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Estimating Probability of Default Via External Data Sources: a Step Toward Basel II

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Estimating Probability of Default Via External Data Sources: a Step Toward Basel II CAPITAL REQUIREMENTS Estimating Probability of Default via External Data Sources: A Step Toward Basel II by Nadeem A. Siddiqi and Shelley B. Klein xternal data will likely be necessary for most banks to achieve the foundation or advanced IRB approach. Although Ethe decision to use the data may be relatively simple, effec- tive use of it is more complicated and can be critical to success. Careful analysis of the definitions and characteristics implicit in the external data is essential, and banks that do this will likely be reward- ed with more appropriate risk-rating results and an easier time defending their processes to the regulators. anks considering their methods of calculating risk capital probability rates available from strategies for compliance as required by Basel II, can, and major external ratings agencies Bwith the Basel II Capital are, attempting to employ the such as Standard and Poor’s Accord will likely use external foundation internal ratings-based (S&P) and Moody’s Financial data sources for the estimation of approach proposed in Basel II. To Services. probability of default as part of calculate regulatory capital, banks However, banks need to be the solution. Definitions and must determine the probabilities careful when using this data as characteristics must be consistent of default associated with their proxies for specific loan portfolios. or adjusted to be so if the exter- portfolios, and then apply regula- 1. They need to understand the nal data is to be an effective and tor-determined loss given default method of calculating default statistically useful supplement to and exposure at default rates. to ensure that it matches both internal data. Banks that do not One seemingly simple approach the bank’s philosophy and have the most sophisticated banks can take is to use default processes. © 2002 by RMA. Siddiqi and Klein are senior consultant and director, respectively, with the Credit Analytics and Data Management Group of the Financial Services business unit of BearingPoint, Inc. The authors thank Charles Hill and Savitha Sagar for valuable research assistance. All information provided is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will con- tinue to be accurate in the future. No one should act upon such information without appropriate professional advice after a thorough examination of the particular situation. The views and opinions are those of the authors and do not necessarily represent the views and opinions of BearingPoint, Inc. 68 The RMA Journal December 2002 - January 2003 Estimating Probability of Default Via External Data Sources: A Step Toward Basel II 2. They must be careful in 3. The advanced IRB approach mately $116 billion of debt. matching the characteristics allows banks to fully estimate These defaults represented a and structures of the loans the risk and regulatory capital record 4.09% of all rated issuers at with those of the underlying requirements internally. The the beginning of the year. This bonds from the published obvious advantage of using default ratio surpassed the previ- default studies, especially for the advanced IRB approach is ous record of 4.01%, set in 1991.1 loans below investment that if a well-managed bank In addition to a generally weak grade, which may require spe- calculates its capital require- global economy, an abundance of cific adjustments. ments for itself, and its risk recently issued speculative-grade 3. Some loan grades have little profile requires less capital debt, particularly in the leisure published default data avail- than the conservative regula- time/media and telecom sectors, able, and banks may need to tor-determined charges, more contributed to the very high extrapolate their default rates capital will be freed for other default rate. To reflect the chang- from available data. use, thus improving overall ing economic environment and Capitalizing on continuous profitability. the associated increases in advances in technology and ana- defaults, yield spreads on highly lytical methods, Basel II is Recent Default Activity speculative debt widened to a prompting banks to learn more The poor global and domestic point where costs associated with about quantitative credit risk economic environment that pre- issuing debt at such levels were measurement. Many banks’ vailed in 2001 resulted in record prohibitive to most prospective response will include using exter- defaults. During that year, S&P issuers. To lower their cost of capi- nal data to calculate risk capital. observed 216 defaults on approxi- tal, many issuers have been