Specific Issues of Economic Capital Management: Economic vs. Regulatory Capital and Business Risk
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1 Specific Issues of Economic Capital Management: Economic vs. Regulatory Capital and Business Risk Corinne Neale Managing Director, Capital Management
2 Regulatory Capital The Pillar 1 Model Managing IRB Capital Economic Capital Capturing Real World Risks Stress Testing Management Actions Communication of Risks Active Portfolio Management Pricing and Performance Analysis 2007 Algorithmics Incorporated. All rights reserved. 2
3 Pillar 1: A Regulatory Model for ERM The Stylized IRB Model Financial Institution Default/No-Default ASRF (LLN) Hardwired Correlation Banking Book Trading Book Single Credit Driver Retail Commercial Medium/Small Commercial Large Derivatives Counterparties Mortgages Credit Cards Lines of Credit Private Firms Sectors Corporates (Public and Private) Sovereign Bond Issuers Corporate Bond Issuers Sectors Sectors Sectors Credit Derivatives LLN LLN LLN LLN 2007 Algorithmics Incorporated. All rights reserved. 3
4 The IRB Model: Limitations Many Risks not captured Concentration risk Single name Sector (industry, geography) Losses driven only by defaults, not by ratings migration One-size-fits-all within each Basel II-defined asset class (e.g., all residential mortgages subject to the same formula / correlation values; new financial products?) Only considers one confidence level (i.e., the 99.9%) Thus, does not address stress scenarios nor tail risk (i.e., what are potential losses beyond 99.9%) Rigidity of modeling assumptions creates disconnect with true economic capital 2007 Algorithmics Incorporated. All rights reserved. 4
5 Pillar II: Expectations for Risk Management In a nutshell, the objectives of Pillar II are to: Compensate for limitations of the IRB Model Promote enterprise-wide measurement and management of risk Evaluate impact of stress scenarios 2007 Algorithmics Incorporated. All rights reserved. 5
6 Regulatory Capital The Pillar 1 Model Managing IRB Capital Economic Capital Capturing Real World Risks Stress Testing Management Actions Communication of Risks Active Portfolio Management Pricing and Performance Analysis 2007 Algorithmics Incorporated. All rights reserved. 6
7 ERM: A Model to Evaluate Real World Risks 2007 Algorithmics Incorporated. All rights reserved. 7
8 Quantifying the Impact of Real World Risks 2007 Algorithmics Incorporated. All rights reserved. 8
9 Bank ICAAP Results Economic Capital Macroeconomic Drivers Correlation Impact Concetration Risk Migration Risk Regulatory Capital Capital Available Source: for this chart 2007 Algorithmics Incorporated. All rights reserved. 9
10 Banks ICAAP Content Current and Project Capital Positions Risk Appetite: Confidence Interval Horizon Scenario the confidence level corresponds to Risks covered by Capital Quantification technique for each risk Control process for risks not covered by capital Risk aggregation techniques used Description Assumptions Limitations Details of stress and scenarios applied Controls and ICAAP validation process ICAAP and Pillar 1 comparisons Internal use of ICAAP 2007 Algorithmics Incorporated. All rights reserved. 10
11 Quantification Issues: Concentration How concentrated is my portfolio? Possible answers: HH Indexes Ratio of largest to smallest exposures Ratio of Additive UL to Absolute UL this is the only one to capture correlation! Where are the higher-aggregate concentrations? This requires multi-level results? How do correlations interact with concentrations? Only a full EC model can help to articulate this 2007 Algorithmics Incorporated. All rights reserved. 11
12 Modeling Single Name Concentration: An Example Chart 2. A nongranular portfolio containing an infinitely fine-grained subportfolio Note: Entire portfolio (subportfolio A plus B) is nongranular Nongranular subportfolio A (# of obligors η) Infinitely fine-grained subportfolio B (# of obligors η) Where you draw the line depends on your accuracy vs performance trade-off Sampling or FFT LLN Source: Bank of Japan Working Paper Series An Efficient Monte Carlo Method for a Large and Nongranular Credit Portfolio Hideaki Higo See: Algorithmics Incorporated. All rights reserved. 12
13 Modeling Single Name Concentration: An Example Financial Institution Banking Book Trading Book Retail Commercial Medium/Small Commercial Large CP analysis DND for derivatives Mortgages Credit Cards Sector analysis DND Notional Lines of Credit CP/Sector analysis DND or Full Migration MtM Exposures CLT CP analysis Full Migration Integrated Market & Credit (Stochastic Exposures) or MtM Full Migration for Bonds Integrated Market & Credit (Stochastic Exposures) Netting & Collateral Impact of Credit Derivatives LLN FFT Sampling Sampling 2007 Algorithmics Incorporated. All rights reserved. 13
