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Home > Financial Risk Management Best Practice > Managing Counterparty Credit Risk

Financial Risk Management Best Practice

Managing Counterparty Credit Risk

by David Shimko

Executive Summary

  • Counterparty risk exposure is the financial measure of performance risk in any contract.

  • Many contract exposures are managed through operational or legal means; this article focuses on financial risk management.

  • Counterparty credit exposure equals current exposure (accounts receivable minus collateral) plus an adjustment for potential future exposure based on possible increases in future net receivables.

  • A comprehensive credit risk management policy addresses counterparty initiation and monitoring, contracting standards, credit authorities and limits, the transaction approval process, credit risk reporting, and reserving and capital policy.

  • Credit risk mitigation is best handled through collateral, but there are legal and financial means to mitigate credit risk as well.

  • Credit insurance can fit the exposure perfectly, but may be costly.

  • Credit default swaps are linked to credit events and payments that may not correspond exactly to counterparty exposures, but may be cheaper than credit insurance.

Defining Counterparty Risk

Counterparty risk is the risk to each party of a contract that the counterparty will not live up to its contractual obligations; it is otherwise known as default risk.

Counterparty risk relates closely to performance risk. It arises whenever one entity depends on another to honor the terms of a contract. If a parts supplier fails to provide steering wheels to General Motors, GM will be damaged because of its inability to deliver complete cars. The resulting profit reduction is defined as the exposure that GM runs to its supplier. Similarly, GM runs a credit exposure to its customers who have not yet paid for their cars. This would include dealers and end customers who are financed by GMAC, GM’s financing subsidiary.

Normally, performance risk is managed operationally—i.e., GM would use alternative suppliers, reserve supplies of steering wheels, and contractual nonperformance remedies to manage its performance risk. Also, to manage risk to its dealers, it may retain title to vehicles, verify insurance coverage, obtain some advance payment, and use legal means to minimize their collections risk. In addition to these counterparty risk situations, GM will experience counterparty risk from its derivative contracts.

Suppose GM wanted to purchase steering wheels on an ongoing basis from a European supplier, and protect itself from devaluation of the US dollar. It would likely enter a foreign exchange swap transaction with a bank. After entering the contract, rates would continue to change, bringing the contract in-the-money to either GM or the bank. If the dollar were to devalue, the contract would move in-the-money to GM, which would expose GM to the possible failure of the bank to honor its contract. Conversely, if the dollar were to strengthen, the bank would have an in-the-money contract with GM, and subsequently become concerned about GM’s possible default risk.

Measuring Counterparty Risk

Counterparty risk exposure can be divided into accounts receivable exposure and potential future exposure. If collateral is held as a bond for performance risk, the amount of the collateral is deducted from the gross exposure calculation. If the collateral itself is risky, such as a deposit of traded securities rather than cash, the collateral may not get full credit. Therefore, total credit exposure can be defined as follows:

Current exposure = Maximum of {Accounts receivable (A/R) – discounted collateral value} and 0

Potential future exposure = Current credit exposure plus maximum likely increase in future credit exposure

The maximum likely increase in future credit exposure is defined relative to a timeframe and relative to a statistical confidence interval, typically 95%. To demonstrate this concept simply, assume a potential foreign exchange transaction as an expected value of zero with an annual standard deviation of σ, a duration of τ, and a normally distributed risk. This is illustrated in Figure 1.

The definite loss shows in which cases GM will owe money to the bank, while vulnerable profit shows cases where the bank may owe money to GM. It is called vulnerable on account of the default risk of the bank. Although the current exposure is zero, the vulnerable profit could be as great as 1.65 standard deviations using a 95% confidence interval. This is also known as the peak exposure. The probability-weighted average of all the exposure figures, both zero and positive, is known as the expected exposure. For the normal distribution case, the expected exposure is 0.40 times the standard deviation.

To determine the expected loss conditional on default, we need to have two more pieces of information. One is the probability of default, which we will call π. The other is the loss given default, i.e., the percentage of the exposure that we never recover, even after settlement or bankruptcy. We call this estimate λ. Given these assumptions, we may summarize:

Peak exposure = 1.65σ√τ

Expected exposure = 0.40σ√τ

Expected loss = 0.40πλσ√τ

For example, if GM determines the Euro volatility to be 15% per year, the contract to be three months in duration (0.25 years), its bank to have a default likelihood of 10%, and the loss given default to be 50%, its expected loss is (0.40 × 0.10 × 0.50 × 0.15 × √0.25) = 0.0015 times the size of the transaction—i.e., $1500 per million dollars hedged.

In the case of a swap rather than a single forward transaction, the amortization of the swap payments reduces exposure over time, so that it does not necessarily rise with the square root of time. In this case, the peak and expected exposure can be determined as in Figure 2.

The peak exposure can be used to understand how much risk is being taken with respect to the counterparty, whereas the expected exposure is an indicator of expected losses.

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Further reading

Books:

  • Saunders, Anthony, and Linda Allen. Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms. 2nd ed. New York: Wiley, 2002.
  • Servigny, Arnaud de, and Olivier Renault. Measuring and Managing Credit Risk. New York: McGraw-Hill, 2004.

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