunTrust Banks, Inc.
U.S. Bancorp
Wells Fargo & Company
18 participating bank holding
companies

Actual
Q3 2012

Tier 1 capital ratio (%)

Projected Projected
Actual
Q4 2014 mimimum Q3 2012

Total risk-based capital ratio (%)

Projected Projected
Actual
Q4 2014 mimimum Q3 2012

Tier 1 leverage ratio (%)

Projected Projected
Actual
Q4 2014 mimimum Q3 2012

Projected Projected
Q4 2014 mimimum

7.3
12.7
11.4

1.5
11.3
6.9

1.5
11.1
6.8

13.6
12.7
13.6

11.0
11.3
8.5

11.0
11.1
8.5

14.6
14.7
17.2

12.6
13.4
11.6

12.6
13.2
11.6

11.3
10.7
7.8

9.4
9.5
5.4

9.4
8.9
5.4

13.3
9.5
10.7
12.7
9.7
13.1
10.4
11.3
13.9

15.9
9.4
7.4
8.9
8.6
8.2
6.8
8.0
6.4

13.2
9.4
7.4
8.3
8.6
5.8
6.3
8.0
5.7

15.3
10.9
12.7
13.9
10.8
15.0
11.9
12.1
16.9

17.1
11.2
7.8
9.8
9.3
9.8
7.9
8.6
8.2

14.8
11.2
7.8
9.3
9.3
7.5
7.4
8.6
7.5

16.9
14.0
15.0
17.1
14.8
18.1
14.7
15.2
17.0

17.9
13.4
10.1
12.9
12.4
12.8
10.3
11.2
9.4

16.0
13.4
10.1
12.5
12.4
10.4
9.9
11.2
8.7

5.6
7.9
9.9
7.4
10.1
7.2
7.1
11.4
7.2

5.9
8.3
5.7
5.6
8.8
5.6
4.7
8.1
5.1

5.1
7.9
5.7
5.3
8.8
3.9
4.7
8.1
4.5

9.5
10.5
17.8
9.8
9.0
9.9

8.7
7.5
13.0
7.3
8.3
7.0

8.7
7.5
12.8
7.3
8.3
7.0

11.7
11.5
19.8
10.6
10.9
11.5

10.8
8.5
14.5
8.2
10.3
8.7

10.8
8.5
14.4
8.2
10.3
8.7

14.5
15.0
21.3
13.0
13.3
14.5

13.4
11.7
16.6
10.4
12.3
11.4

13.4
11.7
16.2
10.4
12.3
11.2

10.4
9.1
7.6
8.5
9.2
9.4

8.7
6.8
7.1
6.5
8.7
7.0

8.7
6.8
6.6
6.5
8.7
7.0

11.1

7.7

7.4

12.9

9.1

8.9

15.7

11.7

11.6

8.0

5.9

Note: The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical
estimates that involve an economic outcome that is more adverse than expected. These estimates are not forecasts of capital ratios. The minimum stressed ratios (%) are the
lowest quarterly ratios from Q4 2012 to Q4 2014 under the severely adverse scenario.
1
The post-stress capital ratios presented in the table are based on an assumption that Ally remains subject to contingent liabilities associated with Residential Capital, LLC
(“ResCap”). On May 14, 2012, ResCap and certain of its subsidiaries filed for relief under Chapter 11 of the Bankruptcy Code in the United States Bankruptcy Court for the
Southern District of New York. As of March 6, 2013, the outcome of the ResCap bankruptcy remained pending.
2
The actual and post-stress capital ratios presented in the table are based on information that BB&T provided to the Federal Reserve in regulatory reports on or before
February 6, 2013. The information that BB&T provided to the Federal Reserve includes information regarding BB&T’s risk-weighted assets. On March 4, 2013, BB&T
disclosed publicly that it had reevaluated its process related to calculating risk-weighted assets and determined that certain adjustments, primarily related to the
presentation of certain unfunded lending commitments, were required in order to conform to regulatory guidance. These adjustments resulted in an increase to
risk-weighted assets and a decrease in BB&T’s risk-based capital ratios and are not reflected in this table.
Source: Federal Reserve estimates in the severely adverse scenario. Stressed ratios with Dodd-Frank Act capital action assumptions through Q4 2014.

Table 3 shows estimates of the minimum tier 1 common ratio during the severely adverse scenario for
each of the 18 BHCs with all prescribed capital
actions through the fourth quarter of 2014.
The changes in post-stress regulatory capital ratios
vary considerably across BHCs (see figures 8 and 9
and table 2). Overall, post-stress regulatory capital
ratios decline from the beginning to the end of the
planning horizon for all but two of the BHCs. The
post-stress capital ratios incorporate projected levels
of total average assets and risk-weighted assets over
the planning horizon, based on projections provided
by the BHCs in their FR Y-14 submissions. Because
the Federal Reserve’s projections of losses and

PPNR also reflect the projected growth or reduction
of risk-weighted assets and total assets for each
BHC, projected changes in risk-weighted assets and
total assets do not always have a straightforward
effect on projected stressed capital ratios.

Projected Losses
The Federal Reserve’s severely adverse scenario projections suggest that the 18 BHCs as a group would
experience significant losses under the severely
adverse scenario. In this scenario, losses are projected
to be $462 billion for the 18 BHCs in the aggregate
over the nine quarters of the planning horizon. These

DFAST 2013: Methodology and Results

Table 3. Dodd-Frank Act stress testing 2013
Minimum stressed tier 1 common ratios, Q4 2012 to Q4 2014
Federal Reserve estimates in the severely adverse scenario
Stressed ratios with DFA stress testing
capital action assumptions

Bank holding company
Ally Financial Inc.1
American Express Company
Bank of America Corporation
The Bank of New York Mellon Corporation
BB&T Corporation2
Capital One Financial Corporation
Citigroup Inc.
Fifth Third Bancorp
The Goldman Sachs Group, Inc.
JPMorgan Chase & Co.
KeyCorp
Morgan Stanley
The PNC Financial Services Group, Inc.
Regions Financial Corporation
State Street Corporation
SunTrust Banks, Inc.
U.S. Bancorp
Wells Fargo & Co.

1.5
11.1
6.8
13.2
9.4
7.4
8.3
8.6
5.8
6.3
8.0
5.7
8.7
7.5
12.8
7.3
8.3
7.0

Note: The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical
estimates that involve an economic outcome that is more adverse than expected.
1
The post-stress capital ratios presented in the table are based on an assumption that Ally remains subject to contingent liabilities associated with Residential Capital, LLC
(“ResCap”). On May 14, 2012, ResCap and certain of its subsidiaries filed for relief under Chapter 11 of the Bankruptcy Code in the United States Bankruptcy Court for the
Southern District of New York. As of March 6, 2013, the outcome of the ResCap bankruptcy remained pending.
2
The actual and post-stress capital ratios presented in the table are based on information that BB&T provided to the Federal Reserve in regulatory reports on or before
February 6, 2013. The information that BB&T provided to the Federal Reserve includes information regarding BB&T’s risk-weighted assets. On March 4, 2013, BB&T
disclosed publicly that it had reevaluated its process related to calculating risk-weighted assets and determined that certain adjustments, primarily related to the
presentation of certain unfunded lending commitments, were required in order to conform to regulatory guidance. These adjustments resulted in an increase to
risk-weighted assets and a decrease in BB&T’s risk-based capital ratios and are not reflected in this table.
Source: Federal Reserve estimates in the severely adverse scenario.

losses include $317 billion in accrual loan portfolio
losses, $13 billion in OTTI and other realized securities losses, $97 billion in trading and counterparty
losses at the six BHCs with large trading portfolios,
and $36 billion in additional losses from items such
as loans measured under the fair-value option (losses
on these loans were calculated based on the global
market shock, consistent with the treatment of fair
valued positions in the trading portfolio), and goodwill impairment charges. Table 1 presents these
results in the aggregate, while table 4 presents them
individually for each of the 18 BHCs.
The biggest sources of loss are losses on the accrual
loan portfolios and trading and counterparty losses
from the global market shock. Together, these two
account for nearly 90 percent of the projected losses
for the 18 BHCs under the severely adverse scenario
(figure 10).

Loan Losses
Projected losses on consumer-related lending—domestic residential mortgages, credit cards, and other
consumer loans—represent 67 percent of projected
loan losses and 46 percent of total projected losses
for the 18 BHCs (see figure 10 and table 1). This is
consistent with both the share of these types of loans
in the BHCs’ loan portfolios—these loans represent
54 percent of the accrual loan portfolio at these firms
as of the third quarter of 2012—and with the
severely adverse scenario, which features very high
unemployment rates and significant further declines
in housing prices. Losses on domestic residential
mortgage loans, including both first liens and junior
liens/home equity, is the single largest category of
losses, at $97 billion, representing 31 percent of total
projected loan losses. Projected losses on credit card
lending—at $87 billion—is the second largest cat-

March 2013

Figure 8. Minimum tier 1 common ratio in the severely adverse scenario
Percent

Percent

15.0

12.0

Median = 7.7%

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

0.0

Citi

0.0

CapOne

3.0

BB&T 2

3.0

BNYM

6.0

BofA

6.0

AmEx

9.0

Ally 1

9.0

1. The post-stress capital ratios presented in the figure are based on an assumption that Ally remains subject to contingent liabilities associated with Residential Capital, LLC
(“ResCap”). On May 14, 2012, ResCap and certain of its subsidiaries filed for relief under Chapter 11 of the Bankruptcy Code in the United States Bankruptcy Court for the
Southern District of New York. As of March 6, 2013, the outcome of the ResCap bankruptcy remained pending.
2. The actual and post-stress capital ratios presented in the figure are based on information that BB&T provided to the Federal Reserve in regulatory reports on or before February 6, 2013. The information that BB&T provided to the Federal Reserve includes information regarding BB&T’s risk-weighted assets. On March 4, 2013, BB&T disclosed publicly
that it had reevaluated its process related to calculating risk-weighted assets and determined that certain adjustments, primarily related to the presentation of certain unfunded
lending commitments, were required in order to conform to regulatory guidance. These adjustments resulted in an increase to risk-weighted assets and a decrease in BB&T’s
risk-based capital ratios and are not reflected in this figure.
Source: Federal Reserve estimates in the severely adverse scenario.

egory, representing 28 percent. The next largest category is projected losses on commercial and industrial loans, at $61 billion.
For the 18 BHCs as a group, the nine-quarter cumulative loss rate on the accrual loan portfolio is
7.5 percent, where the loss rate is calculated as total
projected loan losses over the nine quarters of the
planning horizon divided by average loan balances
over the horizon. This rate is very high by historical
standards, more severe than any U.S. recession since
the 1930s. As illustrated in figure 11, total loan loss
rates vary significantly across BHCs, ranging
between 2.0 percent and 13.2 percent across these
institutions.
The differences in total loan loss rates across the
BHCs reflect differences in loan portfolio composition and differences in risk characteristics for each

type of lending across these firms. Loan portfolio
composition matters because projected loss rates vary
significantly by loan type.23 In the aggregate, ninequarter cumulative loss rates range between 1.8 percent on other loans and 16.7 percent on credit cards,
reflecting both differences in typical performance of
these loans—some loan types tend to generate higher
losses, though generally also higher revenue—and differences in the sensitivity of lending to the severely
adverse scenario. In particular, lending categories
whose performance is sensitive to unemployment
rates or housing prices may experience high stressed
loss rates due to the considerable stress on these factors in the severely adverse scenario.

The loan categories are defined to be generally consistent with
categories on the FR Y-9 C reports.

DFAST 2013: Methodology and Results

Figure 9. Change from Q3 2012 to minimum tier 1 common ratio in the severely adverse scenario
Percent

18.0

Percent

18.0

Change from Q3 2012
to minimum
Minimum ratio

15.0

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

0.0
Goldman

0.0
Fifth Third

3.0

Citi

3.0

CapOne

6.0

BB&T 2

6.0

BNYM

9.0

BofA

9.0

AmEx

12.0

Ally 1

12.0

Figures 12 through 18 present the nine-quarter
cumulative loss rates on seven different categories of
loans for each of the 18 BHCs. There are significant
differences across BHCs in projected loan loss rates
for similar types of loans. For example, while the
median projected loss rate on domestic first-lien residential mortgages is 6.0 percent, the rates among
BHCs with first lien mortgage portfolios vary from a
low of 0.6 percent to a high of 10.3 percent. Similarly, for commercial and industrial loans, the range
of projected loss rates is from 3.5 percent to 49.8 percent, with a median of 6.5 percent. Projected loss
rates on most loan categories show similar dispersion
across BHCs.24
24

Losses are calculated based on the exposure at default, which
includes both outstanding balances and any additional drawdown of the credit line that occurs prior to default, while loss
rates are calculated as a percent of outstanding balances. See
appendix B for more detail on the models used to project net
income and stressed capital.

Differences in projected loss rates across BHCs primarily reflect differences in loan characteristics, such
as loan-to-value ratio or debt service coverage ratio,
and borrower characteristics, such as credit rating or
FICO score. In addition, some BHCs have taken
write-downs on portfolios of impaired loans either
purchased or acquired through mergers. Losses on
these loans are projected using the same loss models
used for loans of the same type, and the resulting loss
projections are reduced by the amount of such writedowns. For these BHCs, projected loss rates will be
lower than for BHCs that hold similar loans not subject to purchase-related write-downs.

