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Capital Management and Stress Test
Capital management framework
3
CCAR Capital management framework
Capital buffers – Stress Test Requirements
Material Risk
Material Impact in Capital
Measures
CCAR stress test Economic CapitalRegulatory Capital B1
Buffer Post Stress
1. Credit Risk- Commercial- Consumer- Investment Issuer- Counterparty
HIGH
2. Market Risk - IRR - Trading - Other mkt. risks
MODERATE
3. Operational and Compliance Risk HIGH
4. Business Risk MODERATE PPNR partially
captured
5. Model Risk LOW Model Buffers
6. Liquidity Risk MODERATE Captured in
idiosyncratic scenario
Liquidity risk does not require economic capital
buffer
The capital planning process needs to identify all the material risks at the Company and show how they are captured in the measures used to assess capital adequacy.
4
CCAR process & stress test overview
The CCAR process is intended to ensure banks hold sufficient capital to continue operating under multiple stressed scenarios inclusive of any proposed capital action. CCAR warrants comprehensive capital-based stress testing .
5
Scenarios
Stress Testing / Modeling and Data Templates
(FRY 14-A, Q and Ms)
Capital Plan Document
Baseline Scenario
Internal Stress
Scenario(s)
Supervisory Stress
Scenario
Loss Estimation• Credit Risk (by portfolio) • Trading Risk
9-Quarters Pro Forma Income
Statement• Loss Estimates.• Revenue impact.• Cost Impact
9-Quarters Pro Forma Balance
Sheet• Retained
Earnings• OCI• DTA Goodwill
Base and Stress Capital
Ratios
Capital Adequacy Assessment
• AFS/HTM• Operational Risk
Integrated Stress Testing• Comprehensive systemic and
idiosyncratic scenarios• Enterprise-wide consolidated
stress testing • Dynamic over the course of the
next nine quarters• Linked to capital adequacy by
expecting Tier 1 common post-stress limits (e.g., 5% Tier 1 common)
• Incorporates financial forecast of revenue and expenses
• CCAR data templates and result disclosures
Single Shock, Risk-Specific Stress Requirements• Trading Market Risk• Credit and Counterparty• Liquidity/ Funding • Operational
Business strategyThe Strategic Plan is a key input to the capital management process. The bank needs to hold sufficient capital and liquidity to support the plan under multiple economic and bank scenarios.
To annual planning and budgeting process
Defines strategic objectives and plans
Recommends Risk Appetite
Develops and disseminates corporate strategic plan
Develops LOB and sub-LOB strategic plans and scenarios
Strategic Plan Process
Approves Risk Appetite
Reviews and Approves
Reviews
Reviews
LOB Leadership, Finance & Risk
Corporate Strategy
Executive Risk Committee
CEO/CFO
Board of Directors
Strategic Plan
State of the world
Baseline or better
Poor economic conditions
Severe economic conditions
Min capital (and
liquidity)
Target capital (and
liquidity)
Capital Planning Process
To capital management process
5
Building Blocks for Stress Testing System
6
Tier 1 Ratios
Master Scenarios
Macro Economic ProjectionsGDP growthUnemploymentUSD/ EURInterest Rates....
Portfolio Specifics
Portfolio GrowthAsset QualityMigration...
Translation Models
P&LDeposit MarginsLending MarginsInvestment FeesCredit LossesOperational Expenses
Required CapitalOperationalMarketCredit
Available Capital
Strategic Plans
Risk Weighted Assets
PD = f(PD0 ,GDP,...) EAD = f(EAD0 ,PGF,...)
RWA = f(PD,LGD,EAD)
EL = f(PD0 ,LGD, EAD)
Scenario generation
Scenario Generation Activities Scenario Generation Output
1. Detailed Systemic Scenario Description
- Define systemic scenario and macroeconomic factors- Calibrate macroeconomic factors- Adjust scenario factors for regional considerations
2. Idiosyncratic Risk Considerations
- Leverage risks identified in Risk Assessment- Determine high-level impact for each idiosyncratic event- Define likelihood for each idiosyncratic event
3. Scenario Assessment, Review and Finalization
- Review systemic scenario(s) and company-specific events- Assign/discuss likelihood for each scenario option- Select scenario(s) and review impact
Scenario “N” (if applicable)
BHC Baseline (Budget)
BHC Stress
Scenario Description
Macro Factors
Key areas of Impact
Multiple scenarios should be developed which are relevant to the Company’s risk profile and incorporate simultaneous firm-specific and market-wide macroeconomic events.
