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Credit Portfolio Management Current State of Practice Charles Smithson Managing Partner, Rutter Associates Copyright 2001 Rutter Associates, LLC www.rutterassociates.com Credit Markets Are Being Transformed The way credit risk is measured and managed is changing, because of • Market realities • Changing regulatory environment • Theoretical and analytical advancements • Technology • Advent of new measurement/management tools Rutter Associates 2 Market Realities • Higher risks -- More concentration in loan portfolios (to less creditworthy obligors) • Lower return • Banks are no longer the primary holder of loans Rutter Associates 3 Defaults in Excess of $1 Billion 1998 Home Holdings Boston Chicken Criimi Mae Grand Union Mercury Finance 1999 Loewen Group Iridium Harnischfeger ICO Global Sun Healthcare SOURCE: Barry L. Campbell, BMO Nesbitt Burns, “Investing in Assets with Credit Risk,” RISK Credit Summit, September 28, 2000 2000 AMF Bowling Armstrong World Ind Genesis Health Ventures ICG Communications Laidlaw Owens Corning Paging Network Pathmark Stores Pillowtex Safety-Kleen SOURCE: “Corporate Defaults: Will Things Get Worse Before They Get Better?” S&P CreditWeek, Jan 31, 2001 Rutter Associates 4 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan ORIGINATORS: What is the bank’s perception regarding large corporate and middle market loans? a) Loans generate sufficient profit that they add shareholder value b) Loans do not add shareholder value by themselves; they are used as a way of establishing or maintaining a relationship with the client … but the loan product must be priced to produce a positive NPV. c) Loans do not add shareholder value by themselves; they are used as as way of establishing or maintaining a relationship with the client … and the loan product can be priced as a “loss leader.” Rutter Associates 5 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan ORIGINATORS: What is the average ROE for… …revolving & backup facilities for large, investment-grade companies? …term loans to middle-market growth (below investment grade) Companies? Rutter Associates 6 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan ORIGINATORS: For non-investment grade loans that your bank originates… …what is the maximum “hold level”? …what is the target “hold level”? Rutter Associates 7 Primary Market for Highly Leveraged Loans by Broad Investor Type 1994 – LTM6/30/2000 50% Share of Market 40% Institutional Investors Foreign Banks 30% Domestic Banks 20% 10% 0% 1994 1995 1996 1997 1998 1999 LTM6/30/00 Source: S&P/Portfolio Management Data Rutter Associates 8 Providers of Software or Data for Probability of Default Vendor Altman Kamakura KMV LPC Moody’s S&P Product Name Risk Mgr – Credit Risk Suite KRIS – cr,cs Private firm model under construction Credit Monitor EDF Calc Private Firm Model Risk Rater Historical Transition Matrices Risk Calc for Public Companies Risk Calc for Private Companies CreditPro CreditModel Rutter Associates 9 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan INVESTORS (PORTFOLIO MANGERS) What is the primary source of probabilities of default for your portfolio model? a) Bond Migration studies (e.g, Moody’s, S&P, Altman) b) KMV’s EDFs c) Probabilities of default implied from term structures of spread d) Internal review of portfolio migration Rutter Associates 10 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan INVESTORS (PORTFOLIO MANGERS) What is the primary source of data on Loss in the Event of Default for your portfolio model? a) Internal review of charge-offs b) Third-party data bases c) Industry-wide studies d) Rating agency analysis Rutter Associates 11 Providers of Data on Utilization Vendor Product Name LPC Loan Loss Database S&P CreditPro Rutter Associates 12 Black-Scholes-Merton No Arbitrage/Contingent Claims Analysis “Structural Models” “Reduced Form Models” First Generation Models Third Generation Models Merton (1974) Black and Cox (1976) Jarrow and Turnbull (1995) Madan-Unal (1996) Duffie and Singleton (1998) Jarrow Lando and Turnbull (1995) Das and Tufano (1996) Second Generation Models Hull and White (1995) Longstaff and Schwartz (1995) “Fourth” Generation Models Risk Management Models Madan and Unal (1999) Creditmetrics™ and KMV Rutter Associates 13 Question posed to Loan INVESTORS (PORTFOLIO MANGERS) Do you use a credit portfolio model? Obligor Facility Exp Loss Portfolio Unexp Loss Capital Risk Cont Rutter Associates 14 Providers of Credit Portfolio Models Developer/Vendor Product Name CSFB CreditRisk+ KMV Portfolo Manager Kamakura Risk Manager – Credit Risk Suite McKinsey CreditPortfolioView RMG Credit Manager Rutter Associates 15 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan INVESTORS (PORTFOLIO MANGERS) Which of the following is your primary credit portfolio model? a) CreditMetrics b) CreditRisk+ c) KMV’s Portfolio Manager d) CreditPortfolioView e) Internally-developed model Rutter Associates 16 Macro Factor CreditRisk+ Portfolio Manager CreditManager CHARACTERISTICS Model Type Structural Structural Factor Actuarial Asset Value Asset Value Macro Factors Default Event Both MTM MTM Default Only Endogenous Exogenous Exogenous Exogenous Exogenous Exogenous Exogenous Exogenous Asset Correlation Equity Correlation Endogenous Endogenous Loss Distribution Simulation Simulation Simulation Gamma Valuation Model Quasi EDF Forward Spread Forward Spread N.A. Stochastic Variable MTM or Default? INPUTS Probability of Default LGD Default Correlation CALCULATION Switches to Set Spread Recovery Recovery Distribution Treatment of Commitments Treatment of Commitments Iterations in Simulations FX & Interest