Losses on Trading, Private Equity, and
Derivatives Positions
The severely adverse scenario results include $97 billion in trading and counterparty credit losses from
the global market shock at the six BHCs with large

March 2013

Table 4. Dodd-Frank Act stress testing 2013
Projected losses, revenues, and net income before taxes for 18 participating bank holding companies
Federal Reserve estimates in the severely adverse scenario
Billions of dollars
Sum of revenues
Bank holding company

Ally Financial Inc.
American Express Company
Bank of America Corporation
The Bank of New York Mellon Corporation
BB&T Corporation
Capital One Financial Corporation
Citigroup Inc.
Fifth Third Bancorp
The Goldman Sachs Group, Inc.
JPMorgan Chase & Co.
KeyCorp
Morgan Stanley
The PNC Financial Services Group, Inc.
Regions Financial Corporation
State Street Corporation
SunTrust Banks, Inc.
U.S. Bancorp
Wells Fargo & Company
18 participating bank holding companies

Minus sum of provisions and losses

Equals

Pre-provision
net revenue1

Other revenue2

Provisions

Realized
losses/gains
on securities
(AFS/HTM)

Trading and
counterparty
losses3

Other
losses/gains4

Net income
before taxes

-3.7
15.4
24.1
6.8
7.1
18.7
44.0
4.9
14.4
45.0
2.5
1.2
9.8
3.1
3.0
4.6
21.2
45.9
267.8

0.3
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.1
0.0
0.0
0.0
0.1
0.0
1.2

5.1
14.2
49.7
1.1
6.4
26.4
49.4
5.1
2.6
51.3
4.3
2.3
9.8
5.2
0.4
7.9
17.2
58.8
317.2

0.7
0.0
0.5
0.2
0.1
0.3
4.4
0.1
0.2
0.9
0.0
0.0
0.8
0.1
0.4
0.0
0.2
3.9
12.9

0.0
0.0
14.1
0.0
0.0
0.0
15.9
0.0
24.9
23.5
0.0
11.7
0.0
0.0
0.0
0.0
0.0
6.9
97.0

0.0
0.4
12.5
0.0
0.1
0.0
2.7
0.0
7.1
1.6
0.6
6.7
0.4
0.0
0.7
0.7
0.3
2.0
36.0

-9.3
0.8
-51.8
5.5
0.6
-8.0
-28.6
-0.3
-20.5
-32.3
-2.4
-19.4
-1.4
-2.2
1.5
-4.1
3.6
-25.7
-194.1

Note: These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are not forecasts of expected
losses, revenues, or net income before taxes.
Average balances used for profitability ratios and portfolio loss rates are averages over the nine-quarter period. Estimates may not sum precisely due to rounding.
1
Pre-provision net revenue includes losses from operational-risk events, mortgage put-back expenses, and OREO costs.
2
Other revenue includes one-time income and (expense) items not included in pre-provision net revenue.
3
Trading and counterparty losses includes mark-to-market losses, changes in credit valuation adjustments, and incremental default losses.
4
Other losses/gains includes projected change in fair value of loans held for sale and loans held for investment measured under the fair-value option, and goodwill impairment
losses.

Figure 10. Projected losses in the severely adverse
scenario

trading, private equity, and counterparty exposures
from derivatives and financing transactions. Trading
and counterparty credit losses range between $7 billion and $25 billion across the six BHCs (see table 4),
with the largest losses at those BHCs with the most
significant trading activities. Even so, the relative size
of losses across firms depends not on nominal portfolio size, but rather on the specific risk characteristics of each BHC’s trading positions, inclusive of
hedges. Importantly, projected losses related to the
global market shock are based on the trading positions held by these firms on a single date (November 14, 2012) and could have differed, perhaps significantly over the nine-quarter planning horizon, based
on trading positions from a different date.

Billions of dollars

Other
loans,12

Other
losses, 36

First-lien mortgages,
domestic, 60

Other
consumer
loans, 27
Commercial
real estate,
domestic, 33
Trading and
counterparty
losses, 97

Junior liens
and HELOCs,
domestic, 37
Securities
losses
(AFS/HTM), 13

Commercial and
industrial loans, 60

Credit cards, 87

Source: Federal Reserve estimates in the severely adverse scenario.

DFAST 2013: Methodology and Results

Figure 11. Total loan loss rates in the severely adverse scenario
Percent

Percent

12.0

9.0

Median = 6.6%

9.0

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

3.0

BofA

3.0

AmEx

6.0

Ally

6.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Projected Pre-Provision Net Revenue and
Net Income
In the aggregate, the 18 BHCs are projected to generate $268 billion in PPNR cumulatively over the nine
quarters of the planning horizon, equal to 2.4 percent of average assets for these firms (see table 1).
Relatively low PPNR projections reflect low levels of
net interest income because of the effect of low interest rates and further flattening of the yield curve in
the early part of the severely adverse scenario, given
the BHCs’ current and projected balance sheet composition. The results also reflect low levels of noninterest income, consistent with the falling asset
prices and sharply contracting economic activity in
the severely adverse scenario. In addition, the PPNR
projections incorporate elevated levels of losses from
operational-risk events such as fraud, employee lawsuits, or computer system or other operating disruptions and expenses related to put-backs of mortgages, netted against reserves already taken by the
BHCs.25

These estimates are conditional on the hypothetical severely
adverse scenario and on conservative assumptions. They are not
a supervisory estimate of the current legal liability that BHCs
might actually face.

The ratio of projected cumulative PPNR to average
assets varies across BHCs (see figure 19 and table 4).
A significant portion of this variation reflects differences in business focus across the institutions. For
instance, the ratio of PPNR to assets tends to be
higher at BHCs focusing on credit card lending,
reflecting the higher net interest income that credit
cards generally produce relative to other forms of
lending.26 Lower PPNR rates do not necessarily
imply lower net income, however, since the same business focus and revenue risk characteristics determining differences in PPNR across firms could also
result in offsetting differences in projected losses.
Projected PPNR and losses are the primary determinants of projected net income. Table 1 presents
aggregate projections of the components of pre-tax
net income, including provisions into the ALLL and
one-time income and expense and extraordinary
items, under the severely adverse scenario. Table 4
presents these projections for each of the 18 BHCs.
The projections are cumulative for the nine quarters
of the planning horizon.

As noted, credit card lending also tends to generate relatively
high loss rates, so the higher PPNR rates at these BHCs do not
necessarily indicate higher profitability.

March 2013

Table 5. Dodd-Frank Act stress testing 2013
Projected loan losses, by type of loan, for 18 participating bank holding companies
Federal Reserve estimates in the severely adverse scenario
Loan
losses1

First-lien
mortgages,
domestic

Junior liens
and HELOCs,
domestic

Commercial
real estate,
domestic

Credit
cards

Other
consumer

Other
loans

Portfolio loan losses, by type of loan, for Q4 2012–Q4 2014 under the severely adverse scenario (billions of dollars)
Ally Financial Inc.
4.5
0.3
0.2
1.4
0.1
American Express Company
10.7
0.0
0.0
2.6
0.0
Bank of America Corporation
57.5
15.3
9.4
8.5
4.7
The Bank of New York Mellon Corporation
1.2
0.4
0.0
0.1
0.1
BB&T Corporation
5.9
0.9
0.4
1.1
2.1
Capital One Financial Corporation
23.6
1.4
0.5
1.5
0.9
Citigroup Inc.
54.6
8.8
4.5
7.8
0.8
Fifth Third Bancorp
5.3
0.7
0.9
1.9
0.8
The Goldman Sachs Group, Inc.
2.0
0.0
0.0
1.4
0.1
JPMorgan Chase & Co.
53.9
11.3
6.7
11.1
5.2
KeyCorp
3.9
0.4
1.1
1.0
0.6
Morgan Stanley
1.6
0.1
0.0
1.2
0.0
The PNC Financial Services Group, Inc.
10.0
1.4
1.6
3.4
2.0
Regions Financial Corporation
5.4
1.1
0.8
1.2
1.7
State Street Corporation
0.3
0.0
0.0
0.0
0.1
SunTrust Banks, Inc.
7.4
1.7
1.7
2.1
1.1
U.S. Bancorp
15.1
1.3
1.0
4.3
3.0
Wells Fargo & Company
53.8
15.3
8.4
9.9
9.6
18 participating bank holding companies
316.6
60.1
37.2
60.5
32.9

0.0
8.0
15.3
0.0
0.3
16.4
23.3
0.4
0.0
14.8
0.1
0.0
0.6
0.2
0.0
0.1
3.2
4.4
87.1

2.4
0.0
3.0
0.0
0.9
2.7
6.5
0.5
0.0
2.3
0.4
0.1
0.7
0.3
0.0
0.5
1.6
5.0
26.8

0.0
0.0
1.3
0.5
0.3
0.1
2.9
0.2
0.6
2.6
0.3
0.1
0.3
0.2
0.2
0.2
0.7
1.2
11.9

Portfolio loss rates, by type of loan, for Q4 2012–Q4 2014 under the severely adverse scenario (percent of average balances)
Ally Financial Inc.
5.2
6.0
9.3
5.2
6.5
American Express Company
11.2
0.0
0.0
9.4
0.0
Bank of America Corporation
6.9
5.9
10.0
5.1
8.6
The Bank of New York Mellon Corporation
2.7
6.7
12.8
3.5
7.7
BB&T Corporation
5.5
2.8
6.1
7.2
7.1
Capital One Financial Corporation
13.2
3.8
21.1
8.9
4.8
Citigroup Inc.
9.2
9.4
13.4
6.0
11.3
Fifth Third Bancorp
6.3
5.4
10.4
6.3
7.7
The Goldman Sachs Group, Inc.
5.2
7.7
9.8
49.8
8.2
JPMorgan Chase & Co.
7.7
8.8
8.8
8.5
7.3
Keycorp
7.3
10.3
12.6
5.8
7.2
Morgan Stanley
3.1
0.6
9.5
7.8
10.2
The PNC Financial Services Group, Inc.
5.8
6.1
6.3
6.4
7.3
Regions Financial Corporation
7.6
8.2
8.5
6.7
9.7
State Street Corporation
2.0
0.0
0.0
0.0
18.3
SunTrust Banks, Inc.
6.4
6.5
11.4
6.2
9.7
U.S. Bancorp
7.1
2.8
6.1
9.5
8.0
Wells Fargo & Company
7.1
7.1
9.3
6.6
8.6
18 participating bank holding companies
7.5
6.6
9.6
6.8
8.0

0.0
12.0
16.2
0.0
16.6
22.2
17.9
21.6
0.0
14.4
19.1
0.0
15.5
18.0
0.0
15.0
17.3
17.7
16.7

4.9
0.0
4.3
0.5
7.0
11.8
16.5
3.6
2.8
3.9
8.8
1.4
3.5
6.8
0.0
2.6
5.4
5.9
6.1

1.8
4.5
1.3
1.7
3.0
1.8
1.8
2.4
1.6
1.9
2.8
0.8
1.6
2.2
1.5
2.2
3.8
1.6
1.8

Bank holding company

Commercial
and industrial

Of note, following U.S. GAAP, the net income projections incorporate loan losses indirectly through
provisions, which equal projected loan losses plus the
amount needed for the ALLL to be at an appropriate
level at the end of each quarter. The slightly more
than $317 billion in total provisions reported in

table 1 is the result of slightly less than $317 billion in
net charge-offs and almost no net change in the
ALLL over the nine-quarter planning horizon.
Table 1 is cumulative over the planning horizon, and
masks variation in the ALLL during the course of
the nine quarters. Specifically, the projected ALLL

DFAST 2013: Methodology and Results

Figure 12. First-lien mortgages, domestic loss rates in the severely adverse scenario
Percent

Percent

12.0

9.0

9.0
Median = 6%

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

3.0

BofA

3.0

AmEx

6.0

Ally

6.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Figure 13. Junior liens and HELOCs, domestic loss rates in the severely adverse scenario
Percent

Percent

24.0

20.0

16.0

16.0
Median = 9.4%

12.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

4.0

BofA

4.0

AmEx

8.0

Ally

8.0

March 2013

Figure 14. Commercial and industrial loss rates in the severely adverse scenario

Percent

49.8

12.0

10.0

10.0
Median = 6.5%

8.0

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

0.0

Citi

0.0

CapOne

2.0

BB&T

2.0

BNYM

4.0

BofA

4.0

AmEx

6.0

Ally

6.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances. Losses are calculated based on the exposure at default, which
includes both outstanding balances and any additional drawdown of the credit line that occurs prior to default, while loss rates are calculated as a percent of outstanding
balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Figure 15. Commercial real estate, domestic loss rates in the severely adverse scenario

20.0

Percent

16.0

20.0
16.0

12.0

Median = 7.8%

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

4.0

BofA

4.0

AmEx

8.0

Ally

8.0

DFAST 2013: Methodology and Results

Figure 16. Credit card loss rates in the severely adverse scenario
Percent

Percent

24.0

20.0

Median = 15.8%

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

0.0
Goldman

0.0
Fifth Third

4.0

Citi

4.0

CapOne

8.0

BB&T

8.0

BNYM

12.0

BofA

12.0

AmEx

16.0

Ally

16.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Figure 17. Other consumer loss rates in the severely adverse scenario

20.0

Percent

16.0

20.0
16.0

12.0

Median = 4.1%

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

4.0

BofA

4.0

AmEx

8.0

Ally

8.0

March 2013

Figure 18. Other loan loss rates in the severely adverse scenario
Percent

Percent

6.0

5.0

4.0

4.0
Median = 1.8%

3.0

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

0.0
BB&T

0.0
BNYM

1.0

BofA

1.0

AmEx

2.0

Ally

2.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average balances.
Source: Federal Reserve estimates in the severely adverse scenario.