14 A Model Basel Granularity Adjustment Run 1 = Systemic + Specific Run 2 = Systemic Financial Institution Banking Book Trading Book Retail Commercial Medium/Small Commercial Large Mortgages Credit Cards Lines of Credit Run 1 LLN CLT FFT Sampling Run 2 LLN LLN LLN LLN 2007 Algorithmics Incorporated. All rights reserved. 14
15 Quantification Issues: Sector Concentration The other form is Sector concentration relates to imperfect diversification across systematic components of risk, namely sectoral factors * E.g., exposure to the U.S. automobile industry, which might be highly correlated to other sectors (e.g., energy, aluminum manufacturing, consumer finance, etc.) Multi-factor modeling enables the full capture of correlations across industry/geographic sectors Identify exposures to highly correlated industries or geographies that increase portfolio risk Likewise, capture diversification benefits that mitigate portfolio risk *Basel Committee on Banking Supervision, Studies on credit risk concentration, Working Paper No. 15, Nov Algorithmics Incorporated. All rights reserved. 15
16 Multi-Factor Modeling Illustration: The Multi-Factor Variable Candidates General State of the Economy Composite Leading Indicator OECD_CLI Industrial Production Index Manufacturing Utilization rate Prices Producer Price Index Producer Sales Index Producer Inventory Index Imports Foreign Trade Exports Import Price Index Export Price Index Foreign Exchange FX Rate Euro/USD FX Rate Euro/YEN Money Markets 3-Year Corporate Bond Yields Call Rate Commercial Paper Rate 2007 Algorithmics Incorporated. All rights reserved. 16
17 Sector / Geography / Business Concentrations Million 300 1, , Sector 1 Sector 2Sector 3 Sector 4 Sector 5 Sector 6Sector 7 Sector 8 Sector 9 Sector 10 Sector 11 Sector 12 0 FTSE classification EL UL Exposure 2007 Algorithmics Incorporated. All rights reserved. 17
18 Quantification Issues: Stress Tests Stress-tests are part of risk management: What-If? Change Assumptions Residual Risk Marginal Risk Business Risk Macro-Economic Risk Exceptional Events Tail Risk Downturn / Market Event Liquidity risk Correlations Sensitivities Understand Risk Profile Capital Adequacy Capital Allocations Management Actions 2007 Algorithmics Incorporated. All rights reserved. 18
19 Business Risk Assessment Through Stress Tests Definition: The risk that, as a result of an external event, some of the bank s business expenses be not covered by the income expected from that business, resulting in a net loss that needs to be funded with capital: Business Budget (Self Funded) Sensitivities Stress Tests Loss Impact Scenarios 2007 Algorithmics Incorporated. All rights reserved. 19
20 Other Risk Assessments Through Stress Tests Illustration: Stress Test 1 Stress Test 2 Stress Test 3 Shocks to asset correlations Shocks to credit quality transition probabilities Shocks to systematic risk 2007 Algorithmics Incorporated. All rights reserved. 20
21 Other Risk Assessments Through Stress Tests Results: EC Base Stress 1 Stress 2 Stress Algorithmics Incorporated. All rights reserved. 21
22 Regulatory Capital The Pillar 1 Model Managing IRB Capital Economic Capital Capturing Real World Risks Stress Testing Management Actions Communication of Rrisks Active Portfolio Management Pricing and Performance Analysis 2007 Algorithmics Incorporated. All rights reserved. 22
23 ERM: Tools for Management Analysis and Action Advanced modeling techniques enable the quantification of real world risks across the portfolio Quantification, in turn, enables financial executives to unlock value: Communication internally, with regulators, and to the market about risk profile; Active management of the portfolio; Pricing decisions and performance analysis; and Ultimately, creation of economic value and profitable business growth 2007 Algorithmics Incorporated. All rights reserved. 23
24 Communication of Risk 2007 Algorithmics Incorporated. All rights reserved. 24
25 Communicating Risks What is my exposure and regulatory capital for United Airlines? What is my exposure and regulatory capital associated with Brazil? What is my total regulatory capital requirement for the bank? Corporate Group Division Subsidiary What is my regulatory capital on the tech sector for our Asian sub? What is my exposure and regulatory capital on non-investment grade products? Branch What is my regulatory Capital on retail mortgages For UK division? Counterparty SIC Country All All Type Group Group 2007 Algorithmics Incorporated. All rights reserved. 25
26 Actively Managing the Portfolio Evaluating risk contributions across quantiles...but: Which cut of the portfolio (sector, geography, business line)? Which statistic (e.g., VaR, UL, Expected Shortfall)? Which quantiles (e.g., 95%, 99.9%, 99.97%)? 2007 Algorithmics Incorporated. All rights reserved. 26
27 Contact Us Eric Takigawa Tel (81) Toru Ohkuni Toru.ohkuni@algorithmics.com Tel (81) Corinne Neale Corinne.neale@algorithmics.com Tel (65) Algorithmics Incorporated. All rights reserved. 27
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