7
Scenario development — Provisions for Loan and Lease Losses Loan losses are projected using product-specific models utilizing historical and expected relationships between credit performance and relevant macroeconomic variables.
9
Mortgage Loan Products
Domestic Mortgages
Commercial & Industrial and Commercial Real Estate
Credit Cards Other Consumer
Other Loans
Loan Types Includes first and junior liens; closed-end and revolving
Includes Commercial & Industrial loans to obligors globally and domestic Commercial Real Estate loans
Includes bank and charge cards both domestically and internationally
Includes personal loans, student loans, auto loans, and other consumer loans
Includes international real estate loans and a variety of non-retail loans
Key Modeling Inputs
Home Price Index (HPI)
Interest rates Unemployment
rate
Obligor and facility risk characteristics
Country (local GDP) Sensitivity to global
trade flows
Vintage Credit score Country Unemployment
rate
Vintage Credit score Country Unemployment
rate
Local GDP HPI Interest rates Unemployment
rate
Business Activities
Domestic residential mortgage portfolios (RESI), the Private Bank, and Bank Holdings in RESI
Corporate and commercial loan, commercial real estate, commercial industrial loans, exposures in Securities & Banking (S&B), Transaction Services, and Bank Holdings
Consumer and corporate credit card lending globally
Domestic credit cards in Bank’s Branded and Retail Services segments
Domestic and global operations
International residential real estate
International commercial real estate and other loans in S&B, Transaction Services, Bank Holdings
FR Y-14 A schedules will require to develop capabilities around loss forecasting—Retail portfolios
Historical Charge-offs DelinquencyEconometric Component
Based Models PD/LGD-Based Models
Model Characteristics
• Simple average of historical net charge-offs or Markov-based loss rates
• Might include lag to address dampening from growth or trend functions to capture recent experience
• Delinquency-based vintage• Ratio-based roll-rate• Unit based to control for size
and/or separate severity
• Entry rate reflecting FICO refresh, behavior score and/or other characteristics such as MTM LTV
• Regression or transition probabilities subsequent to entry
• Separate LGD reflecting current market conditions
• Basel PD/LGD/EAD expected loss approach
• Segmentation based on LOB/product type, rating, FICO Score and/or collateral
Considerations
• Significant lag• No explicit link to root cause
other than in segmentation
• Somewhat lagging since still based on delinquency
• No explicit consideration of certain characteristics such as appreciation/ equity except in segmentation
• Seasoning adjustments and segmentation can increase complexity
• Segmentation inherent and at the loan level
• Calibration in periods of change
• Transparency/flexibility
• PD/LGD typical for commercial but not always well linked to business levers and loss forecasting for consumer
• GAAP consistency (economic vs. accounting)
• Transparency and model stability
LeadingLaggingModels currently utilized by banks vary in level of sophistication, but regulatory expectations are moving towards increasing levels of segmentation and transparency.