Figure 19. PPNR rates in the severely adverse scenario

12.0

Percent

9.0

12.0
9.0

6.0

Median = 2.7%

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average assets.
Source: Federal Reserve estimates in the severely adverse scenario.

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

Goldman

Fifth Third

Citi

CapOne

-3.0
BB&T

-3.0
BNYM

0.0

BofA

0.0

AmEx

3.0

Ally

3.0

DFAST 2013: Methodology and Results

Figure 20. Pre-tax net income rates in the severely adverse scenario
Percent

Percent

6.0

4.0

2.0

Median = -1.7%

Wells

USB

SunTrust

State St

Regions

PNC

Morgan Stanley

KeyCorp

JPMC

-8.0
Goldman

-8.0
Fifth Third

-6.0

Citi

-6.0

CapOne

-4.0

BB&T

-4.0

BNYM

-2.0

BofA

-2.0

AmEx

0.0

Ally

0.0

Note: Estimates are for the nine-quarter period from Q4 2012 to Q4 2014 as a percent of average assets.
Source: Federal Reserve estimates in the severely adverse scenario.

increases during the early quarters of the planning
horizon, given the increased economic stress in the
severely adverse scenario, and then declines as the
economic stress abates.
The Federal Reserve’s projections of pre-tax net
income under the severely adverse scenario imply
negative net income at most of the 18 BHCs individually, and for the BHCs as a group, over the nine
quarter planning horizon. As table 1 shows, projected
net income before taxes (“pre-tax net income”) is
-$194 billion over the planning horizon for the 18
BHCs.
Figure 20 illustrates the ratio of pre-tax net income

to average assets for each of the 18 BHCs. The ratio
ranges between -7.1 percent and 1.6 percent. Projected cumulative net income for most of the BHCs
(13 of 18) is negative over the planning horizon. Differences across the firms reflect differences in the sensitivity of the various components of net income to
the economic and financial market conditions in the
severely adverse scenario. Projected net income for
the six BHCs with large trading operations is also
affected by the effect of the global market shock on
their trading, private equity, and counterparty exposures from derivatives and financing transactions,
introducing some additional variation in projected
net income between these six BHCs and the other
firms participating in DFAST 2013.

Appendix A: Severely Adverse Scenario

This appendix includes the severely adverse scenario
provided by the Federal Reserve.
It is important to note that the severely adverse scenario is not a forecast but rather a hypothetical scenario to be used to assess the strength and resilience of

BHC capital in a severely adverse economic environment. The severely adverse scenario, while unlikely,
represents an outcome in which the U.S. economy
experiences a significant recession and financial market distress, and economic activity in other major
economies also contracts significantly.

DFAST 2013: Methodology and Results

Table A.1. Supervisory severely adverse scenario: Domestic

Date

Real GDP
growth

Q1 2001
Q2 2001
Q3 2001
Q4 2001
Q1 2002
Q2 2002
Q3 2002
Q4 2002
Q1 2003
Q2 2003
Q3 2003
Q4 2003
Q1 2004
Q2 2004
Q3 2004
Q4 2004
Q1 2005
Q2 2005
Q3 2005
Q4 2005
Q1 2006
Q2 2006
Q3 2006
Q4 2006
Q1 2007
Q2 2007
Q3 2007
Q4 2007
Q1 2008
Q2 2008
Q3 2008
Q4 2008
Q1 2009
Q2 2009
Q3 2009
Q4 2009
Q1 2010
Q2 2010
Q3 2010
Q4 2010
Q1 2011
Q2 2011
Q3 2011
Q4 2011
Q1 2012
Q2 2012
Q3 2012
Q4 2012

-1.3
2.6
-1.1
1.4
3.5
2.1
2.0
0.1
1.7
3.4
6.7
3.7
2.7
2.6
3.0
3.3
4.2
1.8
3.2
2.1
5.1
1.6
0.1
2.7
0.5
3.6
3.0
1.7
-1.8
1.3
-3.7
-8.9
-5.3
-0.3
1.4
4.0
2.3
2.2
2.6
2.4
0.1
2.5
1.3
4.1
2.0
1.3
2.0
-3.5

Nominal
Real
CPI
UnemployNominal
disposable disposable
inflation
ment
GDP
income
income
rate
rate
growth
growth
growth
1.4
5.5
0.2
2.7
4.9
4.0
3.8
2.5
4.5
4.6
9.1
5.8
6.3
6.1
6.0
6.4
8.1
4.5
7.5
5.5
8.3
5.2
3.1
4.6
5.2
6.5
4.3
3.6
0.6
4.0
-0.6
-8.4
-4.4
-1.1
1.9
5.3
3.9
4.1
4.6
4.5
2.2
5.2
4.3
4.2
4.2
2.8
5.0
0.0

3.0
-1.1
10.6
-4.6
11.2
2.2
-1.4
1.0
1.5
6.2
5.7
2.3
1.8
4.0
2.7
5.7
-4.8
2.8
2.4
2.2
7.7
3.6
1.9
5.3
1.8
0.6
1.6
2.2
5.9
8.2
-8.8
-0.2
-4.7
-0.5
-6.1
-0.6
5.7
6.3
1.2
1.0
4.4
-1.5
-1.3
-0.2
3.7
3.1
0.8
-3.8

6.0
0.8
10.7
-4.4
12.3
5.4
0.6
2.9
4.4
6.5
8.5
4.2
5.2
7.1
5.3
9.2
-2.5
5.4
7.1
5.8
9.5
6.7
4.9
5.3
5.8
4.1
3.9
6.5
10.0
13.1
-4.9
-5.8
-6.8
1.1
-3.3
2.5
7.6
6.9
2.5
3.1
7.7
2.0
1.1
0.9
6.3
3.8
2.6
-2.3

4.2
4.4
4.8
5.5
5.7
5.8
5.7
5.9
5.9
6.1
6.1
5.8
5.7
5.6
5.4
5.4
5.3
5.1
5.0
5.0
4.7
4.6
4.6
4.4
4.5
4.5
4.7
4.8
5.0
5.3
6.0
6.9
8.3
9.3
9.6
9.9
9.8
9.6
9.5
9.6
9.0
9.0
9.1
8.7
8.3
8.2
8.1
8.9

3.9
2.8
1.1
-0.3
1.3
3.2
2.2
2.4
4.2
-0.7
3.0
1.5
3.4
3.2
2.6
4.4
2.0
2.7
6.2
3.8
2.1
3.7
3.8
-1.6
4.0
4.6
2.6
5.0
4.4
5.4
6.4
-9.0
-2.5
1.9
3.6
3.0
0.9
-0.3
1.4
3.0
4.5
4.4
3.1
1.3
2.5
0.8
2.3
1.8

3-month
Treasury
yield

10-year
Treasury
yield

4.8
3.7
3.2
1.9
1.7
1.7
1.6
1.3
1.2
1.0
0.9
0.9
0.9
1.1
1.5
2.0
2.5
2.9
3.4
3.8
4.4
4.7
4.9
4.9
5.0
4.7
4.3
3.4
2.1
1.6
1.5
0.3
0.2
0.2
0.2
0.1
0.1
0.1
0.2
0.1
0.1
0.0
0.0
0.0
0.1
0.1
0.1
0.1

5.3
5.5
5.3
5.1
5.4
5.4
4.5
4.3
4.2
3.8
4.4
4.4
4.1
4.7
4.4
4.3
4.4
4.2
4.3
4.6
4.7
5.2
5.0
4.7
4.8
4.9
4.8
4.4
3.9
4.1
4.1
3.7
3.2
3.7
3.8
3.7
3.9
3.6
2.9
3.0
3.5
3.3
2.5
2.1
2.1
1.8
1.6
1.4

Dow Jones
BBB
Mortgage Total Stock
corporate
Market
rate
yield
Index
7.4
7.5
7.3
7.2
7.6
7.6
7.3
7.0
6.5
5.7
6.0
5.8
5.5
6.1
5.8
5.4
5.4
5.5
5.5
5.9
6.0
6.5
6.4
6.1
6.1
6.3
6.5
6.4
6.5
6.8
7.2
9.4
9.0
8.2
6.8
6.1
5.8
5.6
5.1
5.0
5.4
5.1
4.9
5.0
4.7
4.5
4.2
5.6

7.0
7.2
6.9
6.8
7.0
6.7
6.2
6.1
5.8
5.5
6.1
5.9
5.6
6.2
5.8
5.7
5.8
5.7
5.8
6.3
6.3
6.6
6.5
6.2
6.2
6.4
6.5
6.2
5.9
6.2
6.3
5.8
5.0
5.1
5.1
4.9
5.0
4.8
4.4
4.5
4.9
4.6
4.2
4.0
3.9
3.7
3.5
4.1

10645.9
11407.2
9563.0
10707.7
10775.7
9384.0
7773.6
8343.2
8051.9
9342.4
9649.7
10799.6
11039.4
11138.9
10895.5
11971.1
11638.3
11876.7
12289.3
12517.7
13155.4
12849.3
13346.0
14257.6
14409.3
15210.7
15362.0
14819.6
13332.0
13073.5
11875.4
9087.2
8113.1
9424.9
10911.7
11497.4
12161.0
10750.0
11947.1
13290.0
14036.4
13968.1
11771.9
13109.6
14753.1
14208.6
14997.8
12105.2

House
Price
Index
112.3
114.5
116.7
119.1
121.4
124.3
127.8
130.4
133.4
136.2
139.8
144.3
150.2
156.4
162.2
167.8
176.1
183.8
189.9
194.9
199.7
199.7
197.5
198.0
196.4
192.1
186.4
180.7
174.5
166.7
159.8
152.0
144.1
142.3
144.0
144.8
145.5
145.7
142.5
140.2
138.8
137.7
137.2
135.9
137.9
141.3
143.4
141.6

Market
Commercial
Volatility
Real Estate
Index
Price Index
(VIX)
140.8
140.0
143.7
137.9
139.7
137.4
140.9
144.2
148.7
151.2
152.2
150.1
155.8
162.6
173.9
178.4
179.6
186.5
190.8
199.6
203.0
211.9
224.2
221.1
233.3
241.5
257.8
260.2
253.6
242.1
246.8
231.9
211.2
175.4
158.7
158.0
153.5
169.3
171.1
179.8
186.4
184.4
184.6
194.1
195.2
196.8
198.6
195.8

32.8
34.7
43.7
35.3
26.1
28.4
45.1
42.6
34.7
29.1
22.7
21.1
21.6
20.0
19.3
16.6
14.6
17.7
14.2
16.5
14.6
23.8
18.6
12.7
19.6
18.9
30.8
31.1
32.2
31.0
46.7
80.9
56.7
42.3
31.3
30.7
27.3
45.8
32.9
23.5
29.4
22.7
48.0
45.5
23.0
26.7
20.5
72.1

(continued on next page)

March 2013

Table A.1. Supervisory severely adverse scenario: Domestic—continued

Date

Real GDP
growth

Q1 2013
Q2 2013
Q3 2013
Q4 2013
Q1 2014
Q2 2014
Q3 2014
Q4 2014
Q1 2015
Q2 2015
Q3 2015
Q4 2015

-6.1
-4.4
-4.2
-1.2
0.0
2.2
2.6
3.8
4.2
4.1
4.6
4.6

Nominal
Real
CPI
UnemployNominal
disposable disposable
inflation
ment
GDP
income
income
rate
rate
growth
growth
growth
-4.7
-3.3
-3.6
-1.2
0.3
2.2
2.4
3.5
3.8
3.7
4.1
4.0

-6.7
-4.6
-3.2
-1.5
0.8
0.9
2.5
2.8
3.6
3.7
3.4
3.1

-5.9
-4.0
-2.8
-1.8
1.2
1.3
2.7
2.9
3.6
3.6
3.1
2.8

10.0
10.7
11.5
11.9
12.0
12.1
12.0
11.9
11.7
11.5
11.4
11.1

Note: Refer to “Data Notes” on page 34 for more information on variables.

