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Interest Rate Risk Modeling—Do The Results Make Sense?

Many credit unions are increasing the number of “What-Ifs” they run. It is important that decision-makers do a gut check on the results being presented.  It is also important to understand that various modeling methodologies may need to be used to ensure appropriate evaluation of the decision.
Take, for instance, a decision to expand auto lending into lower credit tiers.  This decision may prove beneficial to help preserve shrinking margins.  However, taking this potential scenario and running it through a traditional net interest income simulation and NEV will show there is virtually no risk in making this type of decision, assuming the loans are priced near the effective discount rate.
Net interest income and NEV will not address the credit risk component.  In this case, the question that must be answered is, “how will earnings and net worth be impacted by the shift in assets?”  In this example, provision expense should also be adjusted to represent the risk of the shift in assets.  If applicable, collections, legal and other expenses should also be adjusted, to capture the economic reality of increasing credit risk.
Ultimately, any decision that could result in a material change to a credit union’s financial structure should be simulated and all potential financial impacts should be considered, including net operating expenses.  The results should be shared with decision-makers and all should be asking “does this make sense?” and “is there any other impact not captured by the modeling?” to ensure that modeling results do not lead decision-makers astray.
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Aggregating Risks To Net Worth—The Credit Risk Component

During a recent education course, we fielded the following question:  “How do you develop a proxy for a worst-case loan loss assumption when aggregating risks to net worth?”

This is a great question and it stimulated lively discussion.  While there is not one right way, the following method has been valuable in developing concentration risk limits designed to address credit risk.  This method looks back over a specified timeframe (a common, initial look-back is 5 years) and identifies the 6- or 12-month period that experienced the highest annualized loss rate for each loan category.  Each rate is then applied to the current balance of each respective loan category and totaled to come up with the dollars for the total worst-case loan loss assumption.  Frequently, a factor is added to answer, “what if we had to absorb losses beyond our worst historical experience?”  Common factors include increases of 33%, 50%, or even 100% above the worst historical experience.

With many credit unions having just come out of their worst credit loss experiences in memory, this method captures and utilizes the information gained during that environment.  This method is easily reproducible on a periodic basis and can be re-evaluated annually to ensure that the risks are sufficiently captured.  As time progresses, and as loss histories for various loan categories continue, the loss rates may need to be adjusted to account for new loss experiences in order to keep the spirit of capturing a “worst-case” environment.  This process will help to ensure that a credit union’s management and board do not lose sight of the credit union’s worst credit loss experiences.

Whether or not the above methodology is utilized, one thing is abundantly clear—documenting the rationale behind a worst-case loan loss assumption is an absolute must!