10
LeadingLagging
FR Y-14 A schedules will require to develop capabilities around loss forecasting—wholesale portfolios
Top Down Loss Model Simple Delinquency / Rating Based Portfolio Models
More Sophisticated Flow or Transition Models
Loan Level Default and Severity Models
Model Characteristics Model Characteristics Model Characteristics Model Characteristics
• Simple regression of charge-off rate (gross or net) to macroeconomic variables
• Might include lag functions• May be augmented by, or
benchmarked to, call report peer data
• Rating based PD banding• Macroeconomic regression of
PD cycle adjustments by rating band
• Separate severity assumption or model(s)
• May be augmented with vendor data
• Dynamic full risk rating transition matrix
• Various options for regressing / estimating rates as a function of macroeconomic inputs
• Separate severity assumption or model(s)
• Can be augmented with vendor data
• Predict default probability and/or loss severity as a function of loan level characteristic data and macroeconomic inputs
• Often leverages vendor models calibrated to pooled data sets
Considerations Considerations Considerations Considerations
• Longer time series available• Useful benchmark model• Limited segmentation• Implicit but not explicit
reflection of the portfolio condition at the forecast start date (e.g., delinquency pipeline)
• Lags many CCAR banks• Within range of broader
current practices of CCAR banks
• Relatively robust and transparent
• Only marginally more data intensive than top down loss model
• Separates frequency and severity
• Implicit, not explicit transition modeling (requires additional transformation to quarterly defaults)
• Limited vendor-based data specific to CRE
• Explicit modeling of defaults and timing of loss
• More consistent with leading industry approach for commercial
• Much more data intensive (loan level vs. summary level)
• More complex modeling concepts
• May sacrifice some transparency / flexibility
• Limited vendor-based data specific to CRE
• Incorporates loan specific drivers
• Increased segmentation inherent in models
• Much more data intensive – very few companies with sufficient internal data to develop / validate
• Much more complex modeling concepts
• Vendor models gaining more traction; initial and on-going licensing costs, however and some lack of transparency
LeadingLagging
Vendor Solutions available for Credit loss forecasting
LeadingLagging
The following is a representative, but not necessarily comprehensive list of vendor solutions and data sets that can be used to augment the credit modeling
12
Economic Data Portfolio & Loan Level Credit Data Pooled Default and Recovery Data
Representative Vendors / Data Model Characteristics Model Characteristics
• Moody’s Analytics, CreditCycle & Economy.Com (Moody’s specific scenarios and Fed scenarios)
• FHLB regional economic reports (historical)• FRB/FFIEC– Macro Economic Data and Consumer
Macro Performance Data• Credit Bureaus – Consumer Credit Data• NAR – Residential Mortgage Macro Performance Data• S&P Case-Shiller Home Price Indices• S&P Credit Models & Capital Stress Test services• CoreLogic • Argus Information Services & Predictive Analytics• Oracle OFSAA• Axiom
• SNL Call Report Data (e.g., balances, 30-89, 90+, charge-off, recovery data for major product segments)
• RMBS, CMBS Securitization data• Delinquency and flow rates, defaults,
write-offs and charge-offs, recoveries and net-losses, prepayments
• Scoring metrics• Loan to value, debt-to-income ratios,
credit limits and usage• Application volume, marketing
activity, collection treatments• ADCO & Intex
• Moody’s DRD (corporate default and recovery data)
• Moody’s CRD (private firm financial and EDF data)
• Moody’s LGD data (recovery database)
Considerations Considerations Considerations
• Moody’s develops full “economies” under both proprietary scenarios (S1-S5) and Fed scenarios
• Useful for utilizing regional inputs or deriving derivative indices from the limited set of variables forecast by the Fed
• Useful for augmenting internal data when developing top down loss models, or serving as a benchmark to more sophisticated models (i.e., sanity check)
• Useful for augmenting internal rating and recovery data in developing proprietary (internal) rating index or transition matrix based methods
Scenario development — Trading and Counterparty Losses Trading and counterparty losses represent losses on Bank’s trading portfolios, CVA, and other mark-to-market assets, inclusive of default losses.
.
8
Integrated Risk and Capital decision reporting
12
Key Risk Indicators Current Prior Trendvs. Tolerance /
TargetScore Benchmarking
Credit
Mortgages
HELOC
Auto Loans
Credit Cards
Other Consumer
C&I
CRE
Market
Opera-tional
Risk BASELINE STRESSED
S 1 S 2 S 3 S 4 S 5 Benchmarking Key Risk IndicatorsBaseline Stressed
Current Prior Trendvs.
Tolerance/TargetScore Benchmarking S1 S2 S3 S4 S5 Benchmarking
Capital reporting should include baseline and stressed views of KRIs.