1.4
1.1
1.0
0.3
1.0
0.9
0.7
0.6
0.5
0.5
0.3
0.3

3-month
Treasury
yield

10-year
Treasury
yield

0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1

1.2
1.2
1.2
1.2
1.2
1.5
1.7
1.9
2.0
2.1
2.2
2.2

Dow Jones
BBB
Mortgage Total Stock
corporate
Market
rate
yield
Index
6.4
6.7
6.8
6.5
6.2
6.2
6.0
5.9
5.8
5.8
5.6
5.4

4.5
4.7
4.8
4.7
4.7
4.7
4.6
4.5
4.5
4.5
4.4
4.3

9652.6
9032.8
7269.1
7221.7
7749.3
8133.9
9026.1
9706.7
10211.0
12645.7
13854.4
15294.9

House
Price
Index
137.9
133.6
129.0
124.7
120.6
117.2
115.0
113.6
113.2
113.6
114.4
115.5

Market
Commercial
Volatility
Real Estate
Index
Price Index
(VIX)
185.8
178.2
171.8
163.1
160.4
158.8
156.3
157.6
157.1
157.4
162.7
166.0

76.6
76.4
79.4
71.7
70.6
64.5
58.6
53.0
50.1
40.9
26.3
17.1

DFAST 2013: Methodology and Results

Table A.2. Supervisory severely adverse scenario: International

Date

Euro area
real GDP
growth

3.7
0.4
0.3
0.6
0.6
2.3
1.2
0.1
-0.2
0.3
1.8
2.9
2.1
2.2
1.5
1.4
0.8
3.0
2.4
2.6
3.8
4.3
2.8
4.2
3.3
1.8
2.5
1.7
2.1
-1.4
-2.4
-6.6
-10.7
-1.1
1.5
1.6
1.9
4.2
1.5
1.4
2.6
0.9
0.3
-1.3
0.0
-0.7
-0.5
-8.7

Euro area
inflation

Euro area
bilateral
dollar
exchange
rate
($/euro)

Developing
Asia
real GDP
growth

Developing
Asia
inflation

Developing
Asia
bilateral
dollar
exchange
rate
(F/USD,
index,
base =
2000 Q1)

1.1
4.1
1.4
1.7
3.0
2.0
1.6
2.4
3.3
0.3
2.2
2.2
2.3
2.4
2.0
2.5
1.5
2.2
3.2
2.5
1.6
2.5
2.0
1.0
2.2
2.3
2.1
5.0
4.2
3.1
3.2
-1.3
-1.2
-0.1
1.3
1.7
1.6
1.7
2.0
2.7
3.4
2.9
1.9
3.6
2.4
2.0
2.3
1.6

0.9
0.8
0.9
0.9
0.9
1.0
1.0
1.0
1.1
1.2
1.2
1.3
1.2
1.2
1.2
1.4
1.3
1.2
1.2
1.2
1.2
1.3
1.3
1.3
1.3
1.4
1.4
1.5
1.6
1.6
1.4
1.4
1.3
1.4
1.5
1.4
1.4
1.2
1.4
1.3
1.4
1.5
1.3
1.3
1.3
1.3
1.3
1.2

3.9
6.0
4.6
6.9
7.4
9.2
4.9
6.3
6.9
2.8
13.5
11.8
4.6
6.3
8.8
8.0
7.9
7.3
9.8
10.7
12.1
8.0
8.7
10.8
14.7
10.3
8.9
10.3
8.6
8.1
3.8
-0.1
3.4
16.1
12.9
8.0
9.4
8.7
8.8
8.2
9.6
6.7
6.8
6.7
6.1
5.7
7.0
0.3

1.6
2.0
1.2
-0.2
0.3
0.7
1.5
0.7
3.2
1.2
0.0
5.6
4.2
4.0
3.9
0.7
2.8
1.7
2.5
1.8
2.4
3.1
1.8
4.0
3.8
4.8
7.6
6.3
7.9
6.4
2.8
-1.3
-1.2
2.5
4.6
5.3
5.0
3.5
3.8
7.9
6.4
5.6
5.5
2.6
2.9
4.6
2.1
2.5

105.9
106.0
106.3
106.7
107.2
104.7
105.4
104.4
105.4
103.9
102.6
103.3
101.4
102.7
102.7
99.0
98.7
99.0
98.6
98.1
96.8
96.8
96.4
94.6
94.0
92.0
90.7
89.4
88.0
88.6
91.3
92.0
94.0
92.1
91.1
90.5
89.7
90.8
88.2
87.2
86.3
85.2
87.2
87.0
86.1
87.9
86.1
97.2

Japan
real GDP
growth

2.9
-1.0
-4.2
-0.7
-0.6
4.1
2.6
1.5
-2.1
5.1
1.5
4.4
4.1
-0.1
0.4
-0.9
0.8
5.4
1.3
0.9
1.7
1.6
-0.4
5.4
4.1
0.2
-1.4
3.7
2.7
-5.2
-3.7
-12.4
-15.0
6.3
1.0
7.1
5.1
5.1
4.7
-1.1
-8.0
-2.1
9.5
-1.2
5.2
0.3
-3.5
-1.4

Japan
inflation

Japan
bilateral
dollar
exchange
rate
(yen/USD)

U.K.
real GDP
growth

U.K.
inflation

U.K.
bilateral
dollar
exchange
rate
(USD/pound)

0.6
-2.0
-0.6
-1.8
-1.1
0.1
-0.4
-0.6
0.0
0.3
-0.6
-0.7
0.6
-0.3
0.0
1.8
-0.9
-1.2
-1.3
0.7
1.3
-0.1
0.5
-0.4
-0.3
0.0
0.1
2.3
1.3
1.7
3.4
-2.2
-3.5
-1.7
-1.4
-1.5
1.1
-1.2
-2.2
1.2
0.0
-0.7
0.1
-0.7
2.3
-0.9
-2.0
-4.4

125.5
124.7
119.2
131.0
132.7
119.9
121.7
118.8
118.1
119.9
111.4
107.1
104.2
109.4
110.2
102.7
107.2
110.9
113.3
117.9
117.5
114.5
118.0
119.0
117.6
123.4
115.0
111.7
99.9
106.2
105.9
90.8
99.2
96.4
89.5
93.1
93.4
88.5
83.5
81.7
82.8
80.6
77.0
77.0
82.4
79.8
77.9
75.7

5.4
2.7
2.2
1.5
1.7
3.4
3.4
3.8
2.4
4.9
5.0
4.9
3.0
1.0
0.0
2.5
2.5
5.1
3.3
4.4
2.0
1.2
0.8
3.8
4.6
5.0
4.8
0.7
0.3
-3.6
-6.9
-8.1
-5.9
-0.7
1.6
1.7
2.4
2.9
2.5
-1.7
2.0
0.3
2.1
-1.4
-1.2
-1.5
4.1
-6.5

0.1
3.1
1.0
0.0
1.9
0.9
1.4
1.9
1.6
0.3
1.7
1.7
1.3
1.0
1.1
2.4
2.6
1.8
2.7
1.4
1.9
3.0
3.3
2.6
2.6
1.6
0.3
4.0
3.7
5.5
5.9
0.6
0.0
1.9
3.7
3.2
4.1
2.7
2.6
4.3
6.6
4.0
4.2
3.9
1.8
1.1
3.0
1.6

1.4
1.4
1.5
1.5
1.4
1.5
1.6
1.6
1.6
1.7
1.7
1.8
1.8
1.8
1.8
1.9
1.9
1.8
1.8
1.7
1.7
1.8
1.9
2.0
2.0
2.0
2.0
2.0
2.0
2.0
1.8
1.5
1.4
1.6
1.6
1.6
1.5
1.5
1.6
1.5
1.6
1.6
1.6
1.6
1.6
1.6
1.6
1.6

(continued on next page)

March 2013

Table A.2. Supervisory severely adverse scenario: International—continued

Date

Euro area
real GDP
growth

Q1 2013
Q2 2013
Q3 2013
Q4 2013
Q1 2014
Q2 2014
Q3 2014
Q4 2014
Q1 2015
Q2 2015
Q3 2015
Q4 2015

-6.8
-4.3
-2.3
-0.8
0.4
1.2
1.7
2.0
2.0
2.0
2.0
2.0

Euro area
inflation

Euro area
bilateral
dollar
exchange
rate
($/euro)

Developing
Asia
real GDP
growth

Developing
Asia
inflation

Developing
Asia
bilateral
dollar
exchange
rate
(F/USD,
index,
base =
2000 Q1)

1.0
0.4
0.2
0.2
0.4
0.6
0.8
0.9
1.1
1.2
1.3
1.4

1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.2
1.2
1.2

3.9
5.9
6.9
7.5
7.9
8.1
8.3
8.4
8.5
8.5
8.6
8.6

1.8
0.5
0.0
0.1
0.6
1.1
1.4
1.7
1.8
1.9
2.0
2.1

97.9
96.9
95.1
93.0
91.2
89.7
88.5
87.5
86.6
86.0
85.5
85.2

Note: Refer to “Data Notes” on page 34 for more information on variables.

Japan
real GDP
growth

-4.5
-6.5
-6.8
-5.5
-3.1
-1.1
0.3
1.1
1.4
1.5
1.6
1.6

Japan
inflation

Japan
bilateral
dollar
exchange
rate
(yen/USD)

U.K.
real GDP
growth

U.K.
inflation

U.K.
bilateral
dollar
exchange
rate
(USD/pound)

-4.1
-5.0
-4.7
-3.6
-1.9
-0.5
0.3
0.5
0.4
0.2
0.1
0.1

77.8
78.7
78.7
78.4
78.2
78.1
78.2
78.5
79.0
79.6
80.3
80.9

-6.6
-3.7
-1.4
0.1
0.9
1.6
2.1
2.7
3.2
3.5
3.6
3.7

0.7
-0.6
-1.0
-0.7
0.0
0.6
1.0
1.3
1.4
1.5
1.6
1.6

1.6
1.6
1.6
1.6
1.6
1.6
1.6
1.5
1.5
1.5
1.5
1.5

DFAST 2013: Methodology and Results

Data Notes
Sources for data through 2012:Q3 (as released through 11/13/2012).
U.S. real GDP growth: Percent change in real Gross Domestic Product at an annualized rate, Bureau of Economic Analysis.
U.S. nominal GDP growth: Percent change in nominal Gross Domestic Product at an annualized rate, Bureau of
Economic Analysis.
U.S. real disposable income growth: Percent change in nominal disposable personal income divided by the price
index for personal consumption expenditures at an annualized rate, Bureau of Economic Analysis.
U.S. nominal disposable income growth: Percent change in nominal disposable personal income at an annualized
rate, Bureau of Economic Analysis.
U.S. unemployment rate: Quarterly average of monthly data, Bureau of Labor Statistics.
U.S. CPI inflation: Percent change in the Consumer Price Index at an annualized rate, Bureau of Labor
Statistics.
U.S. 3-month Treasury yield: Quarterly average of 3-month Treasury bill secondary market rate discount basis,
Federal Reserve Board.
U.S. 10-year Treasury yield: Quarterly average of the yield on 10-year U.S. Treasury bonds, constructed for
FRB/U.S. model by Federal Reserve staff based on the Svensson smoothed term structure model; see Lars E.
O. Svensson (1995), “Estimating Forward Interest Rates with the Extended Nelson-Siegel Method,” Quarterly
Review, no. 3, Sveriges Riksbank, pp. 13–26.
U.S. BBB corporate yield: Quarterly average of the yield on 10-year BBB-rated corporate bonds, constructed
for FRB/U.S. model by Federal Reserve staff using a Nelson-Siegel smoothed yield curve model; see Charles R.
Nelson and Andrew F. Siegel (1987), “Parsimonious Modeling of Yield Curves,” Journal of Business, vol. 60,
pp. 473–89. Data prior to 1997 is based on the WARGA database. Data after 1997 is based on the Merrill
Lynch database.
U.S. mortgage rate: Quarterly average of weekly series of Freddie Mac data.
U.S. Dow Jones Total Stock Market Index: End of quarter value, Dow Jones.
U.S. House Price Index: CoreLogic, index level, seasonally adjusted by Federal Reserve staff.
U.S. Commercial Real Estate Price Index: From Flow of Funds Accounts of the United States, Federal Reserve
Board (Z.1 release); the series corresponds to the data for price indexes: Commercial Real Estate Price Index
(series FL075035503.Q), divided by 1,000.
U.S. Market Volatility Index (VIX): Chicago Board Options Exchange, converted to quarterly by using the
maximum value in any quarter.
Euro area real GDP growth: Staff calculations based on Statistical Office of the European Communities via
Haver, extended back using ECB Area Wide Model dataset (ECB Working Paper series no. 42).
Euro area inflation: Staff calculations based on Statistical Office of the European Communities via Haver.
Developing Asia real GDP growth: Staff calculations based on Bank of Korea via Haver; Chinese National
Bureau of Statistics via CEIC; Indian Central Statistical Organization via CEIC; Census and Statistics Depart-

March 2013

ment of Hong Kong via CEIC; and Taiwan Directorate-General of Budget, Accounting, and Statistics via
CEIC.
Developing Asia inflation: Staff calculations based on Bank of Korea via CEIC; Chinese Statistical Information
and Consultancy Service via CEIC and IMF Recent Economic Developments; Labour Bureau of India via
CEIC and IMF; Census and Statistics Department of Hong Kong via CEIC; and Taiwan Directorate-General
of Budget, Accounting, and Statistics via CEIC.
Japan real GDP growth: Cabinet Office via Haver.
Japan inflation: Ministry of Internal Affairs and Communications via Haver.
U.K. real GDP growth: Office of National Statistics via Haver.
U.K. inflation: Office of National Statistics (uses Retail Price Index to extend series back to 1960) via Haver.
Exchange rates: Bloomberg.

