How to assure examiners your IRR is being managed effectively – Part 2

In a past article published this spring, I pointed out that there are better alternatives when considering A/LM models for managing Interest Rate Risk (IRR) than the traditional Net Economic Value (NEV) model. In this, the final article on this subject, I will provide further discussion on the advantages Earnings at Risk (EAR) has over NEV as an effective method for measuring and managing IRR.

First let’s review the four points I raised in my article last spring.

Point 1:

To assure examiners that a credit union is in compliance with IRR regulations, credit union managers need to be able to show that their credit union:

• Is using an independently validated IRR measurement system
• Has management and a board that is trained in how their IRR model works and is using it effectively
• Consistently applies the IRR model in on-going operations and planning

Point 2:

IRR has some basic concepts: (1) IRR is the risk to earnings and capital arising from movement in interest rates; (2) IRR arises from the difference between the timing of rate changes and the timing of cash flows; and (3) in credit unions, the primary issue driving IRR is their long-term loans or long-term investments.

Point 3:

NCUA regulations are clear – there is no one IRR model that should be used to meet IRR regulatory requirements. Indeed, there is more than one IRR measurement model that a credit union can use. Unfortunately, many examiners are steeped in the belief that proper IRR modeling should utilize NEV.

Point 4:

NEV has many weaknesses when used to measure IRR risk in credit union operations. NEV applies a present value calculation against future cash flows to: (1) discount the value of assets; (2) discount the value of liabilities; then (3) subtracts the value of liabilities from the value of assets to arrive at Net Economic Value. Conceptually, this is the liquidation value of a financial institution. NEV is an effective concept when used in some financial applications, but it is a poor measure of a credit union’s IRR. NEV requires: (1) maturities of assets and liabilities; (2) market prices of assets and liabilities; and (3) applicable discount rates to use when valuing assets and liabilities. We can easily see the shortcomings trying to apply NEV to a credit union: (1) there are no maturities in non-maturity deposits (so, many NEV models use an arbitrary number); (2) there is no market price for checking accounts or savings accounts (again, many NEV models guess); (3) there is no market where one can “purchase” a credit union’s core deposit accounts; so (4) there is no way to establish a discount rate where there is no market place. Since so much of NEV is based on estimations and guesses for establishing discount rates and market prices, NEV is not an effective model to determine a credit union’s exposure to IRR.

Earnings at Risk is a better model for measuring and managing IRR

A better IRR management model is based on Earnings at Risk (EAR). NEV (sometimes labeled as Value at Risk) calculates the “liquidation value” of the balance sheet to be applied in the event of the sale of an institution. EAR, on the other hand, calculates the “on-going concern” value of the income statement. EAR is an operational measure and is a far better IRR model for credit unions especially when compared to NEV.

EAR does not rely on assumptions to the extent that NEV does and therefore has greater value for CEOs and CFOs who are trying to forecast the effects potential changes in interest rates will have on profitability and equity. Effective EAR models project cash flows and impacts on profitability using actual payments coming from individual loans and investments in a credit union’s balance sheet. Better EAR models also take into account additional factors that affect profitability such as fee income, maturing CDs and operating expenses. EAR A/LM models assure validity by holding constant assets and liabilities in a balance sheet so as to measure the actual IRR in the current balance sheet. Once the “base” IRR is established, an EAR model can also be used for multiple simulations where management can vary inputs and view the impacts each change or combination of changes has on IRR, income and equity. Simulations may include: (1) increasing or decreasing loans and/or investments; in combination with (2) increasing or decreasing deposits (specific types or general) including changing the mix of deposits. All these simulations can be run using different rates of interest under consideration for deposits, loans, and so forth.

It is important to note, that all A/LM models should include the effects of interest rate “shocks” that measure the impact possible changes in interest rates will have on balance sheets and profitability. Efficacious models measure the impact of two distinct possible rate shock scenarios: (1) an immediate, extreme (typically 500 basis points) increase or decrease in rates; and (2) small but sustained changes in interest rates (sometimes referred to as Stepped Shocks).

A/LM modeling policies should include acceptable limits to risk relating to IRR. It is of note that there are now a handful of A/LM modeling providers that can help set A/LM limits using stochastic methods which are far better than using arbitrary or traditional methods.

Once examiners understand the weaknesses in NEV and the strengths in statistically-validated and tested EAR models, they almost always accept EAR as a better alternative for measuring and managing IRR. Furthermore, since EAR provides a model that boards, CEOs and CFOs can more effectively use in their risk management and planning processes, regulators frequently become advocates of EAR.