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Portfolio Credit Risk

by Thomas C. Wilson of McKinsey and Company

October 1998

Introduction and Summary: Financial institutions are increasingly measuring and man-aging the risk from credit exposures at the portfolio level, in addition to the transaction level.  This change in perspective has occurred for a number of reasons.  First is the recognition that the traditional binary classification of credits into "good" credits and "bad" credits is not sufficient-- a precondition for managing credit risk at the port-folio level is the recognition that all credits can potentially become "bad" over time given a particular economic scenario.  The second reason is the declining profitability of traditional credit products, implying little room for error in terms of the selection and pricing of individual transactions, or for portfolio decisions, where diversification and timing effects increasingly mean the difference between profit and loss.  Finally, management has more opportunities to manage exposure proactively after it has been originated, with the increased liquidity in the secondary loan market, the increased importance of syndicated lending, the availability of credit derivatives and third-party guarantees, and so on.

In order to take advantage of credit portfolio management opportunities, however, management must first answer several technical questions: What is the risk of a given portfolio? How do different macroeconomic scenarios, at both the regional and the industry sector level, affect the portfolio's risk profile? What is the effect of changing the portfolio mix? How might risk-based pricing at the individual contract and the portfolio level be influenced by the level of expected losses and credit risk capital?

This paper describes a new and intuitive method for answering these technical questions by tabulating the exact loss distribution arising from correlated credit events for any arbitrary portfolio of counterparty exposures, down to the individual contract level, with the losses measured on a marked-to-market basis that explicitly recognizes the potential impact of defaults and credit migrations. The importance of tabulating the exact loss distribution is highlighted by the fact that counterparty defaults and rating migrations cannot be predicted with perfect foresight and are not perfectly correlated, implying that management faces a distribution of potential losses rather than a single potential loss.  In order to define credit risk more precisely in the context of loss distributions, the financial industry is converging on risk measures that summarize management-relevant aspects of the entire loss distribution.  Two distributional statistics are becoming increasingly relevant for measuring credit risk: expected losses and a critical value of the loss distribution, often defined as the portfolio's credit risk capital (CRC).  Each of these serves a distinct and useful role in supporting management decision making and control.

Published in: FRBNY Economic Policy Review, Vol. 4, No. 3, (October 1998), pp. 71-82.

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