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

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.

Figure 7. Projecting net income and regulatory capital

The framework begins with a projection of PPNR, which equals projected net interest income plus non-interest 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, 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.

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 default-related 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 non-objection 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 Dodd-Frank 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 risk-weighted assets that are based on projections made by the BHCs under the severely adverse scenario.

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 rateby 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.

Figure A. Ending aggregate tier 1 common levels using different tax rates

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Source: Federal Reserve projections in the severely adverse scenario.
"Pps" is percentage points.

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

Accessible Version | Return to text

Source: Federal Reserve projections in the severely adverse scenario.

"Bps" is basis points; "pps" is percentage points.

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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 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 risk-sensitive 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 BHC-estimated 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 non-credit-related expenses reported on the FR Y-9C report, which contains consolidated income statement and balance sheet information for each BHC, including components of interest income, non-interest 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 risk-measurement 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 industry-average 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 variables, 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.

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15. See generally 12 CFR part 225, appendix A. Return to text

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

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), to text

18. 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. Return to text

19. The FR Y-14 schedules are available at to text

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. Return to text

21. The FR Y-9C report is available at to text

Last update: March 28, 2013

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