Appendix B: Models to Project
Net Income and Stressed Capital

This appendix describes the models used to project
stressed capital ratios and pre-tax net income and its
components for the 18 BHCs subject to DFAST
2013.27 The models fall into four broad categories:
1. Models to project losses on loans held in the
accrual loan portfolio.
2. Models to project other types of losses, including
those from changes in fair value on loans held for
sale or measured under the fair-value option,
securities, trading and counterparty exposures,
losses related to operational-risk events, and
mortgage repurchase/put-back losses.
3. Models to project the components of PPNR (revenues and non-credit-related expenses).
4. The model to project capital ratios, given projections of pre-tax net income, assumptions for
determining provisions into the ALLL, and
assumed capital actions under the Dodd-Frank
Act stress test rule.
A majority of the models described here were refined
incrementally over the past year—in some instances,
benefitting from more granular data collection
through the FR Y-14 report. However, some of the
models were either changed substantially or newly
implemented for DFAST 2013, including the commercial real estate mortgage model, the credit card
27

In connection with DFAST 2013, and in addition to the models
developed and data collected by the Federal Reserve, the Federal Reserve used proprietary models or data licensed from the
following providers: Andrew Davidson & Co., Inc.; BlackRock
Financial Management, Inc.; Bloomberg Finance L.P.; CB
Richard Ellis, Inc.; CoreLogic Solutions, LLC; Equifax Information Services LLC; Fitch Solutions, Inc.; Intex Solutions,
Inc.: Investortools, Inc.; McDash Analytics, LLC, a wholly
owned subsidiary of Lender Processing Services, Inc.; Markit
Group; Moody’s Analytics, Inc.; Morningstar Credit Ratings,
LLC; Municipal Securities Rulemaking Board; and Standard &
Poor’s Financial Services LLC. In addition, with respect to the
global market shock component of the severely adverse scenario, the Federal Reserve used proprietary data licensed from
the following providers: Bank of America Corporation; Barclays Bank PLC; Bloomberg Finance L.P.; JPMorgan Chase &
Co.; Markit Group; Moody’s Analytics, Inc.; Standard & Poor’s
Financial Services LLC; and Thomson Reuters LLC.

model, the modeling of losses due to operational-risk
events, and the PPNR model.

Losses on the Accrual Loan Portfolio
More than a dozen individual models are used to
project losses on loans held in the accrual loan portfolio. The individual loan types modeled can broadly
be divided into wholesale loans, such as commercial
and industrial (C&I) loans and commercial real estate
(CRE) loans, and retail loans, including various types
of residential mortgages, credit cards, student loans,
auto loans, small business loans, and other consumer
lending. In some cases, these major categories comprise several subcategories, each with its own loss
projection model, but the models within a subcategory are similar in structure and approach. The
models project losses using detailed loan portfolio
data provided by the BHCs on the FR Y-14 report.
Two general approaches are taken to model losses on
the accrual loan portfolio. In the first approach—an
approach broadly used for DFAST 2013—the models
estimate expected losses under the macroeconomic
scenario; that is, they project the probability of
default (PD), loss given default (LGD), and exposure
at default (EAD) for each quarter of the planning
horizon. Expected losses in quarter t are the product
of these three components:
Losst = PDt * LGDt * EADt
PD is generally modeled as part of a transition process in which loans move from one payment status to
another (e.g., from current to delinquent) in response
to economic conditions. Default is the last possible
transition and PD represents the likelihood that a
loan will default during a given period. The number
of payment statuses and the transition paths modeled
differ by loan type.
LGD is typically defined as a percentage of EAD
and is based on historical data. For some loan types,

DFAST 2013: Methodology and Results

LGD is modeled as a function of borrower, collateral, or loan characteristics and the macroeconomic
variables from the severely adverse scenario. For
other loan types, it is assumed to be a fixed percentage for all loans in a category. Finally, the approach
to EAD varies by loan type and depends on whether
the outstanding loan amount can change between the
current period and the period in which the loan
defaults (e.g., for lines of credit).
In the second approach, the models capture the historical behavior of net charge-offs relative to changes
in macroeconomic and financial market variables and
loan portfolio characteristics.
The loss models primarily focus on losses arising
from loans in the accrual loan portfolio as of September 30, 2012. The loss projections also incorporate losses on loans originated or purchased after the
planning horizon begins. These incremental loan balances are calculated based on the BHCs’ own projections of loan balances over the planning horizon
under the severely adverse scenario. These balances
are assumed to have the same risk characteristics as
those of the loan portfolio as of September 30, 2012,
with the exception of loan age in the retail portfolios,
where seasoning is incorporated. This is a simple, but
generally conservative, assumption.
Loss projections generated by the models are
adjusted to take account of purchase accounting
treatment, which recognizes discounts on impaired
loans acquired during mergers, and any other writedowns already taken on loans held in the accrual loan
portfolio. This latter adjustment ensures that losses
related to these loans are not double-counted in the
projections.

The PD for a C&I loan is projected over the planning
horizon by first calculating the loan’s PD at the
beginning of the planning horizon and then projecting it forward using an estimated equation that
relates historical changes in PD to changes in the
macroeconomic environment. The PD as of September 30, 2012, is calculated for every C&I loan in a
BHC’s portfolio using detailed, loan-level information submitted by the BHC. For publicly traded borrowers, a borrower-specific PD, based on the
expected default frequency, is used. For other borrowers, the PD is estimated based on the BHC’s
internal credit rating, which is converted to a standardized rating scale. Loans that are 90 days past
due, in non-accrual status, or that have an ASC
310-10 reserve as of September 30, 2012 are assigned
a PD of 100 percent.
Quarterly changes in the PD after the third quarter
of 2012 are projected over the planning horizon
using a series of equations that relate historical
changes in the average PD as a function of changes
in macroeconomic variables, including changes in
real GDP, the unemployment rate, and the spread on
BBB-rated corporate bonds. The equations are estimated separately by borrower industries, credit quality categories, and countries.
The LGD for a C&I loan at the beginning of the
planning horizon is determined by the line of business, seniority of lien (if secured), country, and ASC
310-10 reserve, if applicable. The LGD is then projected forward by relating the change in the LGD to
changes in the PD. In the model, the PD is used as a
proxy for economic conditions, and, by construct,
increases in PD generally lead to higher LGDs.

Losses stemming from default on corporate loans are
projected at the loan level using an expected-loss
modeling framework. Corporate loans consist of a
number of different categories of loans, as defined by
the FR Y-9C. The largest group of these loans
include C&I loans, which are generally defined as
loans with more than $1 million in committed balances and are “graded” using a BHC’s corporate
loan rating process.28

The EAD for closed-end C&I loans is assumed to
equal the loan’s outstanding balance. The EAD for
C&I revolving lines of credit equals the sum of the
funded balance and a portion of the unfunded commitment, which reflects the amount that is likely to
be drawn down by the borrower in the event of
default. This drawdown amount was estimated based
on the historical drawdown experience for defaulted
U.S. syndicated loans that are in the Shared National
Credit (SNC) database.29 The EAD for standby letters of credit and trade finance credit are conservatively assumed to equal the total commitment.

Wholesale Lending: Corporate Loans

All definitions of loan categories and default in this appendix
are definitions used for the purposes of the supervisory stress
test models and do not necessarily align with general industry
definitions or classifications.

SNCs have commitments of greater than $20 million and are
held by three or more regulated participating entities. See www
.federalreserve.gov/bankinforeg/snc.htm for additional information about SNCs.

March 2013

Other corporate loans that are similar in some
respects to C&I loans are modeled using the same
framework. These loans include owner-occupied
commercial real estate loans, capital equipment
leases, loans to depositories, and other loans.30 Projected losses for these loans are disclosed in the other
loans category.

Wholesale Lending: Commercial
Real Estate Mortgages
CRE mortgages are loans collateralized by domestic
and international multifamily or non-farm, nonresidential properties, and construction and land
development loans (C&LD), as defined by the FR
Y-9C. Losses stemming from default on CRE mortgages are projected at the loan level using an
expected-loss modeling framework.
The PD model for CRE mortgages is a hazard model
of the probability that a loan transitions from current to default status, given the characteristics of the
loan as well as macroeconomic variables, such as
house prices and CRE vacancy rates, at both the geographic market and national level. Once defaulted,
the model assumes the loan does not re-perform; the
effect of re-performance on the estimated loan loss is
captured in the LGD model. A CRE mortgage loan
is considered in default if it is 90 days past due, in
non-accrual status, has an ASC 310-10 reserve, or
had a very low internal credit rating at the most
recent time its maturity was extended. The effect of
seasoning and loan maturity on the PD is estimated
to be different for income-producing and C&LD
loans, and is estimated separately for each loan type
using historical FR Y-14 data. However, the effect of
other loan characteristics and the macroeconomic
variables is assumed to be the same for incomeproducing properties and C&LD loans and is estimated using a single model for both types of loans
using historical CMBS data.
The LGD for CRE mortgages is estimated using
Y-14 data on ASC 310-10 reserves. The model first
estimates the probability that a defaulted loan will
have losses as a function of loan characteristics and
macroeconomic variables, and then, using loans with
losses, estimates the loss on the CRE mortgage, as a
function of the expected probability of loss, charac30

The corporate loan category also includes loans that are dissimilar from typical corporate loans, such as securities lending
and farmland loans, which are generally a small share of BHC
portfolios. For these loans, a conservative and uniform loss rate
based on analysis of historical data was assigned.

teristics of the loan, and macroeconomic variables.
Finally, the EAD for CRE mortgages is assumed to
equal the loan’s outstanding balance for amortizing
loans and the full committed balance for C&LD
loans.

Retail Lending: Residential Mortgages
Residential mortgages held in BHC portfolios include
first and junior liens, either closed-end loans or
revolving credits, that are secured by one- to-fourfamily residential real estate as defined by the FR
Y-9C. Losses stemming from default on residential
mortgages are projected at the loan level using an
expected-loss modeling framework.31
The PD model for first-lien residential mortgages
estimates the probability that a loan transitions to
different payment statuses, including current, delinquent, default, and paid off. Separate PD models are
estimated for three types of closed-end, first-lien
mortgages: fixed-rate, adjustable-rate, and option
adjustable-rate mortgages. The PD model specification varies somewhat by loan type, but in general,
each model estimates the probability that a loan transitions from one payment state to another (e.g., from
current to delinquent or from delinquent to default)
over a single quarter, given the characteristics of the
loan, borrower, and underlying property as well as
macroeconomic variables such as local house prices,
the statewide unemployment rate, and interest rates.32
Origination vintage effects are also included in part
to capture unobserved characteristics of loan quality.
The historical data used to estimate this model are
industry-wide, loan-level data from many banks and
mortgage loan originators. These estimated PD models are used to simulate default associated with the
severely adverse scenario for each loan reported by
each BHC. Loans that are 180 days or more past due
as of September 30, 2012, are considered in default
and are assigned a PD of 100 percent.
The LGD for residential mortgages is estimated using
two models. One model estimates the amount of time
that elapses between default and real estate owned
(REO) disposition (timeline model), while the other
relates characteristics of the defaulted loan, such as
31

To predict losses on new originations over the planning horizon,
newly originated loans are assumed to have the same risk characteristics as the existing portfolio, with the exception of the
loan age, LTV, and delinquency status.
The effects of loan modification and evolving modification
practices are captured in the probability that a delinquent loan
transitions back to current status (re-performing loans).

DFAST 2013: Methodology and Results

the property value at default, to one component of
losses net of recoveries—the proceeds from the sale
of the property net of foreclosure expenses (loss
model).33 These net proceeds are calculated from historical data on loan balances, servicer advances, and
losses from defaulted loans in private-label mortgagebacked securities (RMBS). These RMBS data are
also used to estimate the LGD loss model separately
for prime jumbo loans, subprime, and alt-A loans.34
Finally, using the elapsed time between default and
REO disposition estimated in the timeline model,
total estimated losses are allocated into credit losses
on the defaulted loans, which are fully written down
at the time of default, or net losses arising from the
eventual sale of the underlying property (other real
estate owned—or OREO—expenses), which flow
through PPNR. House price changes from the time
of default to foreclosure completion (REO acquisition) are captured in LGD, while house price changes
after foreclosure completion and before sale of the
property are captured in OREO expenses. The LGD
for loans already in default as of September 30, 2012,
includes further home price declines through the
point of foreclosure.
Home equity loans (HELs) are junior-lien, closedend loans, and home equity lines of credit (HELOCs)
are revolving open-end loans extended under lines of
credit, both secured by one- to four-family residential
real estate as defined by the FR Y-9C. Losses stemming from default on HELs and HELOCs are projected at the loan level in an expected loss framework
that is similar to first-lien mortgages, with a few differences. In the PD model for HELs and HELOCs,
the delinquency state is defined as ever delinquent, to
simplify the competing risk-model structure. The
model also assumes that second-lien HELs and
HELOCs that are current as of September 30, 2012,
but are behind a seriously delinquent first-lien will all
default within the planning horizon. The LGD for
HEL and HELOCs is estimated using data from
private-label mortgage-backed securities, using the
same models used for closed-end first-lien, but the
33

Other components of losses net of recoveries are calculated
directly from available data. Private mortgage insurance is not
incorporated into the LGD models. Industry data suggest that
insurance coverage on portfolio loans is infrequent and cancellation or nullification of guarantees was a common occurrence
during the recent downturn.
The differences between characteristics of mortgages in RMBS
and mortgages in bank portfolios, such as loan-to-value ratio
(LTV), are controlled for by including various risk characteristics in the LGD model, such as original LTV ratio, credit score,
and credit quality segment (prime, alt-A, and subprime).

estimated total mortgage losses for properties with a
defaulted HEL or HELOC are allocated based on the
lien position. Finally, for HELOCs, EAD is conservatively assumed to equal the credit limit.

