A stronger regulatory focus on managing interest rate risk on the balance sheet has brought to the forefront the requirement that institutions back test their IRR models. Back testing is a means to check the sufficiency of the data, the setup and the assumptions used to produce an analytical report. Back testing a model compares the projections of a past report against the actual figures produced during that same time horizon.

Comparing actual data to a past projection can help identify and measure discrepancies so that any that are found can be properly explained or corrected. By identifying variances between projections and actual figures, an institution can pinpoint holes in the core data, the modeling structure, the assumptions and even the report presentation. These items then can be fixed or their limitations notated so management can plan and budget accordingly.

From an IRR perspective, back testing is only possible in some cases. In addition, it must be emphasized that the assumptions in an ALM model are necessary to isolate interest rate risk, and, therefore, they cannot be perfectly replicated in actuality.