Interest Rate Risk: Are Your Assumptions Accurate?

4-16-14-Moss-Adams.pngModel assumptions have gained a great deal of importance in the banking industry. Financial institutions are using them more and more to generate output that summarizes the risks embedded in their balance sheet. But are these models always accurate? The answer, at least from banking regulators, is increasingly no.

For example, many interest rate risk (IRR) models continue to show that earnings will improve as a result of an increase in interest rates. However, a December 2012 presentation by the San Francisco Federal Reserve indicates that deposit assumptions, such as decay rates, beta-adjusted gaps (the relative repricing rate assumed for deposits versus a benchmark rate), account balances and deposit mix have a significant impact on IRR measurements. As a result, the Fed contends that the current IRR environment may cause model results to provide misleading data. In particular, the Fed cited an increase in non-maturity deposits as a percentage of total deposits.

The Fed noted that one of the main reasons for the increase in non-maturity deposits since midway through the recession is the drop in the federal funds rate. It believes that customers have parked funds over the past several years in non-maturity deposits since there’s been little difference in earnings between non-maturity and time deposits. This shift has caused non-maturity deposits to increase to 83 percent of total deposits as of December 31, 2012, from an average of 62 percent from 1985 to 2008—an increase of 33 percent.

So, for example, if your institution’s IRR model deposit mix assumption is based on current or recent historical deposit characteristics, there could be a surprise waiting for you, since it isn’t likely that interest margins on your deposit base will remain the same as interest rates rise. More likely, most institutions’ deposit mix will return to average pre-recession levels.

Changes to basic deposit assumptions can have a significant impact on earnings. For example, if interest rates rise by 200 basis points (bps), reallocation of the deposits mix to pre-recession levels may negatively impact earnings at risk (EAR) by up to 400 bps. EAR is a measure of the change in earnings based on changes in interest rates. Let’s say you’re currently reporting a positive exposure to EAR of 5.8 percent using today’s deposit mix. By adjusting the deposit mix to pre-recession levels, using the same 200 bps increase in interest rates, you’d see your EAR drop to a positive exposure of 1.8 percent.

Similarly, changing account balance assumptions to assume a decline in non–interest bearing deposits or changing deposit decay and beta-adjusted gap assumptions could easily take a positive EAR result and make it negative.

So what can you do to help your institution address these risks and regulators’ concerns?

  1. Reexamine key IRR assumptions. Don’t focus only on deposit assumptions, but regularly evaluate all assumptions feeding your IRR. This exercise most likely will result in an adjustment of your model assumptions and drive a deeper understanding of the true risks embedded in your balance sheet.
  2. Perform stress testing or scenario testing of your assumptions periodically. Determine which have the greatest potential impact on your institution, and spend more time ensuring those assumptions are valid.
  3. Perform detailed, comprehensive back testing. The best way to determine whether the assumptions used in your IRR model are reasonable is to test actual results based on prior assumptions. Analysis will help you identify the impact of shifts in transactional patterns and the resulting impact on the balance sheet. Although you may not be able to predict these types of shifts, by completing this testing you’ll be able to modify assumptions and update your model, resulting in more accurate, meaningful reporting.
  4. Revisit scenario testing. What changes are occurring in the market that could affect your institution negatively? What’s the likelihood they’ll occur and the degree of impact on your institution? Is your institution willing to assume that level of risk?
  5. Document your evaluation. Your regulator conducts analysis in these areas to evaluate your management of IRR. Thoroughly documenting the basis of your assumptions will aid them in understanding how you mitigate risk as an organization.