Retail Lending: Credit Cards
Credit cards include both general purpose and
private-label credit cards, as well as charge cards, as
defined by the FR Y-9C. Credit card loans extended
to individuals are included in retail credit cards, while
credit cards loans extended to businesses and corporations are included in other retail lending and are
modeled separately. Losses stemming from defaults
on credit cards are projected at the loan level using
an expected-loss modeling framework.
The PD model for credit cards estimates the probability that a loan transitions from delinquency status
to default status, given the characteristics of the
account and borrower as well as macroeconomic
variables such as unemployment. When an account
defaults, it is assumed to be closed and does not
return to current status. Credit card loans are considered in default when they are 120 days past due.
Because the relationship between the PD and its
determinants can vary with the initial status of the
account, separate transition models are estimated for
accounts that are current and active, current and
inactive accounts, and delinquent accounts. In addition, because this relationship can also vary with time
horizons, separate transition models are estimated for
short-, medium-, and long-term horizons. The historical data used to estimate this model are industrywide, loan-level data from many banks, and separate
models were estimated for bank cards and charge
cards. The PD model is used to forecast the PD for
each loan reported by each BHC in the Y-14M
report.
The LGD for credit cards is assumed to be a
fixed percentage and is calculated separately for bank
cards and charge cards based on historical industry
data on LGD during the most recent economic
downturn. The EAD for credit cards equals the sum
of the amount outstanding on the account and a
portion of the credit line, which reflects the amount
that is likely to be drawn down by the borrower
between the beginning of the planning horizon and
the time of default. This drawdown amount is estimated as a function of account and borrower characteristics. Because this relationship can vary with the
initial status of the account and time to default, separate models are estimated for current and delinquent

March 2013

accounts and for accounts with short-, medium-, and
long-term transition to default. For accounts that are
current, separate models were also estimated for different credit-line-size segments.

Retail Lending: Auto
Auto loans are consumer loans extended for the purpose of purchasing new and used automobiles and
light motor vehicles as defined by the FR Y-9C.
Losses stemming from default in auto retail loan
portfolios are projected at the portfolio segment level
using an expected loss framework.
The PD model for auto loans estimates the probability that a loan transitions from either a current or
delinquent status to default status, given the characteristics of the loan and borrower as well as macroeconomic variables such as house prices and the
unemployment rate (which, in some cases, are interacted with loan and borrower characteristics to allow
for greater sensitivity to stressful conditions in highrisk segments). Default on auto loans is defined
based on either the payment status (120 days past
due), actions of the borrower (bankruptcy), or the
lender (repossession). Because the relationship
between the PD and its determinants can vary with
the initial status of the account, separate transition
models are estimated for accounts that are current
and delinquent accounts. The historical data used to
estimate this model are loan-level, credit bureau data.
The LGD for auto loans is estimated given the characteristics of the loan as well as macroeconomic variables. The historical data used to estimate this model
are pooled, segment-level data provided by the BHCs
on the FR Y-14Q. The EAD for auto loans is based
on the typical pattern of amortization of loans that
ultimately defaulted in historical credit bureau data.
The estimated EAD model captures the average
amortization by loan age for current and delinquent
loans over nine quarters.

Retail Lending: Other Retail Lending
Other retail lending includes the small business loan
portfolio, the other consumer loan portfolio, the student loan portfolio, the business and corporate credit
card portfolio, and international retail portfolio.
Losses due to default on other retail lending are forecast by modeling net charge-off rates as a function of
portfolio risk characteristics and macroeconomic
variables, then using this model to predict future
charge-offs consistent with the macroeconomic vari-

ables provided in the severely adverse scenario.35 The
predicted net charge-off rate is applied to balance
projections provided by the BHCs to estimate projected losses. Default is defined as 90 days or more
past due for domestic and international other consumer loans and 120 days or more past due for student loans, small business loans, corporate cards, and
international retail portfolios. The net charge-off rate
is modeled in a system of equations that also includes
the delinquency rate and the default rate. In general,
each rate is modeled in an autoregressive specification that also includes the rate in the previous delinquency state, characteristics of the underlying loans,
macroeconomic variables and, in some cases, seasonal factors. The models are specified to implicitly
capture roll-rate dynamics. In some cases, the characteristics of the underlying loans, such as dummy variables for each segment of credit score at origination,
are also interacted with the macroeconomic variables
to capture differences in sensitivities across risk segments to changes in the macroeconomic environment. Each retail product type is modeled separately
and, for each product type, economic theory and the
institutional characteristics of the product guide the
inclusion and lag structure of the macroeconomic
variables in the model.
Because of data limitations and the relatively small
size of these portfolios, the net charge-off rate for
each loan type is modeled using industrywide, monthly data at the segment level. For most
portfolios, these data are collected on the FR Y-14Q
Retail schedule, which segments each portfolio by
characteristics such as borrower credit score; loan
vintage; type of facility (e.g., installment versus
revolving); and, for international portfolios, geographic region.36
Charge-off rates are projected by applying the estimated system of equations to each segment of the
BHC’s loan portfolio as of September 30, 2012. The
portfolio level charge-off rate equals the dollarweighted average of the segment-level charge-off
rates.37 These projected charge-off rates are applied
35

An exception is made for the government-guaranteed portion of
BHCs’ student loan portfolios, to which an assumed monthly
PD of 1.5 percent and LGD of 3 percent is applied.
Business and corporate credit card portfolio data, which previously were collected on the FR Y-14Q Retail schedule, are now
collected at the loan-level on the FR Y-14M Credit Card schedule and subsequently aggregated to the segment level.
The dollar weights used are based on the distribution reported
during the last observation period. This method assumes that
the distribution of loans across risk segments, other than delin-

DFAST 2013: Methodology and Results

to the balance projections supplied by the BHC to
calculate portfolio losses.

Loan-Loss Provisions for the
Accrual Loan Portfolio
Losses on the accrual loan portfolio flow into net
income through provisions for loan and lease losses.
Provisions for loan and lease losses equal projected
loan losses for the quarter plus the amount needed
for the ALLL to be at an appropriate level at the end
of the quarter, which is a function of projected future
loan losses. The appropriate level of ALLL at the end
of a given quarter is generally assumed to be the
amount needed to cover projected loan losses over
the next four quarters.38 Because this calculation of
ALLL is based on projected losses under the severely
adverse scenario, it may differ from a BHC’s actual
level of ALLL at the beginning of the planning horizon, which is based on the BHC’s assessment of
future losses in the current economic environment.
Any difference between these two measures of ALLL
is smoothed into the provisions projection over the
nine quarters of the planning horizon. Because projected loan losses include off-balance sheet commitments, the BHC’s allowance at the beginning of the
planning horizon for credit losses on off-balance
sheet exposures (as reported on the FR Y-9C) is subtracted from the provisions projection in equal
amounts each quarter.

Other Losses
Loans Held for Sale or Measured under
the Fair-Value Option
Certain loans are not accounted for on an accrual
basis. Loans to which the fair-value option (FVO) is
applied are valued as mark-to-market assets; loans
under the held-for-sale (HFS) and some loans under
the held-for-investment (HFI) accounting classifications are carried at the lower of cost or market value.
FVO, HFS, and HFI loan portfolios are identified by
the BHCs and reported on the FR Y-14. Losses
related to FVO, HFS, and HFI loans are recognized

quency status segments, remains constant over the projection
period.
For loan types modeled in a charge-off framework, the appropriate level of ALLL was adjusted to reflect the difference in
timing between the recognition of expected losses and that of
charge-offs.

in the income statement at the time of the
devaluation.
For the six BHCs subject to the global market shock,
changes in the value of these loans are calculated
using the price shocks applied to similar loans in
other mark-to-market positions on the BHCs’ balance sheets (e.g., trading account positions). For the
remaining BHCs, losses on FVO, HFS, and HFI
loans are not projected separately, and any gains or
losses on these loans are captured in PPNR as part of
non-interest income. The PPNR model is described
later in this paper (see page 46).
For the six BHCs subject to the global market shock,
losses on C&I loans held under FVO, HFS, and HFI
accounting standards are estimated by applying
the percent change in the secondary market prices for
corporate loans during the second half of 2008 to
current outstanding and committed loan balances.
The loss rates applied to C&I loans vary with the
credit rating reported by the BHCs and with the
amount funded. Loss rates for investment-grade
loans with more than half of their credit line used are
based on historical price changes for investment
grade loans, while loss rates for investment-grade
loans with less than half of their credit line used are
based on changes in CDS spreads. Loss rates for all
non-investment grade loan facilities, regardless of
the percent funded, are based on price changes for
loans with the same credit rating.
Losses on CRE and retail loans held under FVO,
HFS, and HFI accounting standards are estimated in
a similar way. The loss rate applied to these loans are
taken from the global market shock and vary by
major type of loan (e.g., residential mortgages, student loans, credit cards, and the major categories of
CRE loans) and by loan vintage (year of origination). Losses on all major residential and other retail
asset types (including student loans and credit cards)
are estimated applying a percent change in value
based on the loan type and vintage to the carrying
value of FVO and HFS exposures provided by the
firms. Because retail FVO and HFS loans are generally of relatively high credit quality, the changes in
value are based on the global market shock for AAArated positions in the non-agency residential whole
loans, credit card asset-backed securities (ABS), auto
ABS, and student loan ABS portfolios. No losses are
assumed for residential mortgage loans under forward contract with the government-sponsored enterprises (GSEs).

March 2013

Securities in the Available-for-Sale and
Held-to-Maturity Portfolios
Losses on securities held in the available-for-sale
(AFS) or held-to-maturity (HTM) portfolios are projected other-than-temporary impairment (OTTI)
over the planning horizon. OTTI projections incorporate other-than-temporary differences between
amortized cost and fair market value due to credit
impairment, but not differences reflecting changes in
liquidity or market conditions.
Some of the AFS/HTM securities, including U.S.
Treasury and U.S. government agency obligations
and U.S. government agency mortgage-backed securities (MBS), are assumed not to be at risk for the
kind of credit impairment that results in OTTI
charges. The remaining securities can be grouped into
two basic categories: securitizations, where the value
of the security depends on the value of an underlying
pool of collateral, and direct obligations such as corporate or sovereign bonds, where the value of the
security depends primarily on the credit quality of
the issuer.39
In all, 10 separate models are used to project OTTI,
reflecting differences in the basic structure of the
securities (securitized versus direct obligation) and
differences in underlying collateral and obligor type.
Overall, the OTTI projections involve CUSIP-level
analysis of more than 70,000 individual positions at
the 18 BHCs.
For securitized obligations, credit and prepayment
models estimate delinquency, default, severity, and
prepayment vectors on the underlying pool of collateral under the supervisory scenarios. In most cases,
these projections incorporate relatively detailed information on the underlying collateral characteristics for
each individual security, derived from commercial
databases that contain loan-level collateral and security structure information. Delinquency, default,
severity, and prepayment vectors are projected either
using econometric models developed by the Federal
Reserve or third-party models designed to project
these estimates in stressed economic environments.
The models used vary with the type of underlying
collateral, but generally estimate the relationship
between the collateral’s performance vectors and economic variables, such as the unemployment rate and
39

Equities are also held in the AFS portfolios, although in small
amounts. Losses on these positions are calculated by applying
market value shocks based on the equity price changes in the
supervisory scenarios.

house prices. These vectors are then applied to a cash
flow engine that captures the specific structure of
each security (e.g., tranche, subordination, and payment rules) to calculate the intrinsic value (present
value of the cash flows) for that security. If the projected intrinsic value is less than the value at which
the security is being carried on the BHC’s balance
sheet (amortized cost), then the security is considered
to be other than temporarily impaired, and OTTI is
calculated as the difference between amortized cost
and intrinsic value.
For direct obligations, the basic approach is to assess
the PD or severe credit deterioration for each security
issuer or group of security issuers over the planning
horizon. PD is either modeled directly or inferred by
modeling changes in expected default frequencies or
credit default swap (CDS) spreads for the bonds in
question. A security is considered other than temporarily impaired if the projected value of the PD or
CDS spread crossed a predetermined threshold
level—generally the level consistent with a CCC/Caa
rating—at any point during the planning horizon.
LGD on these securities is based on historical data
on bond recovery rates. OTTI is calculated as the difference between the bond’s amortized cost and its
projected value under the supervisory scenarios.
No OTTI charges are assigned to securities acquired
by the BHCs after September 30, 2012, (“incremental
balances”) because these are assumed to be purchased at already discounted prices. This assumption
is also consistent with historical data showing that
the composition of the AFS and HTM portfolios
tends to shift toward U.S. Treasury and agency obligations in times of economic stress, suggesting that
incremental AFS/HTM balances are less likely to be
at risk of generating OTTI charges.

