Functionality of a good credit risk management model

A credit risk management model tells the credit risk manager how to allocate scarce
credit risk capital to various businesses so as to optimize the risk and return
characteristics of the firm. It is important to understand that optimize does not mean
minimize risk otherwise every firm would simply invest its capital in riskless assets.
Optimize means for any given target return, minimize the risk.
A credit risk management model works by comparing the risk and return characteristics
between individual assets or businesses. One function is to quantify the
diversification of risks. Being well-diversified means that the firm has no concentrations
of risk to, say, one geographical location or one counterparty.
Figure 10.1 depicts the various outputs from a credit risk management model. The
output depicted by credit risk is the probability distribution of losses due to credit
risk. This reports for each capital number the probability that the firm may lose that
amount of capital or more. For a greater capital number, the probability is less. Of
course, a complete report would also describe where and how those losses might
occur so that the credit risk manager can take the necessary prudent action.
The marginal statistics explain the affect of adding or subtracting one asset to the
portfolio. It reports the new risks and profits. In particular, it helps the firm decide
whether it likes that new asset or what price it should pay for it.
The last output, optimal portfolio, goes beyond the previous two outputs in that it
tells the credit risk manager the optimal mix of investments and/or business
ventures. The calculation of such an output would build on the data and calculation
of the previous outputs.
Of course, Figure 10.1 is a wish lists of outputs. Actual models may only produce some of the outputs for a limited number of products and asset classes. For example,
present technology only allows one to calculate the optimal portfolio in special
situations with severe assumptions. In reality, firms attain or try to attain the optimal
portfolio through a series of iterations involving models, intuition, and experience.
Nevertheless, Figure 10.1 will provide the framework for our discussion.
Models, in most general terms, are used to explain and/or predict. A credit risk
management model is not a predictive model. It does not tell the credit risk manger
which business ventures will succeed and which will fail. Models that claim predictive
powers should be used by the firm’s various business units and applied to individual
assets. If these models work and the associated business unit consistently exceeds
its profit targets, then the business unit would be rewarded with large bonuses and/
or increased capital. Regular success within a business unit will show up at the
credit risk management level. So it is not a contradiction that the business unit may
use one model while the risk management uses another.
Credit risk management models, in the sense that they are defined here, are used
to explain rather than predict. Credit risk management models are often criticized
for their failure to predict (see Shirreff, 1998). But this is an unfair criticism. One
cannot expect these models to predict credit events such as credit rating changes or
even defaults. Credit risk management models can predict neither individual credit
events nor collective credit events. For example, no model exists for predicting an
increase in the general level of defaults.
While this author is an advocate of credit risk management models and he has
seen many banks realize the benefits of models, one must be cautioned that there are risks associated with developing models. At present many institutions are rushing
to lay claim to the best and only credit risk management model. Such ambitions may
actually undermine the risk management function for the following reasons.
First, when improperly used, models are a distraction from the other responsibilities
of risk management. In the bigger picture the model is simply a single component,
though an important one, of risk management. Second, a model may undermine risk
management if it leads to a complacent, mechanical reliance on the model. And more
subtly it can stifle competition. The risk manager should have the incentive to
innovate just like any other employee.