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Effective Credit Risk-Rating Systems

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Effective Credit Risk-Rating Systems INTERNAL RISK RATINGS Credit Risk-Rating Systems by Tom Yu, Tom Garside, and Jim Stoker n this first of two articles, the authors describe the capabilities, desired attributes, and potential accruing benefits of effective credit risk-rating systems. The practical issues arising in an over- haul, the main theme of the second article, will be shown through a case study of one regional bank’s initiative to upgrade its credit risk man- agement process. redit risk ratings provide a models cannot be improved but portfolios. For corporate lending, common language for that the process of implementation credit scoring has been an impor- describing credit risk is challenging. Ratings are so tight- tant accelerator for securitization. exposure within an organization ly woven into the fabric of most and, increasingly, with parties out- institutions that they are part of the Justification for Change side the organization. As such, they culture. And any significant change A decade of advancements in drive a wide range of credit to the culture is difficult. quantitative measures of credit risk processes—from origination to However, the pressures to have led to better risk management monitoring to securitization to change are mounting from both at the transaction level as well as workout—and it is logical that bet- internal and external sources. the portfolio level. Lenders can ter credit risk ratings can lead to Internally, it may be the desire to actively manage their portfolio better credit risk management. Yet price loans more aggressively or to risks and returns relative to the many lenders are using ratings sys- support a more economically institution’s risk appetite and per- tems that were put in place 10 or attractive CLO structure. formance targets. more years ago. Externally, the capital markets At the same time, it is becom- The primary barrier to change, desire more detailed, more finely ing increasingly clear that banks, in it seems, is not that the old rating differentiated measures of credit spite of their historical role, are actu- © 2001 by RMA. Yu is a senior manager specializing in North American work at Oliver, Wyman & Company (OWC) in New York; Garside is director and head of the firm’s Risk Management Practice in London; and Stoker is a senior manager specializing in Risk, based in New York. The authors acknowledge the assistance of George Morris, Jim Wiener, and John Stroughair, directors, and John Stewart, senior manager, all at OWC. Oliver, Wyman & Company is a strategy consulting firm dedicated exclusively to the financial services industry. Contact Stoker at [email protected]; visit OWC’s Web site at www.owc.com 38 The RMA Journal September 2001 Effective Credit Risk Rating Systems ally disadvantaged holders of credit the mean loss that can be expected nation for credits that seem identi- risk. The combination of high capital from holding the asset. This is cal- cal to the credit officer considering requirements and double taxation culated as the product of three com- the loans, damages the credibility of means that credit extension is typical- ponents: the model and makes it difficult to ly not contributing positively to Expected Loss (EL) 5 employ as a decision-support tool. shareholder value creation. Improved Probability of Default (PD) 3 Unconstrained model development risk ratings can improve the returns Exposure At Default (EAD) 3 also runs the risk of creating a in this business by significantly low- Loss Given Default (LGD). black-box solution; to the extent This article concentrates on the ering risk and process costs. possible, a new rating system success of a credit rating system in Some leading players are (joined with good internal training) rethinking the business model as a terms of its ability to quantify PD should produce results with which and LGD. For most commercial credit conduit. The originate-and- people are intuitively comfortable exposures, EAD is generally treated hold strategy is being replaced with and be capable of providing guid- one of originate-package-distribute. independently from the risk ratings, ance on why discrepancies have and this article will treat it as such. Credit risk is becoming managed in arisen. At times, this will require a The important risk drivers that much the same way as interest rate high-level design decision regarding risk or equity risk. To make this affect PD and LGD vary from asset the balance between complexity and class to asset class. For example, strategy work, it is essential that clarity within the institution. While the drivers of risk vary widely credit risk is measured in a more complexity can add to a model’s standardized, accurate, and timely between retail, commercial, and predictive power, it can also reduce asset-backed lending. Therefore, a fashion. organizational buy-in by making the successful credit risk rating system Additional impetus is provided system less intuitive, dramatically by the proposed reforms to bank reg- that covers material exposures reducing its practical value. Good across a bank will necessarily be ulation put forward by the Bank for rating systems should improve quite complex, with numerous dis- International Settlements (commonly process efficiency by reducing known as Basel II) that are intended tinct models. process costs and freeing time for This points to a second goal of to supersede the straight 8% mini- sales and relationship management. a credit risk rating system: It is not mum capital charge levied on banks All of these points require trust in since 1988. The expectations inher- enough to accurately measure risk, the rating system—users must be it also must provide the bank with a ent in this reform adds to the pres- confident that it works—with vali- unified view of its credit risk. It sures for changing internal risk rat- dation and back-testing as crucial ing systems. The promise is that less needs to ensure that a rating system elements in achieving this. permits the simple aggregation of capital will be required for banks Designing a system to include risk—by obligor, portfolio, line of using more advanced ratings. Many all the qualities listed above is chal- banks will find that without a sub- business, and product type—and lenging, because it involves both a thus allow the institution to make stantial overhaul, their credit risk-rat- technical excellence during the decisions based on solid estimation ing system will fail to meet Basel II development stage and potentially guidelines. of the credit risk being taken. far-reaching organizational and cul- Simply put, being “right” is not tural realignments. enough. The system must be easily Steps Toward Change Begin with Understanding the Goal understood by a wide range of peo- Components of a Successful ple and be useful for management The fundamental goal of a System decision taking. credit risk rating system is to esti- There are three key dimensions mate the credit risk of a given trans- For the user, this means that it to a risk rating system, as seen in should behave in an intuitive and action or portfolio of transactions Figure 1. To be effective, a system predictive fashion. For example, a /assets. The industry standard must be successful in all three “building block” for quantifying system that generates dramatically dimensions: different risk ratings, without expla- credit risk is Expected Loss (EL), 1. Ratings Scale addresses the 39 Effective Credit Risk Rating Systems but often this Figure 1 is not the case with specific credit expo- sures being overlooked, such as letters of credit or the counterparty credit risk aris- ing from trad- ing positions. To get an accu- rate profile of an institution’s credit risk institution-wide metric against basis but poorly in gauging an exposure, every credit exposure which all assets will be com- absolute level of expected loss of needs a comparable risk rating. The pared. each. key is to use a “master scale”—a 2. Ratings Assignment addresses Most rating systems use a two- single scale to which all counterpar- the actual ratings process. dimensional scale to solve this prob- ties are mapped. It should be noted 3. Validation addresses confidence lem, with the probability of default that having such a universal ratings in the system, both internally (PD) and the loss given default scale does not imply that all asset and externally. (LGD) being quantified separately classes use the entire scale. For (consistent with the proposed Basel Ratings scale. A risk rating example, you would expect corpo- II guidelines). The first dimension system uses an objective scale to rate loans to be concentrated at the (PD) is primarily determined by the rank credits according to risk. In top end of the scale (with low prob- obligor characteristics. The second defining the scale, we answer three ability of default) and retail loans to dimension estimates how the facility questions: be concentrated towards the lower- structure affects the LGD. • What does a given rating middle part of the scale. A key element in the definition mean? Ratings assignment. After the of a ratings scale is the determina- • How many ratings should there ratings scale is defined, it is neces- tion of the appropriate level of gran- be? sary to choose an approach for ularity. Each grade should have • To which credits does the scale assigning ratings to counterparties, markedly (and measurably) different apply? and this raises several issues: risk characteristics. If the level of The ultimate goal is to provide • How are ratings assigned for granularity is too small (that is, there a measure of the loss expected for each business unit? are too few grades), the system will booking a credit and the capital • Who assigns the ratings? not be a useful decision support tool required to support it.
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