Is Your Credit Union Ready for the “S” in Its CAMEL?

By Stephanie Evans

By Dennis Child, Research Specialist, TCT Risk Solutions, LLC

CAMEL is a term coined by the National Credit Union Administration and many state credit union regulators to rate the financial and regulatory compliance performance of each credit union under their supervision.  Most everyone in the credit union industry knows what each letter represents in the term “CAMEL”.  For those who might need a refresher: “C” stands for Capital Adequacy, “A” is for Asset Quality, “M” is for Management Capability, and “E” is for Earnings and Liquidity.  A credit union’s CAMEL score is considered by many to be a picture of its management performance and financial health.  A CAMEL score of 1 is the best possible; a score of 5 is considered significantly substandard. A credit union’s CAMEL score is considered an important barometer when judging a credit union’s overall performance.  As such, regulators, boards, and managers read a lot into a credit union’s CAMEL score.

Now, NCUA is considering adding an “S” to the end of their existing CAMEL examination rating system.  The “S” stands for Sensitivity.  More specifically, Interest Rate Sensitivity.   For decades, NCUA and most state credit union regulators have been reviewing credit unions’ processes for managing Interest Rate Risk (IRR) and the potential impacts interest rate changes might have on equity.   Adding “S” to CAMEL would formalize a process already in place but will bring Interest Rate Risk management to a prominent spot in a credit union’s primary performance score.  Examiners will be placing more pressure on credit unions to demonstrate they are addressing their sensitivity to interest rates in accordance with regulations and good management practices.  Clearly, it will be more important than ever that every credit union have systems and models in place to manage their Interest Rate Risk effectively. 

Effective Interest Rate Risk management models should serve several purposes for credit unions: (1) they should be used by management and boards to assure changes in interest rates will not dramatically harm their credit union; (2) they should be integrated into the credit union’s short and long term planning; (3) they should help assure regulators that management is complying with all regulatory expectations in terms of risk management – particularly Interest Rate Risk (IRR).

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

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

Many credit union managers have difficulty understanding and explaining their respective IRR model.  Interest Rate Risk concepts and models use stochastic methodology but managers should be able to answer examiners’ basic questions as to how their model works and why it complies with regulations.  Sadly, examiners sometimes are attached to one particular IRR model and may have difficulty understanding IRR models that are different from what they have been indoctrinated in.  So, let’s start with the basics: (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; (3) in credit unions, the primary issue driving IRR is their long-term loans or long term investments.  Managers and examiners understand these basics of IRR.  What drives much of the disagreement between managers and examiners is the proper IRR model that a credit union should use.  NCUA regulations are clear – there is no one IRR model that should be used to meet regulatory IRR requirements.  Friction between examiners and managers is exacerbated when managers cannot effectively explain how their IRR model works.

Indeed, there is more than one IRR measurement model that a credit union can use.  Unfortunately, many examiners are still steeped in the belief that proper IRR modeling should be based on Net Economic Valuation (NEV).  Dr. Randy Thompson of TCT Risk Solutions LLC, many other financial institution experts, and this author have long held that NEV is an ineffective model for credit unions to use to manage Interest Rate Risk.  A far better IRR model is based on Earnings at Risk (EAR).   NEV or Value at Risk calculates the “liquidation value” of the balance sheet to be applied in the event of the sale of an institution. EAR calculates the “on-going concern” value of the income statement.  EAR is an operational measure and is far superior to NEV as it applies to credit unions.

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 (sometimes erroneously referred to as Net Equity 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. One should easily be able to see the shortcomings trying to apply NEV to a credit union: (1) there are no maturities in non-maturity deposits (so, many NEV models and regulators guess); (2) there is no market price for checking accounts or savings accounts (again, many NEV models and regulators 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 a questionable model at best to use when it comes to determining a credit union’s IRR exposure.  

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.

With the right A/LM models in place (and proper usage)  credit union managers have no reason to fear the “S” in their CAMEL.

TCT Risk Solutions, LLC, a CUSO owned by credit unions, utilizes EAR in its A/LM (IRR) modeling tools.  For more information, visit the TCT website: www.tctrisk.com.