PPNR forecasting modeling framework
Business Plan - PPNR Forecast
Business Plan - PPNR Forecast
Business Plan - PPNR Forecast Macroeconomic Scenarios
• Baseline• Fed Adverse• Fed Severely Adverse• BHC Scenarios (Systemic and
Idiosyncratic)
PPNR Model
Estimated Regression Coefficients
PPNR Drivers
Net Interest Income
Projected Balances
Projected Yields
Non-interest Income
Non-interest Expenses
+
-
Compensation
Op Risk Events
Put‐back Losses
OREO Expenses
Changes in MSR
Income
Other Expenses
x
Fee & Commissions
Securitization & Gain on
Sale…
Servicing Revenue
Segments
Baseline Scenario
Scenario 1
Scenario 2
Balances Originations
# of Accounts
# of Loans
Assets
• Residential Mortgages• HELOCs• C&I Loans• Small Business• CRE Loans• Credit Cards• Other Consumer (Auto,
Student, etc.)• Other Loans & Leases• Interest-bearing Securities• Trading Assets• Deposits with Other Banks
Liabilities
• Customer Deposits• Fed Funds, Repos, Other
Short-term Borrowing• Trading Liabilities• TruPS• Long-term Debt• Other
# of Deposits …
Modeling Components
• Alternative Variables
• Simple vs. Multiple
• Transformations
• Autoregression/Lags
• Data Disaggregation
• Data Augmentation
• Residual Analysis
• Sensitivity Analysis
13
Modeling aspect Fed ModelIndustry Practice
(less complex)Industry Practice(more complex)
Model Type Multiple autoregressive
models
Single regressions Lagged variables Moving averages used where
regressions had insufficient fit
Multiple regressions 2-3 drivers for each regression Dummy variables to adjust for
seasonality Moving averages used where
regressions had insufficient fit
Considerations for Granularity
BHC business model Ability to accurately model
small components of revenue
Data availability (included available balance and volume forecasts)
Market environment, competitive landscape, and resources available to lines of business
Granularity of Components
17 components of PPNR:o Interest income (5)o Interest expense (3)o Non-interest non-trading
income (5)o Non-interest expense (3)o Trading revenue (1)
~10 regressions with sufficient fit Non-interest income and expense
line items projected
+100 regressions with sufficient fit Components of balances modeled in
addition to line items
Macroeconomic Variables
Interest Rates GDP Equity Markets and
Volatility
Direct forecasts based on internally provided balances and volumes
GDP growth Interest rates Equity markets Commodities
Model Ownership N/A
Input from line of business on economic drivers
Line of business has no review of output after model creation
Line of business CFOs own economic drivers and model results
Line of business determines whether identified correlations are non-spurious
Documentation and Validation
N/A Documentation and validation consistent with SR 11-7 model risk management
framework
There are a range of industry practices related to PPNR modeling capabilities across US institutions. PPNR modeling is one of the most challenging modeling areas and has been the source of Matters Requiring Attention (“MRAs”) for many banks in the 2012 and 2013 CCAR cycles.
PPNR industry modeling practices
11
Loss forecasting — Operational risk modeling
2.1. Regression Analysis of Frequency and Severity using internal loss data
• Regression techniques
• Lagging
2.2. Add external data when necessary
2.3. Add scenario analysis to calculated idiosyncratic add-on
Economic Indicators Dataset
LOB / Risk Type
Retail Bankin
g
Commercial
Banking
Clearing
Retail Brokerag
e
Private Bankin
g
Business Disruption / IT
Clients / Business Practice
Damage to Physical Assets
HR and Workplace Safety
Execution and Process
External Fraud
Internal Fraud
# Economic Factors 4Q’11 1Q’12 2Q’12 3Q’12 4Q’12 1Q’12 2Q’13 3Q’13 4Q’13
1 Real GDP change (% YoY)
2 Unemployment rate
3 Inflation (%)
4 Personal savings rate
5 House price index
6 Consumer debt to income ratio
7 Personal bankruptcy filing
8 Business bankruptcy filing
9 Prime interest rate
10 3-Month Libor
11 10-Year Treasury Note
12 Vehicle Sales (millions)
13 S&P 500 Index (end of period)
14 National Consumer loan growth
15 National C&I loan growth
AMA Inputs
BU 1
BU 2
BU 3...