Trading and Counterparty Credit Risk
Total potential mark-to-market losses stemming from
trading positions under a stressed market environment can be broken into two primary types. The first
type of loss arises from a decrease in the market
value of trading positions, regardless of the BHC’s
counterparties. The second type is the counterparty
credit risk associated with changes in counterparty
exposures and with deterioration of counterparties’
creditworthiness under stressed market conditions,
which adversely affects the riskiness of positively valued trading positions. The models used to project
losses on trading positions under the global market
shock account for both sources of potential losses,

DFAST 2013: Methodology and Results

incorporate the accounting treatment of these positions, and generally rely on information provided by
firms on estimated sensitivities of their exposures to
specific risk factor shocks. Because positions in the
trading account are mark-to-market on a daily basis,
the approach used to generate loss projections on
trading positions is intended to capture the marketvalue effect of the global market shock.
Losses on trading positions, such as equities, FX,
interest rates, commodities, credit products, private
equity, and other fair-value assets, arising from the
global market shock are calculated using the BHCs’
own estimates of the sensitivity of the value of these
positions to changes in a wide range of market rates,
prices, spreads, and volatilities. Trading losses are calculated by multiplying these sensitivities by the risk
factor changes included in the global market shock
developed by the Federal Reserve. These shocks are
assumed to be instantaneous and no additional hedging, recovery in value, or changes in positions are
incorporated into the loss calculation.
Counterparty credit losses capture the effect of the
global market shock on counterparty exposures and
on credit valuation adjustments (CVA) and incremental default risk (IDR) of the six BHCs with large
trading positions. CVAs are adjustments above and
beyond the mark-to-market valuation of the BHCs’
trading portfolios that capture changes in the risk
that a counterparty to derivatives transaction or
other trading position will default on its obligations.
Using detailed data provided by the six trading
BHCs on the FR Y-14A Counterparty schedule, each
trading firm’s baseline and stressed CVA for each
counterparty or ratings band is calculated as a function of unstressed and stressed values of exposure,
PD, and LGD. CVA losses equal the difference
between the baseline and the stressed CVAs.
In addition to CVA and mark-to-market losses on
trading positions, default risk in the trading book is
captured through incremental default risk (IDR).
IDR estimates the potential additional loss stemming
from the default of individual counterparties in
excess of the CVA-related losses associated with the
defaulting counterparties or obligors. IDR complements CVA in the stress tests by estimating the losses
from jump-to-default in the tail of the distribution of
defaults, where the tail percentile is calibrated using
the corporate bond spread in the severely adverse
scenario.

The IDR models estimate losses from jump-todefault for various exposure types, including singlename, index and index-tranche, securitizations, and
counterparty credit, at different levels of granularity
depending on exposure type. The loss estimates are
based on simulation models of obligor-level defaults.
The IDR loss models rely on position and exposure
data provided by the firms. IDR losses occur over
nine-quarters. For IDR on collateralized counterparty credit positions, the projections assume a margin period of risk after the initial market shock during which no collateral is received in response to margin calls, and default risk is elevated to reflect the
funding stress from collateral calls.
Losses on trading and counterparty positions as a
result of a global market shock were estimated only
for the six BHCs with large trading operations since
trading operations determine risk and performance
to a larger extent at these firms than at any other
BHCs participating in DFAST 2013. In addition, the
Federal Reserve’s projections of PPNR for all 18
BHCs incorporate the effect of the supervisory scenarios on the revenues generated by day-to-day trading activities, such as market-making for customers
and clients.

Losses Related to Operational-Risk Events
Losses related to operational-risk events are a component of PPNR and include losses stemming from
events such as fraud, employee lawsuits, or computer
system or other operating disruptions. Operationalrisk loss estimates are an average of losses estimated
using three approaches: a panel regression model, a
loss distribution approach (LDA), and a historical
simulation approach. In all three models, projections
of operational-risk-related losses for the 18 BHCs are
modeled for each of seven operational-risk categories
identified in the Federal Reserve’s advanced
approaches rule.40 All three models are based on historical operational-loss data submitted by the BHCs
on the FR Y-14Q.
In the panel regression model, projections of losses
related to operational-risk events are the product of
40

The seven operational-loss event type categories identified in the
Federal Reserve’s advanced approaches rule 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. See 12 CFR part 225,
appendix G, section 2.

March 2013

two primary components: loss frequency and loss
severity. The expected loss frequency is the estimated
number of operational-loss events in the severely
adverse scenario, while loss severity is the estimated
loss per event in each category. Loss frequency is
modeled as a function of macroeconomic variables
and BHC-specific characteristics. The model is estimated using FR Y-14Q data on operational-loss
events as reported by BHCs. Macroeconomic variables, such as the real GDP growth rate, stock market
return and volatility, credit spread, and the unemployment rate, are included directly in the panel
regression model and/or used to project certain firmspecific characteristics. Loss is projected as a product
of projected loss frequency from the panel regression
model and loss severity, which equals the historical
dollar loss per event in each operational-risk category. Total losses related to operational-risk events
equal losses summed across operational-risk categories. Because the relationship between the frequency
of operational-risk events and macroeconomic conditions varies across the categories, separate models
were estimated for each category.41
In the LDA model, expected losses related to
operational-risk conditional on the macroeconomic
scenarios are proxied by the losses at different percentiles of simulated, annualized loss distributions.
The loss frequency is assumed to follow a Poisson
distribution, in which the estimated intensity parameter of the Poisson distribution is specific to each
event type and BHC. A loss severity distribution is
also fit to each event type for each BHC.42 The distribution of aggregate annual losses is simulated, and
the macroeconomic scenario is implicitly incorporated in the results through the percentile choice,
which was based on analysis of historical loss data
for all BHCs taken together. The approach used to
choose the percentile for each scenario essentially targets the total loss forecast for all BHCs and allows
the LDA approach to split this loss among the individual BHCs and event types. Loss forecasts for an
individual BHC are the sum of the BHCs’ loss estimates for each event type.
41

Operational-risk losses due to damage to physical assets, and
business disruption and system failure are not expected to be
dependent on the macroeconomic environment, and therefore
were set equal to each BHC’s average annual operational-risk
loss in that category. External fraud was modeled using each
BHC’s average quarterly losses during the period from the
beginning of the financial crisis in the third quarter of 2007
through the end of the recession in the fourth quarter of 2009.
Multiple candidate specifications for the distribution were fit to
the data, and the final specification was chosen based on a number of criteria, including a measure of goodness-of-fit.

In the third approach—the historical simulation
approach—the distribution of aggregate annual
losses are simulated by repeatedly drawing the annual
event frequency from the same distribution used in
the LDA, but the severity of those events was drawn
from historical realized loss data rather than an estimated loss severity distribution. Losses from the
same percentile of the distribution as in the LDA are
used to approximate the severely adverse scenario.

Mortgage Repurchase Losses
Mortgage repurchase expenses are a component of
PPNR and are related to litigation, or to demands by
mortgage investors to repurchase loans deemed to
have breached representations and warranties, or to
loans insured by the U.S. government for which coverage could be denied if loan defects are identified.
Mortgage repurchase losses for loans sold with representations and warranties liability are estimated in
two parts. The first part is to estimate credit losses
for all loans sold by a BHC that have outstanding
representations and warranties liability, including
loans sold as whole loans, into private-label securities
(PLS) or to a GSE (Fannie Mae and Freddie Mac) or
loans insured by the government. This part takes into
account both losses recognized to date and future
losses projected over the remaining lifetime of the
loans. The second part is to estimate the share of this
credit loss that may be ultimately put back to the selling BHC (whether through contractual repurchase, a
settlement agreement, or litigation loss).
Future credit loss rates for mortgages (e.g., grouped
by vintage and investor type) are projected using
industry-wide data and models that incorporate the
house price assumptions in the severely adverse scenario.43 These industry-wide credit loss rates for the
GSEs are first adjusted to reflect the relative credit
performance of loans sold by each BHC and then are
applied to the outstanding balances of the corresponding groups of loans reported by each BHC.
These estimates are based on data provided by the
BHCs, which are collected on the FR Y-14A and
include vintage-level data on original and current
unpaid balances, current delinquency status, and
losses recognized to date, among other measures.
Losses recognized to date on mortgages sold into
43

The data used to model credit losses for government-insured
loans and loans sold to GSEs were loans randomly selected
from an industry database. The data used to model credit losses
for loans sold into private-label securities and as whole loans
were loans in proxy deals chosen based on the dealer, issuer, and
originator information contained in the database.

DFAST 2013: Methodology and Results

private-label securities (PLS) and as whole loans are
estimated by applying historical credit loss rates by
vintage to the unpaid principal balance of the run-off
portfolio.
The share of past and future credit losses likely to be
ultimately put back to the selling BHCs (the “putback rate”) is estimated separately for each investor
type and considers both investor behavior to date
and the procedural mechanics of pursuing repurchase claims. For whole loans and loans sold into
PLS, the estimated put-back rate is based on information from recent settlement activities in the banking industry and incorporates adjustments for supervisory assessments of BHC-specific put-back risk.
For government-insured loans, the estimated putback rate is also based on information from recent
settlement activities. Finally, for loans sold to Fannie
Mae and Freddie Mac, the estimated put-back rate is
based on historical information on the repurchases of
loans sold to Fannie Mae or Freddie Mac, with consideration given to the relative seasoning of each vintage and the time interval between default and
demand.
The initial estimate of mortgage repurchase losses
equals the estimated put-back rate applied to the corresponding credit losses for all loans sold by a BHC
that have outstanding representations and warranties
liability. This initial estimate is adjusted to account
for various other factors.
First, because this methodology does not distinguish
between originated loans and purchased loans, repurchase losses stemming from PLS are adjusted to
avoid double-counting of put-back exposure related
to whole loans sold to another CCAR BHC and are
subsequently included in a PLS deal. Second, prior to
incorporating estimated mortgage repurchase losses
into a BHC’s PPNR, estimated losses are reduced by
the BHC’s reported starting period amount of
reserves for put-back losses.44 Finally, the projection
assumes that a majority—but not all—of the mortgage repurchase losses projected using these techniques are realized over the planning horizon, with
the losses divided equally across quarters and incorporated into the PPNR projections. This assumption
attempts to balance the recognition that the resolution of repurchase issues could be a lengthy process
44

These netted expenses include repurchase reserves as of the
third quarter of 2012 and litigation reserves as of the third
quarter of 2012 that the BHC identified as being held specifically for put-back issues.

against the desire to ensure that the severely adverse
scenario projections incorporate a conservative
assessment of the losses to which the BHCs could be
exposed over the planning horizon.

Pre-Provision Net Revenue
PPNR is forecast using a series of autoregressive
models that relate the components of a BHC’s revenues and non-credit-related expenses, expressed as a
share of relevant asset or liability balances, to BHC
characteristics, and to macroeconomic variables.
These models are estimated using historical, mergeradjusted, panel data from the FR Y-9C. Separate
models are estimated for 17 different components of
PPNR, including five components of interest income,
three components of interest expense, five components of noninterest non-trading income, three components of non-interest expenses, and trading revenue. When choosing the level of detail at which to
model the components of PPNR, consideration is
given both to the BHCs’ business models and the
ability to accurately model small components of revenue. Movements in PPNR stemming from
operational-risk events, mortgage repurchases, or
OREO, are modeled in separate frameworks,
described earlier in this document. The PPNR model
estimates and projections are adjusted where appropriate to avoid double-counting movements associated with these items.
The model specification varies somewhat by PPNR
component. But in general, each component is
related to characteristics of the BHCs, including, in
some cases, total assets, asset composition, funding
sources, and liabilities. In some PPNR components,
these measures of BHC portfolio and business activity do not adequately capture the significant variation across BHCs, so BHC-specific controls are
included in the models for these components. Macroeconomic variables used to project PPNR include
yields on Treasury securities, corporate bond yields,
mortgage rates, real GDP, and stock market price
movements and volatility. The specific macroeconomic variables differ across equations based on statistical predictive power and economic interpretation.
Because forecasts of PPNR from trading activities
are intended to include the effect of the relevant macroeconomic variables and to exclude the effect of the
global market shock, net trading revenue is modeled

March 2013

using a median regression approach to effectively
lessen the influence of extreme movements in trading
revenue associated with the recent financial crisis.