rates Pricing parameters Xxxx Default Rate Volatility OUTPUT Risk Contribution Capital 17 Standard Dev Mar Std Dev Incr Std Dev Multiple of Risk Cont Multiple of Risk Cont Standard Dev ETA Standard Dev Direct Estimate Multiple of Risk Cont Rutter Associates Existing Model Comparisons • Descriptive – Basle Committee on Banking Supervision (1999) – Federal Reserve System Task Force (1998) • Mathematical – Gordy (2000) – Lopez and Saidenberg (2000) – Hickman and Koyluoglu (1998) • Empirical • ISDA/IIF • Occasional ad hoc comparisons using available data sets Rutter Associates 18 Existing Model Comparisons (Continued) • Academic – Identify mathematical relation between model types – Some simulation over stylized portfolios – Mathematically and experimentally models can give similar results • ISDA/IIF – Ambitious range of portfolio types and model types (25 Banks participated with a variety of models and portfolios ) – Similar inputs result in similar outcomes – One time effort; not reproducible • Industry – Use of “actual” portfolios to illustrate use of the model – Focus on applications: Hedging; Capital allocation – Reproducible results Rutter Associates 19 Portfolio Selection Process KMV Non-Fin Universe 7287 N.A. Firms Random sample of Approx. 3000 Non-Fin obligors KMV Financial Universe 1722 N.A. Firms Proper subset of KMV Non-Financial Modify Selection To Obtain Desired Rating Distribution Proper subset of KMV Financial Non-Financial Test portfolio Financial Test portfolio Filtered by Geography, Industry, Facility, etc. Starting Portfolio 2903 Obligors 3136 Exposures N.A. North America. Asian and European portfolios are also available. Rutter Associates 20 S&P Rating (Implied) Distribution of Obligors AA A BBB BB B CCC Grand Total Investment Grade Non-Investment Grade Distribution of Commitments 2.2% 6.5% 34.2% 30.6% 17.6% 9.0% 100.0% 7.4% 11.0% 38.2% 27.6% 10.6% 5.1% 100.0% 42.9% 57.1% 56.6% 43.4% Rutter Associates 21 Distribution of Commitments by Facility Type Term Loan Guarantee Bonds Grand Total Facility Share 55% 13% 11% 20% 100% AA 10% 0% 9% 5% 7% A 12% 0% 17% 13% 11% BBB 40% 13% 53% 43% 38% BB 27% 50% 10% 25% 28% B 8% 25% 8% 10% 11% CCC 4% 13% 4% 5% 5% 100% 100% 100% 100% 100% Rating Composition Revolvers Notes: Very few firms have an implied AAA rating based on KMV EDF values Rutter Associates 22 Models Used KMV Portfolio Manager RiskMetrics Group CreditManager CSFB CreditRisk+ Rutter Associates Macro Factor Model* *The Macro Factor Model implements the approach described by Wilson in CreditPortfolioView Rutter Associates 23 Typical Implementation of Risk Contribution Standard deviation Percentile for Capital ` Expected Loss 99.9th Percentile Risk Contribution Standard Deviation Is Allocated to Deals Allocations Sum to Portfolio Standard Deviation Rutter Associates 24 Typical Implementation of Risk Contribution sp RCAsset = xA xA By construction risk contributions sum to portfolio standard deviation SA RCAsset = sp Rutter Associates 25 Typical Capital Allocation Capital is a multiple of Risk Contribution CapAsset = RCAsset x Portfolio Capital sp Rutter Associates 26 Alternative Risk Contribution Measures • Standard deviation based measure -- contribution per dollar of exposure (KMV, RMG, CR+, MF) • Standard deviation based measure -- contribution per deal (currently RMG) • Marginal contribution (measured at a given percentile loss) – Incremental effect of a transaction on a given percentile of the distribution – Marginal contributions do not sum to standard deviation or to capital • Capital-based measure Rutter Associates 27 An Alternative Capital-Based Risk Contribution “Empirical Tail Allocation (ETA)” Standard deviation ETA models losses in the tail region ` 98th <100 99.9th Percentile Expected Loss Portfolio Losses Rutter Associates 28 ETA Concept • Simulate a large number of portfolio losses – Identify losses in the “neighborhood” of capital • For each loss in the neighborhood of capital – Identify those exposures that contributed to the loss – Identify how much each exposure lossed (optional) • Calculate conditional probabilities – Conditional on a capital-level loss • Probability of Obligor “A” contributing • Expected dollar amount of “A’s” contribution • Conditional probabilities and losses are scaled to allocate economic capital or calculate risk contribution Rutter Associates 29 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan INVESTORS (PORTFOLIO MANGERS) Rank the following tools in order of their importance to the management of your credit portfolio. (“1” denotes the most important and “4” denotes the least important.) Management of new business and renewals of existing business Loan sales and trading Credit derivatives Securitizations Rutter Associates 30 To meet the challenge of increasing riskadjusted return ... ... the managers of credit portfolios must adopt Modern Portfolio Management to create efficient portfolios ... banks must become “asset managers” with respect to their own portfolios ...the organization of financial institutions must change Rutter Associates 31 Survey of Credit Market Participants (December 2000 issue of CREDIT) Question posed to Loan INVESTORS (PORTFOLIO MANGERS) Do you now or do you plan to mark the loan portfolio to market or model? a) Currently mark to market b) Currently mark to model c) Plan to mark to market or model in the future d) No plans to mark to market or model Rutter Associates 32 Survey of Credit Market Participants (December 2000 issue of CREDIT) Who “owns” the economics of the loan portfolio? a) Portfolio Management exclusively b) Line Units exclusively c) Portfolio Mgmt / Line partnership d) Treasury Rutter Associates 33