34 JANUARY / FEBRUARY 2019 DIRECTORS / SENIOR MANAGEMENT Asset/Liability Rate Risk Not a game of “perfect” Lester Murray Associate Partner-Financial Strategies Group The Baker Group lester@GoBaker.com The Baker Group is a Preferred Service Provider of the Indiana Bankers Association and an IBA Diamond Associate To many, it is a never-ending source of frustration that the exercise of projecting earnings in the context of interest rate risk modeling is such a messy process. • Wouldn’t it be nice if all the variables involved weren’t so variable? • Wouldn’t it be nice if all the uncertainties about rates, markets, competition and customers’ behavior could be less uncertain? • And then, wouldn’t it be nice to be able to know, with unflagging confidence, that the reports produced by your efforts described an outcome from which reality would not deviate? Yes, all these things would be nice but, unfortunately, none of them are likely to happen. The process is far from neat and tidy, and it is unlikely that “down-to-thepenny” precision will ever be achieved. In fact, about the only thing anyone is close to knowing for sure is that whatever the projections say, they’re probably going to be wrong. Hopefully, not too wrong. Following the Federal Reserve’s near-zero rate policy that began in December 2008, the target rate for Fed funds didn’t change again for seven years, and it was another year after that before it changed again. The same is true for the prime rate. To be sure, credit markets had their ups and downs over that period, but for the big variables that affect banks’ interest income and interest expense, that’s about as close to “neat and tidy” as interest rate risk modeling is ever going to get. The assumptions that govern the repricing behavior of assets and liabilities in changing rate environments never really got put to the test, because rates never really changed. It’s hardly been a surprise, then, that for most banks, projections over that time period were pretty spot-on, and the results of back-testing exercises confirmed those results. They should have; it was just the past happening over and over. Climate Change The super-low and static post-crisis rate environment has now undergone more than a handful of increases, and the probability is high that there will be more. For the first time in a long time, risk managers this year will be comparing projections of rising-rate outcomes to actual, higher-rate results. How narrow or wide the variances might be will largely be determined by how close one’s modeling assumptions were to real-life behavior. Chances are, projections will be missed, and the misses could potentially be pretty big. No doubt some of these misses will lead to consternation. While there might be times when a panicked response is appropriate, getting back a bad back-test should not be one of them. Remembering that the whole reason behind the concept is to determine the validity and suitability of your assumptions, delving into the reasons why results didn’t line up with projected estimates is just a learning opportunity. Did the extrapolation of historical norms ignore demographic changes in one’s customer base? Did the competitive landscape change since that last deposit study was performed? Did Walmart move into, or out of, town? The reasons why things may not play out as expected are many and varied, and it doesn’t necessarily follow that there’s anything “wrong” with your processes. The problem lies in the assumptive inputs, and this provides a golden opportunity to see where, and how, adjustments can be made so that reality can better be
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