Over the years, financial institutions have gained confidence in the modeling software they rely on to guide asset-liability management, but there is still significant room for improvement. Validations of credit union ALM models from 2012 through 2015 indicate that 52 percent are still ranked as average and 24 percent of models are ranked below average.

Here are 10 areas that we have encountered in our work with financial institutions where modeling can be improved:

1. Data inputs/current contractual position

The precision of an interest-rate risk simulation model depends on the quality of the input data and the category designs that capture the data. The adage “garbage in, garbage out” applies here. Financial analysts should regularly review cash flow and other model inputs. In addition, regulatory guidance is clear about the critical importance of rigorous data quality assessment and documentation. Through regular audits, internal and external data inputs must be continually verified to be accurate, complete and consistent with the model purpose and design.

Balancing the model to the general ledger is only the first step of the review process. It is also necessary to review maturity and repricing schedules and rates for accuracy. For example, ask: Do variable or adjustable rate balances reprice appropriately?

 

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