LT 1 LT 2 LT 3 …
Internal Loss
Database
External Loss
Database
Scenarios Loss
Database
AMA Calculation Engine
Frequency distribution
Severity distribution
Aggregate Loss Distribution
Scenario Design
Loss Forecasting
Capital Impact & Validation• Systemic
• Idiosyncratic• Supervisory
• EL • RWA
• EC• RC
• Risk type / LOB cell
• Lagging
Stress Testing Output
Scenario 1 2010 Amount in $MilBHC Baseline Q4 2010 Q1 2011 Q2 2011 Q3 2011 Q4 2011 Q1 2012 Q2 2012 Q3 2012 Q4 2012
Projected Operational Risk Losses
Scenario 2 2010 Amount in $MilBHC Stress Q4 2010 Q1 2011 Q2 2011 Q3 2011 Q4 2011 Q1 2012 Q2 2012 Q3 2012 Q4 2012
Projected Operational Risk Losses
Scenario 3 2010 Amount in $MilSupervisory Stress Q4 2010 Q1 2011 Q2 2011 Q3 2011 Q4 2011 Q1 2012 Q2 2012 Q3 2012 Q4 2012
Projected Operational Risk Losses
2011 Amount in $Mil 2012Amount in $Mil
2011 Amount in $Mil 2012Amount in $Mil
2011 Amount in $Mil 2012 Amount in $Mil
• Systemic• Idiosyncratic• Supervisory
LOB / Risk Type
Retail Banking
Commercial Banking
Clearing Retail Brokerage
Private Banking
Business Disruption / IT Clients/ Business PracticeDamage to Physical AssetsHR and Workplace SafetyExecution and ProcessExternal FraudInternal Fraud
• LOB• Risk Type
Stress Testing Process
16
Pro-forma capital ratios
B/S and P&L
Forecast
Loss / PPNR
Forecast
Scenario and
Financial Data
The completion of FR Y-14 reports represents a significant challenge for Mizuho given the breadth and depth of areas covered by the schedules
FR Y-14M*
• Credit card data collection schedule (domestic)
• First lien closed-end 1-4 family residential loan schedule
• Home equity loan and home equity line of credit schedule
• Address matching loan level data collection
FR Y-14Q
• Securities risk• Retail risk*• PPNR• Wholesale risk• Trading risk• Basel III/Dodd-Frank• Regulatory capital
instruments• Fair value option/Held
for sale• Mortgage servicing
rights• Operational risk • Supplemental schedules
FR Y-14A
• Summary schedules for each scenario
– Income statements, balance sheet, and equity /Capital statements; Retail, Wholesale, Loans, Securities; Trading; Counterparty Credit Risk; Operational risk; and PPNR
• Macro scenario schedule
• Basel III and Dodd Frank schedule
• Regulatory capital instruments
• Counterparty credit risk
15
*Not applicable to Mizuho’s US operations as these schedules are focused on retail exposure information
• Large number of data providers
• Numerous data sources
• Increased data granularity
• Aggregation of data across main platforms
• Complex accountability framework
• Change management challenge due to constantly changing requirements
• Diverse skill set required
• Y-14A
• Y-14 Semi-Annual
• Y-14Q
Key Challenges
The completion of FR Y-14 and other material regulatory filings is supported by over 3,000 data attributes across 16 categories
16
Below is the approximate count of total data attributes, by different product type, used to build a data platform with the capabilities to address external regulatory reports and internal management reports/analytics
# Type of Product Approximate # of data attributes
10 Repo 175+
11 Equities 50+
12 Forex 20+
Mitigants
13 Guarantees 175+
14 Credit derivatives 75+
15 Collaterals 50+
Financial Data
16 GL data 25+
# Type of Product Approximate # of data attributes
1 Loan contracts 450+
2 Investments 350+
3 Overdraft accounts 325+
4 Options 300+
5 Swaps 300+
6 Futures 250+
7 Money market contracts 200+
8 Bills 200+
9 Letters of Credit 175+
Stress test aggregation solution functionality overview
The stress test platform requires a consolidated baseline forecast with aggregated incremental stress impacts, determined at each business unit/portfolio and at the aggregate enterprise level, to produce a set of pro forma stressed financials.
