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Credit Risk arises because the possibility that promised cash flows on financial claims held by Financial Institutions such as loans and bonds will not be paid in full.
Credit risk is risk due to uncertainty in a counterparty's (also called an obligor's or credit's) ability to meet its obligations. Because there are many types of counterparties—from individuals to sovereign governments—and many different types of obligations—from auto loans to derivatives transactions—credit risk takes many forms. Institutions manage it in different ways.
In assessing credit risk from a single counterparty, an institution must consider three issues:
default probability: What is the likelihood that the counterparty will default on its obligation either over the life of the obligation or over some specified horizon, such as a year? Calculated for a one-year horizon, this may be called the expected default frequency. credit exposure: In the event of a default, how large will the outstanding obligation be when the default occurs? recovery rate: In the event of a default, what fraction of the exposure may be recovered through bankruptcy proceedings or some other form of settlement?
When we speak of the credit quality of an obligation, this refers generally to the counterparty's ability to perform on that obligation. This encompasses both the obligation's default probability and anticipated recovery rate.
To place credit exposure and credit quality in perspective, recall that every risk comprise two elements: exposure and uncertainty. For credit risk, credit exposure represents the former, and credit quality represents the latter.
For loans to individuals or small businesses, credit quality is typically assessed through a process of credit scoring. Prior to extending credit, a bank or other lender will obtain information about the party requesting a loan. In the case of a bank issuing credit cards, this might include the party's annual income, existing debts, whether they rent or own a home, etc. A standard formula is applied to the information to produce a number, which is called a credit score. Based upon the credit score, the lending institution will decide whether or not to extend credit. The process is formulaic and highly standardized.
Many forms of credit risk—especially those associated with larger institutional counterparties—are complicated, unique or are of such a nature that that it is worth assessing them in a less formulaic manner. The term credit analysis is used to describe any process for assessing the credit quality of a counterparty. While the term can encompass credit scoring, it is more commonly used to refer to processes that entail human judgment. One or more people, called credit analysts, will review information about the counterparty. This might include its balance sheet, income statement, recent trends in its industry, the current economic environment, etc. They may also assess the exact nature of an obligation. For example, secured debt generally has higher credit quality than does subordinated debt of the same issuer. Based upon this analysis, the credit analysts assign the counterparty (or the specific obligation) a credit rating, which can be used for making credit decisions.
Many banks, investment managers and insurance companies hire their own credit analysts who prepare credit ratings for internal use. Other firms—including Standard & Poor's, Moody's and Fitch—are in the business of developing credit ratings for use by investors or other third parties. Institutions that have publicly traded debt hire one or more of them to prepare credit ratings for their debt. Those credit ratings are then distributed for little or no charge to investors. Some regulators also develop credit ratings. In the United States, the National Association of Insurance Commissioners publishes credit ratings that are used for calculating capital charges for bond portfolios held by insurance companies.
Exhibit 1 indicates the system of credit ratings employed by Standard & Poor's. Other systems are similar.
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Standard & Poor's Credit Ratings
Exhibit 1
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AAA Best credit quality—Extremely reliable with regard to financial obligations.
AA Very good credit quality—Very reliable. A More susceptible to economic conditions—still good credit quality.
BBB Lowest rating in investment grade.
BB Caution is necessary—Best sub-investment credit quality.
B Vulnerable to changes in economic conditions—Currently showing the ability to meet its financial obligations.
CCC Currently vulnerable to nonpayment—Dependent on favorable economic conditions.
CC Highly vulnerable to a payment default.
C Close to or already bankrupt—payment on the obligation currently continued.
D Payment default on some financial obligation has actually occurred.
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This is the system of credit ratings Standard & Poor's applies to bonds. Ratings can be modified with + or – signs, so a AA– is a higher rating than is an A+ rating. With such modifications, BBB– is the lowest investment grade rating. Other credit rating systems are similar. Source: Standard & Poor's.
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The manner in which credit exposure is assessed is highly dependent on the nature of the obligation. If a bank has loaned money to a firm, the bank might calculate its credit exposure as the outstanding balance on the loan. Suppose instead that the bank has extended a line of credit to a firm, but none of the line has yet been drawn down. The immediate credit exposure is zero, but this doesn't reflect the fact that the firm has the right to draw on the line of credit. Indeed, if the firm gets into financial distress, it can be expected to draw down on the credit line prior to any bankruptcy. A simple solution is for the bank to consider its credit exposure to be equal to the total line of credit. However, this may overstates the credit exposure. Another approach would be to calculate the credit exposure as being some fraction of the total line of credit, with the fraction determined based upon an analysis of prior experience with similar credits.
Credit risk modelling is a concept that broadly encompasses any algorithm-based methods of assessing credit risk. The term encompasses credit scoring, but it is more frequently used to describe the use of asset value models and intensity models in several contexts. These include
supplanting traditional credit analysis; being used by financial engineers to value credit derivatives; and being extended as portfolio credit risk measures used to analyze the credit risk of entire portfolios of obligations to support securitization, risk management or regulatory purposes.
Derivative instruments represent contingent obligations, so they entail credit risk. While it is possible to measure the mark-to-market credit exposure of derivatives based upon their current market values, this metric provides an incomplete picture. For example, many derivatives, such as forwards or swaps, have a market value of zero when they are first entered into. Mark-to-market exposure—which is based only on current market values—does not capture the potential for market values to increase over time. For that purpose some probabilistic metric of potential credit exposure must be used.
There are many ways that credit risk can be managed or mitigated. The first line of defence is the use of credit scoring or credit analysis to avoid extending credit to parties that entail excessive credit risk. Credit risk limits are widely used. These generally specify the maximum exposure a firm is willing to take to a counterparty. Industry limits or country limits may also be established to limit the sum credit exposure a firm is willing to take to counterparties in a particular industry or country. Calculation of exposure under such limits requires some form of credit risk modelling. Transactions may be structured to include collateralization or various credit enhancements. Credit risks can be hedged with credit derivatives. Finally, firms can hold capital against outstanding credit exposures.
(Source: RiskGlossary.com)
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