However, 70 out of 100 CEOs and CFOs informally surveyed by Abrigo, formerly FARIN, acknowledged they don’t rely on their ALM modeling for decision-making.
One reason ALM models are underutilized is that many bankers don’t trust the results of their ALM models, according to Koch. They recognize that most ALM models lack precision due to a number of factors. Incoming data from the core system might be missing information. For example, a variable loan might be missing the repricing index and margin information because it was set up on the loan system without that data due to human error. Or non-maturity deposit data might be using incorrect assumptions about how long those accounts will remain with the institution because the assumptions are based on industry averages.
Financial institutions certainly have options to correct such issues so they can begin using their ALM process for strategic decision-making. Running a core deposit analysis provides institution-specific, updated information about decay rates for non-maturity deposit accounts, and working with ALM advisory experts can ensure the ALM model has the necessary data and power to generate decision-useful information. For example, institution-specific information on attrition rates of specific non-maturity deposit account products can feed into decisions about what rates to offer customers on those products, rather than relying solely on what rates competitors are offering.
“When it’s done right, ALM provides a community financial institution with the right guidance on maximizing profit while managing risk,” Koch says.
Much like portfolio stress testing, a robust ALM process should allow for the generation of scenarios to provide management a clear view of the financial institution's risk profile under a variety of conditions, said Neekis Hammond, Managing Director of Abrigo Advisory Services. Financial institutions that utilize the same portfolio data for the ALM as for other risk activities, such as calculating the allowance for credit losses, will be able to provide these scenarios with more confidence than institutions using various systems and inputs.
"When executed thoughtfully, CECL [current expected credit loss] models may be leveraged to produce a variety of detailed information about interest timing, credit adjusted rates of return, and lost interest due to defaults," Hammond said.
Financial institutions that maximize profit while managing risk will be able to not only avoid the hazards of extreme increases in interest rates, they will also be able to elude the danger of underperformance and failing to create value during more routine interest rate periods.
