In the absence of a formal ERM program, an area in which bank and credit union leaders can focus is financial risk modeling. By starting with this reduced scope, the bank benefits from a shorter list of key players and interrelated data that allow for alignment.

In the same webinar, Navigating Post Pandemic: A Stronger Enterprise Risk Program, Dave Koch, the Managing Director of Advisory Services from Abrigo, recommended ways in which bank leaders can coalesce financial risks. He suggested reviewing common scenarios used between risk silos. What assumptions are used for moderate or severe credit stress tests or as part of the Allowance for Credit Losses funding? If those same scenarios were applied in modeling earnings and liquidity, how would the bank fare? In using the same scenarios, bank management can identify potential interactions and overall impact on bank capital and performance, and some examiners or auditors will look for consistency across all financial results.

Similarly, Koch recommended looking at the data sources used across risk analyses. Is it coming from the same, reliable source, and is it used with equal granularity?

“If we are using combined balances in an aggregated assessment over here, but we're doing loan-level data over there, you’re going to have a mismatch,” suggested Koch, much like if orchestra members use a different time signature.

It can be far easier to align assumptions and key data sets, Koch explained, when the institution is using a single platform for financial risk modeling. Bankers can avoid "Frankenstein" dashboards with reports from different systems, and documentation is consistent for audit and exam time.