Regulatory Compliance : IRR Exposure Limits

IRR exposure limits define the Board’s tolerance for interest rate related negative performance variability, as measured in defined tests.  As a regulatory compliance input, IRR exposure limits are designed to protect the deposit/share insurance fund from potential loss across a wide range of hypothetical interest rate scenarios.  In this application, IRR exposure limits are a vital element of the asset-liability management (ALM) activities of all financial institutions.

All IRR exposure limits have two definitional dimensions (see Exhibit 1 below):

  • They must expand at least proportionately as IRR test scenarios diverge from Base Case IRR limits.  For example, if the IRR exposure limit defined for a +/-100 bp rate shock is -10%, then the IRR exposure limit for a +/-200 bp must be at least double that (for example -20%).
  • The negative performance influences of embedded options, which increase risk as interest rates diverge farther from Base Case, must be recognized by non-linearly widening IRR exposure limits.  For example, if the IRR exposure limit defined for a +/-100 bp rate shock is -10%, then the IRR exposure limit for a +/-200 bp must be more than double that (for example -25%).

A simple spreadsheet for creating IRR exposure limits that include all dimensions of good design is available free from MPS (contact McGuire). 

When setting IRR exposure limits, keep in mind that they are based on extreme types of risk tests, not actual operating conditions.  The key point is that hypothetical IRR exposures are depicted, not expected exposures.  Thus be sure to define your institution’s IRR exposure limits wide enough to accommodate extreme test outcomes.  This is no time to be shy or too conservative!

In addition, recognize that IRR exposure limits are compared to the estimated exposures produced by an ALM model.  For IRR limits to be a valuable reference point, the ALM model used must be a precise predictor of balance sheet IRR.  This requires that the model’s underlying data, category set up definitions, contractual inputs, behavior assumptions, and reporting are correct.  If an ALM model has not been independently verified recently, this must be done to ensure model accuracy. 

A final issue is that the IRR testing environment and balance sheet growth assumptions should be stable over time (preferably a static balance sheet is used for earning at risk analyses).  This allows IRR exposure limits to better match the IRR analyses produced over time, facilitating trend reviews.