Interest Rate Risk Management – What to Consider
By: Robert L. Hamby, CPA
Date: 12/17/09
Common goals for any asset liability management process are to monitor earnings growth and stability, equity growth and stability and provide risk management over interest rate risk, credit risk, liquidity risk and leverage. When your Bank considers interest rate risk management, what should you include in the process? The following describes some components to include in your interest rate risk management process.
The most important aspect of an effective interest rate risk management process is active board and senior management oversight. Your Asset Liability Management (ALM) policy should include responsibilities of both the Board of Directors and senior management. The ALM policy should establish appropriate risk limits that senior management should operate within. The risk limits should be monitored frequently with adequate systems for measuring risks.
The measurement system used should be robust enough to measure all of the institution’s risks, based on the financial instruments embedded within the organization. In the simplest of terms, an effective ALM Modeling system is merely a very powerful calculator. It relies on various source data as a starting point; but the primary ingredients to an effective interest rate risk model involve key assumptions by management.
Some of the key assumptions that should go into the interest rate risk model include:
- Prepayment assumptions for both loan and investment instruments. Most models use the standard OTS prepayment speeds for investment instruments related to mortgages, but management should also consider prepayment speeds on the loan portfolio.
- Growth assumptions should be reasonable based on historical patterns.
- Deposit betas are the change at which the rate on depository accounts moves in correlation to the change in the base rate. For example, a 100 basis point change in the base rate will change the rate on very sensitive depository accounts (i.e. money market accounts) by close to 100 points. For less sensitive depository accounts (savings accounts), a 100 basis point change in the base rate will only change the rate on the deposit account by a small amount. Deposit betas can be estimated using the institution’s history of rate changes in comparison to interest rate changes - commonly known as a regression analysis.
- Decay rates are the measure of the average life for depository accounts. These are difficult to measure as the measurement is based on customer behaviors. Decay rates can be estimated using historical information for an individual deposit category and determining the percentage of accounts that leave over a specified time period. The OTS has conducted many studies on decay rates. Various interest rate risk models use these OTS rates as an industry-wide median decay rate. Management should consider using decay rates in the interest rate risk model to make better predictions of financial results.
As is the case for any type of software used to perform calculations, the ALM model should be validated. The validation process is essentially an independent review of the concepts and calculations used in the model. Model validations are generally conducted by the ALM software vendor. They provide documentation of or certification of the integrity of the model. Management should obtain a copy of the validation for their records.
In order for management to effectively determine the accuracy of the interest rate risk model projections, back testing procedures should be performed. Back testing is the process of reviewing the projections of the ALM Model after the fact and comparing those projections to actual performance. Back testing should be completed periodically as a tool to help management adjust assumptions within the interest rate risk model in order to more accurately represent the performance trends of the institution.
Although many ALM models can be very complex, the level and detail of analysis depends on the size and sophistication of the institution.
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