Baseline Income Statement
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:
8 Loan lossesInvestment portfolio (OTTI):
9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012
Baseline Balance Sheet
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks
3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:
11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus
19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Baseline
Summary Income Statement - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue - - - - - - - -
Net interest revenue:2 Interest revenue - - - - - - - - 3 Interest expense - - - - - - - - 4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses - - - - - - - -
7 Pre-provision net revenue - - - - - - - -
Losses:
8 Loan losses - - - - - - - - Investment portfolio (OTTI):
9 AFS - - - - - - - - 10 HTM - - - - - - - - 11 Total OTTI - - - - - - - - 12 Trading losses - - - - - - - - 13 Counterparty losses - - - - - - - - 14 Operational/fiduciary - - - - - - - - 15 Off-balance sheet - - - - - - - - 16 Total losses - - - - - - - -
17 Taxes - - - - - - - -
18 Extraordinary items, net of tax - - - - - - - -
19 Net income - - - - - - - -
2011 2012
Summary Balance Sheet - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks - - - - - - - - 2 Interest-bearing deposits with banks - - - - - - - -
3 Securities purchased under resale agreements - - - - - - - - 4 Trading account assets - - - - - - - - 5 AFS investment securities - - - - - - - - 6 HTM investment securities - - - - - - - - 7 Loans and leases - - - - - - - - 8 Goodwill and other intangible assets - - - - - - - - 9 Other assets - - - - - - - -
10 Total assets - - - - - - - -
Liabilities:
11 Deposits - - - - - - - - 12 Securities sold under repurchase agreements - - - - - - - - 13 Federal funds purchased - - - - - - - - 14 Short-term borrowings - - - - - - - - 15 Accrued expenses and other liabilities - - - - - - - - 16 Long-term debt - - - - - - - - 17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus - - - - - - - -
19 Common stock + surplus - - - - - - - - 20 Retained earnings - - - - - - - - 21 Accumulated other comprehensive income - - - - - - - - 22 Treasury stock - - - - - - - - 23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies - - - - - - - -
2011 2012
Stressed Pro Forma
BU 1 Stress Losses - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:8 Loan losses
Investment portfolio (OTTI):9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012Source Reports
BU 1 Stress Losses - Scenario 1Source Reports
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Corporate
BU 1 Stress Losses - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:8 Loan losses
Investment portfolio (OTTI):9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012Source Reports
BU 1 Stress Losses - Scenario 1Source Reports
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Business Unit 4
BU 1 Stress Losses - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:8 Loan losses
Investment portfolio (OTTI):9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012Source Reports
BU 1 Stress Losses - Scenario 1Source Reports
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Business Unit 3
BU 1 Stress Losses - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:8 Loan losses
Investment portfolio (OTTI):9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012Source Reports
BU 1 Stress Losses - Scenario 1Source Reports
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Business Unit 2
BU 1 Stress Losses - Scenario 1
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Revenue:1 Fee revenue
Net interest revenue:2 Interest revenue3 Interest expense4 Net interest revenue - - - - - - - - 5 Total revenue - - - - - - - -
6 Operating expenses
7 Pre-provision net revenue - - - - - - - -
Losses:8 Loan losses
Investment portfolio (OTTI):9 AFS10 HTM11 Total OTTI - - - - - - - - 12 Trading losses13 Counterparty losses14 Operational/fiduciary15 Off-balance sheet16 Total losses - - - - - - - -
17 Taxes
18 Extraordinary items, net of tax
19 Net income - - - - - - - -
2011 2012Source Reports
BU 1 Stress Losses - Scenario 1Source Reports
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
($MM)
Assets:1 Cash and due from banks2 Interest-bearing deposits with banks3 Securities purchased under resale agreements4 Trading account assets5 AFS investment securities6 HTM investment securities7 Loans and leases8 Goodwill and other intangible assets9 Other assets
10 Total assets - - - - - - - -
Liabilities:11 Deposits12 Securities sold under repurchase agreements13 Federal funds purchased14 Short-term borrowings15 Accrued expenses and other liabilities16 Long-term debt17 Total liabilities - - - - - - - -