forced Basel II offers three different ways of determining risk capital: Table 1 1. The standardized approach, Corporate Defaults Rates—All Ratings, 1982 through 2001 which applies industry-based Year Default Rate (%) Number of Total Debt Defaulting averages to different asset Defaults ($ Billions) classes and is most suitable 1982 1.26 18 0.9 for very small banks that have 1983 0.68 10 0.4 a relatively homogenous asset 1984 0.83 13 0.4 base and do not have the 1985 1.09 18 0.3 resources to meet regulatory 1986 1.69 32 0.5 requirements to internally cal- 1987 0.93 19 1.6 culate risk. 1988 1.49 32 3.3 2. The foundation internal-rat- 1989 1.75 39 7.3 ings-based (IRB) approach, 1990 2.86 64 21.2 whereby banks need to inter- 1991 4.01 88 23.6 nally estimate part of the risk 1992 1.35 31 5.4 calculation formula, with the 1993 0.86 22 2.4 1994 0.62 18 2.3 rest being determined by 1995 0.97 32 9.0 (conservative) regulator-deter- 1996 0.56 20 2.7 mined rules. This approach 1997 0.59 23 4.9 may be suitable for small and 1998 1.26 56 11.3 medium-sized banks looking 1999 2.19 108 37.8 to get a foothold in the 2000 2.56 132 42.3 advanced approach, without 2001 4.09 216 116.1 having the resources to com- Source: Standard and Poor's, Special Report - Record Defaults in 2001 the Result of Poor mit to it fully. Credit Quality and a Weak Economy. 69 Estimating Probability of Default Via External Data Sources: A Step Toward Basel II to use alternative debt structures. ping is complete, any loan can pools. As used by S&P, the static In some cases, issuers provide col- then be given an equivalent S&P pool assesses the default rates of lateral when issuing debt, or issu- rating, for example, based on the all bonds of a given bond rating, ing securitizations, to receive high- internal bank rating. Then, based regardless of age.3 er credit ratings. A number of on the applicant’s credit rating, his- The S&P default rates do not issuers have also issued debt with torical default performance obser- take into account the age of an structures, including interest vations from S&P may be used to issuance. Default curves obtained reserves, which ensure interest estimate the probability and from S&P’s CreditPro database do payments to investors for a num- potential timing of default. Thus not reflect a new issue bias. New ber of years after issuance. Table 1 starting from existing internal bank issue bias refers to the expected provides historical corporate ratings of commercial loans, proba- results of the hypothesis that an default rates for the past 20 years. bilities of default can be attached. issuer that has just received a sub- stantial cash inflow from a bond The Basic Process A Few Kinks offering or loan is not likely to The risk calculation process While this process of obtain- default in the near term, regard- outlined in Basel II for those ing default probabilities from less of the issuer’s credit rating. A institutions seeking to apply one external data vendors seems new issue bias would be expected of the IRB approaches is also straightforward, several caveats to reduce marginal default rates in composed of three parts. First, the are in order. First, most of the the first three years subsequent to probability of default (PD) must empirical work on corporate the issuance of new debt, with the be obtained. Second, the loss defaults thus far has concentrated effect getting more pronounced as given default (LGD) must be on publicly traded bonds. Due to the credit quality declines. established. Finally, the exposure the private nature of the loan mar- To address this concern, at default (EAD) must be estimat- ket, there is limited publicly avail- Professor Ed Altman from New ed. The foundation IRB approach able loan default data. Second, York University developed a requires banks to estimate only since loan portfolios vary from series of default curves based the PD, while the LGD and EAD bank to bank, even if a reasonable upon this new issue bias hypothe- are determined by regulatory default database were available, it sis. As stated in Managing Credit guidance. In this article, we focus would be inappropriate to gener- Risk: The Next Great Financial on one methodology that can be alize these results for the entire Challenge, “The aging effect is used to estimate the probabilities market.2 intuitively sound, since most com- of default without committing What this implies is that panies have a great deal of cash substantial internal resources, to external default data must be just after they issue a bond. Even utilize the foundation IRB carefully scrutinized for suitability if their operating cash flow is neg- approach to regulatory capital cal- of application to any particular ative, they are usually able to culation, as well as to check any bank’s portfolio.
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