22 MARCH / APRIL 2018 Lester Murray Associate Partner The Baker Group lester@GoBaker.com The Baker Group is a Preferred Service Provider of the Indiana Bankers Association and an IBA Diamond Associate Member. DIRECTORS / SENIOR MANAGEMENT Article author Look Before You Leap Using simulations in a decision-making framework Over the last several years, community bankers have become well aware of the regulatory emphasis on, and requirements of, interest rate risk (IRR) management. Throughout the current and persistent environment of ultra-low interest rates, regulatory mandates have expanded to include more stressful rate scenarios, under which income is projected and capital is valued. In addition, sensitivity testing (stressing) of various modeling assumptions has now become part and parcel of routine risk-measuring exercises. Another regulatory condition of these efforts is that they be conducted on a static balance sheet. Quite reasonably, examining agencies do not want to review reports in which interest rate risk could perhaps be masked by simple growth or changes in balance sheet composition. Get the Most Out of Your Model All of that is fine and is certainly adequate in helping to put check marks in the many regulatory boxes requiring one. But, if management stops there, it is failing to exploit what can perhaps be an IRR model’s most valuable capability. That is, giving management the ability to view the outcomes of contemplated changes to strategies and tactics while they are still being contemplated, rather than waiting to experience the results after implementation. To some degree, this concept has already crept into the purview of regulators, as they are strongly recommending that modeling processes include changes in the composition and volumes of various deposit accounts, while exploring the potential effects of alternative funding sources. This type of simulation is less about strategy, which management controls, and more about the consequences that higher interest rates may bring to bear on depositor behavior. And that is certainly something beyond anyone’s control. But what about the things that management does control, or at least heavily influence? For instance, ideas that might successfully reach fruition if outcomes could be known, or missteps that might be avoided for the same reason. Suppose management is considering offering borrowers a new type of loan product with characteristics that may differ significantly from what is currently available. While no model will be able to determine how many customers may or may not go for the new product, performing simulations will allow decision-makers to quantify the effects of various levels of acceptance. Management now has a much better understanding of the risk/reward balance, or imbalance, of trying something new. What about a new kind of deposit product? Maybe a new, longer CD that provides for periodic rate adjustments. What if it brings in $5 million in new money? What if it brings in $50 million? How much do various volumes affect net interest income in various scenarios? What happens to the duration of liabilities and the economic value of equity? Much of the mystery surrounding these potential changes can be cleared up with the performance of strategic simulations. As community bankers know all too well, they operate in an extremely competitive environment. It’s an environment in which adaption and innovation is not only a good idea, it’s necessary for survival. Change for the sake of change is seldom beneficial, and not all innovations bring about the desired results. By taking advantage of your IRR model’s ability to simulate other-than-static outcomes, community bankers can have a better chance of finding strategies that have the greatest chance of success and, just as importantly, identifying the ones that don’t. HB
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