Equity Capital and
Regulatory Capital
The final modeling step translates the projections of
revenues, expenses, losses, and provisions from the
models described above into estimates of equity and
regulatory capital for each BHC under the severely
adverse scenario. The projected components of pretax net income are summed, and a consistent tax rate
across all BHCs is applied to calculate after-tax net
income over the projection period. Projected aftertax net income, combined with the capital action
assumptions prescribed in the Dodd-Frank Act stress
test rules, are used to project quarter-by-quarter
changes in equity capital.45
The change in equity capital equals projected aftertax net income minus capital distributions (dividends
and any other actions that disperse equity), plus any
employee compensation-related issuance or other
corporate actions that increase equity, plus other
45

The Federal Reserve used the following capital action assumptions in projecting post-stress capital levels and ratios: (1) for the
fourth quarter of 2012, each company’s actual capital actions as
of the end of that quarter; (2) for each quarter from the first
quarter of 2013 through the end of 2014, each company’s projections of capital included: (i) common stock dividends equal
to the quarterly average dollar amount of common stock dividends that the company paid in the previous year (that is, from
first through the fourth quarter of 2012); (ii) payments on any
other instrument that is eligible for inclusion in the numerator
of a regulatory capital ratio equal to the stated dividend, interest, or principal due on such instrument during the quarter; and
(iii) an assumption of no redemption, repurchase, or issuance of
any capital instrument that is eligible for inclusion in the
numerator of a regulatory capital ratio, except for common
stock issuances associated with expensed employee compensation. These assumptions are consistent with the capital action
assumptions companies are required to use in their Dodd-Frank
Act company-run stress tests. See 12 CFR 252.146(b)(2).

comprehensive income and other equity adjustments
that are consistent with the Dodd-Frank Act stress
test rules.
Projected changes in equity capital in turn determine
changes in regulatory capital measures. These regulatory capital measures are consistent with current U.S.
regulatory capital rules that limit or eliminate the recognition of certain intangible assets and unrealized
gains and losses in tier 1 capital. For example, consistent with regulatory capital rules, only a limited
amount of deferred tax assets is allowable in projected regulatory capital. Regulatory capital measures
do not include unrealized gains and losses, but incorporate the cumulative effect of some other comprehensive income items, as projected by the BHCs, and
apply the limits specified in the current U.S. regulatory capital rules.46
Regulatory capital projections were not adjusted to
account for any differences between projected and
actual performance of the BHCs during the time the
supervisory stress test results were being produced in
the fourth quarter of 2012 and the first quarter of
2013.
Capital ratios are calculated using average total assets
and risk-weighted assets based on projections made
by the BHCs under the severely adverse scenario.
BHCs were required to project market risk-weighted
assets over the planning horizon based on the
market-risk capital rules that came into effect on
January 1, 2013, for purposes of identifying positions
subject to the market-risk rule and projecting the
RWA amount of these positions.47 The BHCprovided projections were adjusted to account for
differences between BHC and Federal Reserve projections of certain balance sheet items, such as the
ALLL, servicing assets, and deferred tax assets.
46
47

See generally 12 CFR part 225, appendix A.
See 12 CFR part 225, appendix E

Appendix C: BHC-Specific Results

Tables begin on next page.

DFAST 2013: Methodology and Results

Table C.1. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Ally Financial Inc.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

7.3
13.6
14.6
11.3

1.5
11.0
12.6
9.4

Note: The post-stress capital ratios presented in the table are based on an assumption that Ally remains subject to contingent liabilities associated with Residential Capital, LLC
(“ResCap”). On May 14, 2012, ResCap and certain of its subsidiaries filed for relief under Chapter 11 of the Bankruptcy Code in the United States Bankruptcy Court for the
Southern District of New York. As of March 6, 2013, the outcome of the ResCap bankruptcy remained pending.

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

-3.7
0.3

-2.8

5.1
0.7
0.0
0.0
-9.3

-7.1

Average assets are nine-quarter average assets.
Pre-provision net revenue includes losses from operational-risk events,
mortgage put-back expenses, and OREO costs.
Other revenue includes one-time income and (expense) items not included in
pre-provision net revenue.
Trading and counterparty losses includes mark-to-market losses, changes in
credit valuation adjustments, and incremental default losses.
Other losses/gains includes projected change in fair value of loans held for sale
and loans held for investment measured under the fair-value option, and
goodwill impairment losses.

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

4.5
0.3
0.2
1.4
0.1
0.0
2.4
0.0

5.2
6.0
9.3
5.2
6.5
0.0
4.9
1.8

March 2013

Table C.2. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
American Express Company
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

15.4
0.0

11.0

14.2
0.0
0.0
0.4
0.8

0.6

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

12.7
12.7
14.7
10.7

11.3
11.3
13.4
9.5

11.1
11.1
13.2
8.9

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

10.7
0.0
0.0
2.6
0.0
8.0
0.0
0.0

11.2
0.0
0.0
9.4
0.0
12.0
0.0
4.5

DFAST 2013: Methodology and Results

Table C.3. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Bank of America Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

24.1
1.0

1.3

49.7
0.5
14.1
12.5
-51.8

-2.7

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

11.4
13.6
17.2
7.8

6.9
8.5
11.6
5.4

6.8
8.5
11.6
5.4

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

57.5
15.3
9.4
8.5
4.7
15.3
3.0
1.3

6.9
5.9
10.0
5.1
8.6
16.2
4.3
1.3

March 2013

Table C.4. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
The Bank of New York Mellon Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

6.8
0.0

2.1

1.1
0.2
0.0
0.0
5.5

1.6

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

13.3
15.3
16.9
5.6

15.9
17.1
17.9
5.9

13.2
14.8
16.0
5.1

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

1.2
0.4
0.0
0.1
0.1
0.0
0.0
0.5

2.7
6.7
12.8
3.5
7.7
0.0
0.5
1.7

DFAST 2013: Methodology and Results

Table C.5. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
BB&T Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.5
10.9
14.0
7.9

9.4
11.2
13.4
8.3

9.4
11.2
13.4
7.9

Note: The actual and post-stress capital ratios presented in the table are based on information that BB&T provided to the Federal Reserve in regulatory reports on or before
February 6, 2013. The information that BB&T provided to the Federal Reserve includes information regarding BB&T’s risk-weighted assets. On March 4, 2013, BB&T disclosed
publicly that it had reevaluated its process related to calculating risk-weighted assets and determined that certain adjustments, primarily related to the presentation of certain
unfunded lending commitments, were required in order to conform to regulatory guidance. These adjustments resulted in an increase to risk-weighted assets and a decrease in
BB&T’s risk-based capital ratios and are not reflected in this table.

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

7.1
0.0

4.1

6.4
0.1
0.0
0.1
0.6

0.3

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

5.9
0.9
0.4
1.1
2.1
0.3
0.9
0.3

5.5
2.8
6.1
7.2
7.1
16.6
7.0
3.0

March 2013

Table C.6. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Capital One Financial Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

18.7
0.0

6.7

26.4
0.3
0.0
0.0
-8.0

-2.9

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

10.7
12.7
15.0
9.9

7.4
7.8
10.1
5.7

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

23.6
1.4
0.5
1.5
0.9
16.4
2.7
0.1

13.2
3.8
21.1
8.9
4.8
22.2
11.8
1.8

DFAST 2013: Methodology and Results

Table C.7. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Citigroup Inc.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

44.0
0.0

2.5

49.4
4.4
15.9
2.7
-28.6

-1.6

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

12.7
13.9
17.1
7.4

8.9
9.8
12.9
5.6

8.3
9.3
12.5
5.3

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

54.6
8.8
4.5
7.8
0.8
23.3
6.5
2.9

9.2
9.4
13.4
6.0
11.3
17.9
16.5
1.8

March 2013

Table C.8. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Fifth Third Bancorp
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

4.9
0.0

4.2

5.1
0.1
0.0
0.0
-0.3

-0.2

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.7
10.8
14.8
10.1

8.6
9.3
12.4
8.8

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

5.3
0.7
0.9
1.9
0.8
0.4
0.5
0.2

6.3
5.4
10.4
6.3
7.7
21.6
3.6
2.4

DFAST 2013: Methodology and Results

Table C.9. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
The Goldman Sachs Group, Inc.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

14.4
0.0

1.7

2.6
0.2
24.9
7.1
-20.5

-2.4

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

13.1
15.0
18.1
7.2

8.2
9.8
12.8
5.6

5.8
7.5
10.4
3.9

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

2.0
0.0
0.0
1.4
0.1
0.0
0.0
0.6

5.2
7.7
9.8
49.8
8.2
0.0
2.8
1.6

March 2013

Table C.10. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
JPMorgan Chase & Co.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

45.0
0.0

2.0

51.3
0.9
23.5
1.6
-32.3

-1.4

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

10.4
11.9
14.7
7.1

6.8
7.9
10.3
4.7

6.3
7.4
9.9
4.7

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

53.9
11.3
6.7
11.1
5.2
14.8
2.3
2.6

7.7
8.8
8.8
8.5
7.3
14.4
3.9
1.9

DFAST 2013: Methodology and Results

Table C.11. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
KeyCorp
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

2.5
0.0

3.0

4.3
0.0
0.0
0.6
-2.4

-2.8

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

11.3
12.1
15.2
11.4

8.0
8.6
11.2
8.1

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

3.9
0.4
1.1
1.0
0.6
0.1
0.4
0.3

7.3
10.3
12.6
5.8
7.2
19.1
8.8
2.8

March 2013

Table C.12. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Morgan Stanley
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario
Billions of
dollars
Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

1.2
0.0

Q3 2012

Q4 2014

Minimum

13.9
16.9
17.0
7.2

6.4
8.2
9.4
5.1

5.7
7.5
8.7
4.5

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Percent of
average assets1
0.2

2.3
0.0
11.7
6.7
-19.4

Stressed capital ratios

-2.9

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

1.6
0.1
0.0
1.2
0.0
0.0
0.1
0.1

3.1
0.6
9.5
7.8
10.2
0.0
1.4
0.8

DFAST 2013: Methodology and Results

Table C.13. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
The PNC Financial Services Group, Inc.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

9.8
-0.1

3.2

9.8
0.8
0.0
0.4
-1.4

-0.5

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.5
11.7
14.5
10.4

8.7
10.8
13.4
8.7

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

10.0
1.4
1.6
3.4
2.0
0.6
0.7
0.3

5.8
6.1
6.3
6.4
7.3
15.5
3.5
1.6

March 2013

Table C.14. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Regions Financial Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

3.1
0.0

2.6

5.2
0.1
0.0
0.0
-2.2

-1.9

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

10.5
11.5
15.0
9.1

7.5
8.5
11.7
6.8

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

5.4
1.1
0.8
1.2
1.7
0.2
0.3
0.2

7.6
8.2
8.5
6.7
9.7
18.0
6.8
2.2

DFAST 2013: Methodology and Results

Table C.15. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
State Street Corporation
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

3.0
0.0

1.5

0.4
0.4
0.0
0.7
1.5

0.8

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

17.8
19.8
21.3
7.6

13.0
14.5
16.6
7.1

12.8
14.4
16.2
6.6

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

0.3
0.0
0.0
0.0
0.1
0.0
0.0
0.2

2.0
0.0
0.0
0.0
18.3
0.0
0.0
1.5

March 2013

Table C.16. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
SunTrust Banks, Inc.
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

4.6
0.0

2.8

7.9
0.0
0.0
0.7
-4.1

-2.5

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.8
10.6
13.0
8.5

7.3
8.2
10.4
6.5

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

7.4
1.7
1.7
2.1
1.1
0.1
0.5
0.2

6.4
6.5
11.4
6.2
9.7
15.0
2.6
2.2

DFAST 2013: Methodology and Results

Table C.17. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
U.S. Bancorp
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

21.2
0.1

6.2

17.2
0.2
0.0
0.3
3.6

1.1

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.0
10.9
13.3
9.2

8.3
10.3
12.3
8.7

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

15.1
1.3
1.0
4.3
3.0
3.2
1.6
0.7

7.1
2.8
6.1
9.5
8.0
17.3
5.4
3.8

March 2013

Table C.18. Dodd-Frank Act stress testing 2013
Projected stressed capital ratios, losses, revenues, net income before taxes,
and loan losses, by type of loan
Federal Reserve estimates in the severely adverse scenario
Wells Fargo & Company
The capital ratios are calculated using capital action assumptions provided within the Dodd-Frank Act stress testing rule. These projections represent hypothetical estimates that involve an economic outcome that is more adverse than expected. These estimates are
not forecasts of expected losses, revenues, net income before taxes, or capital ratios. The minimum capital ratio presented is for the
period Q4 2012 to Q4 2014.

Projected capital ratios through Q4 2014 under the severely adverse scenario
Actual

Tier 1 common ratio (%)
Tier 1 capital ratio (%)
Total risk-based capital ratio (%)
Tier 1 leverage ratio (%)

Projected losses, revenue, and net income before taxes
through Q4 2014 under the severely adverse scenario

Pre-provision net revenue2
Other revenue3
less
Provisions
Realized losses/gains on securities (AFS/HTM)
Trading and counterparty losses4
Other losses/gains5
equals
Net income before taxes
1
2

Billions of
dollars

Percent of
average assets1

45.9
0.0

3.3

58.8
3.9
6.9
2.0
-25.7

-1.9

Stressed capital ratios

Q3 2012

Q4 2014

Minimum

9.9
11.5
14.5
9.4

7.0
8.7
11.4
7.0

7.0
8.7
11.2
7.0

Projected loan losses, by type of loan, for Q4 2012–Q4 2014
under the severely adverse scenario

Loan losses1
First-lien mortgages, domestic
Junior liens and HELOCs, domestic
Commercial and industrial
Commercial real estate, domestic
Credit cards
Other consumer
Other loans
1

Billions of
dollars

Portfolio loss
rates (%)

53.8
15.3
8.4
9.9
9.6
4.4
5.0
1.2

7.1
7.1
9.3
6.6
8.6
17.7
5.9
1.6

Full text of District Notices (Federal Reserve Bank of Dallas) : Federal Reserve Releases Summary Results of Bank Stress Tests, Notice 13-07 : 2013 Stress Test Methodology and Results

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