Shareholders' Equity:18 Preferred stock + surplus19 Common stock + surplus20 Retained earnings21 Accumulated other comprehensive income22 Treasury stock23 Total shareholders' equity - - - - - - - -
24 Total liabilities and shareholders' equity - - - - - - - -
Off-balance sheet:25 Commitments and contingencies
2011 2012
Business Unit 1
Consolidated Baseline Income Statement and
Balance Sheet Forecast
Incremental Stress Impact Estimates Pro Forma Stressed
Income Statement and Balance Sheet
2016
Current Actions Taken at CCAR Institutions
CCAR institutions continue to enhance capital management process and related validation processes
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At RiskInefficient Unstable Stress
Testing Process
FunctionalIssue Awareness with Manual Processes and
Control
SustainableReliable,
Controlled Function
AspirationalHigh Performing Enterprise-
wide Business enabler
Strategy
• Siloed Stress Testing Approach• Ad-hoc planning for
consolidated stress testing exercises
• Coordinated business and corporate stress testing approach
• Integrated business and corporate approach
• Comprehensive coverage and alignment of stress testing efforts
• IT enabled strategy focused on creating value for business and corporate function
• Integrated framework fully aligned to Basel, ICAAP, contingency, recovery and resolution planning
Governance
• Structures remain inconsistent and are based on “who can do it” rather than “who should do it”
• Skills and capabilities requirements loosely defined
• Consistent structures exist with clear functional boundaries between risk, finance and LOB
• Some functions are centralized
• Skills and capability requirements are well defined and pursued
• Stress testing committee and working group
• Centralized and organized stress testing unit to increase accountability and drive expertise
• Stress testing fully aligned to strategic planning and performance evaluation
• Highly skilled resources focused on analysis vs. result production
• Leverage shared services to deliver routine, high volume transaction processing when necessary
Process
• Scenario Analysis, loss forecasting, aggregation and reporting processes are informally documented, not standard and disconnected
• Issues are partially known and managed reactively
• Standard policies and procedures are well documented and maintained
• Ad-hoc efforts to standardize and automate procedures
• Activities are performed manually and consume excessive resources
• Outsource of systemic scenario generation
• Processes are highly standardized and consistent across LOBs
• Linkage between LOB and corporate stress testing processes
• Key activities and controls are performed on a timely basis based on controlled cycle time and effective preventive controls that reduce errors
• End-to-end process approach to standardization & simplification
• Integrated loss and RWA forecasting
• Continuous process improvement and ongoing formalized documentation
Technology
• Multiple databases with no common structure or reliable interfaces
• Heavy reliance on ad-hoc reporting to provide information
• Significant data manipulation to support stress testing needs
• Streamlined inventory of risk and finance applications participate in stress testing process
• Data validation controls in place to ensure completeness and reconciled information to GL/disclosures
• Automation of balance sheet aggregation and reporting steps in stress testing process
• Model and data quality governance and controls in place
• Financial and risk applications (scenarios, loss forecasting, balance sheet aggregation and fully integrated into a common stress testing platform
• Ability to expand functionality and link other areas (RWA, ICAAP, liquidity risk, ALM, etc.)
• Flexible functionality (e.g., what if and sensitivity analysis)
Stabilization Sustainability
The identification, discovery and preparation of data to complete the FR Y-14 reports should leverage both top-down and bottom-up approaches
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There are two methodologies to identify, discover and get data ready for the FR Y-14 reporting, top down approach and bottom up approach as shown in the diagram below.
Data gaps
Data sourcing solutions
Strategic enhancements
Tactical workarounds end-user computing
Understand the internal/ external
reporting requirements
Component evaluation & issue resolutions
FRY-14Data Elements
•Balance sheet,•Income statement • Risk reports,•Financial data
FRY-14Data Model
Data schema (grouping)
Group FRY-14 DataRequirements
Identify source system for the data elements
Data dictionary
Top Down
Bottom Up
Defining Reporting Requirements – Reporting & Data
Anticipating Reporting Requirements – Work Streams
Mapping Sourcing
Analysis