Credit Risk and Capital: A Basic Primer - Executive Summary

This is a summary of an article by David Finnie of RSD Solutions LLC. The full article can be found in the "Resources" section of RSD Solutions' web site (www.RSDsolutions.com).

Building an integrated risk management capability has been of paramount interest for many financial institutions over the past decade or so. Increasingly, non-financial firms have begun to see the value of this framework. Financial institutions are looking for an ability to capture all of their risks in a fungible, useful format. A format that allows them to understand, as fully as possible, their total risk profile, their risk composition and their risk return performance. Non-financial firms can use the same framework to acchttp://www2.blogger.com/img/gl.link.gifomplish the same understanding and, importantly, to determine how much capital is required to maintain debt ratings and shareholder expectations and to allow the successful execution of the firm’s organizational strategies.

The framework to accomplish integrated risk management and risk-based capital management is an economic capital framework. The Credit Risk and Capital Basic Primer, available on the RSD Solutions website (), outlines the approaches and methodology to develop the capital needed to support the credit risk activities of the firm.

To build a fully developed economic capital framework, a risk capital framework capturing credit, market and operational risk is needed. For non-financial firms, this is necessary but insufficient since many of their capital needs are derived from non-risk factors. For this reason, it is also necessary to deal with infrastructure needs, business model attributes and strategic needs among others.

Credit and Counterparty Risk is the potential for loss due to the failure of a borrower, endorser, guarantor or counterparty to repay a loan or honor another predetermined financial obligation.

Credit Risk Capital is needed to provide protection for Unexpected Losses (ULs). Expected Losses, those losses that would be expected given the portfolio of obligations held by the firm, need to be built into the pricing of those obligations. A simple example – a high risk bond provides a higher interest rate than a low risk bond. Unexpected Losses are the variances around the Expected Losses. These losses are covered by the firm’s capital.

The development of credit risk capital depends on the three key concepts needed to determine Expected Loss – Exposure at Default, Probability of Default and Loss Given Default. To bring this to Unexpected Loss, the volatilities of these variables and the correlation of the assets within the credit portfolio are also needed.

Probability of Default is the critical driver of capital in this model and is expressed in the capital equation as the cumulative distribution function for a standard normal random variable (refer to The Credit Risk and Capital Basic Primer, available on the RSD Solutions website) which includes the inverse cumulative distribution function for a standard normal random variable. The complex set of equations boils down to some very simple relationships:

• Diversity matters – both in terms of the diversity within the portfolio (i.e. the direct relationship between individual obligors) as well as the relationship of the portfolio to general economic conditions.
• The loss distribution is generally characterized as “fat-tailed” (or leptokurtotic) which means that to reach a given confidence level, one must move out further along the distribution than for a normal distribution.
• The capital result is heavily dependent upon the risk of the underlying obligor or portfolio of obligors – each level of risk entails a different distribution of losses and, as the risk increases, the distribution becomes increasingly “fat-tailed” – the capital requirement increases at an increasing rate as risk deteriorates.

As the Credit Risk Capital Primer concludes, the amount of capital required to support credit operations can be managed through standard credit decision frameworks and through effective credit facility pricing.