Market risk—the risk that a sudden change in market prices could affect earnings or capital—can be difficult to measure, but that doesn’t make it any less important. One way of capturing a bank’s exposure to changing interest rates is Earnings At Risk (EAR) analysis. EAR models can be quite complicated, but they also allow for great flexibility.

Earnings At Risk (EAR) models may be likened to financial calculators or spreadsheets in which principal amounts are multiplied by interest and by the time period to equal interest income and interest expense. Besides interest revenue and expense, EAR also takes into account the effects of interest rate changes on noninterest income (origination fees, penalties) and expense (filing fees, appraisal charges, credit check charges) in order to generate a bottom line net income figure.

EAR models permit changing all the variables that determine interest income and expense (such as outstanding balances, interest rates received or paid on those balances, and the time periods the rates are received or paid on the income balances). Consequently, EAR methodologies are able to capture repricing risk, basis risk and yield curve risk . Because there is so much variation in what you might see in an EAR report, it is important that you ask for specific details about the summary information you receive.

It is not necessary that you be able to construct an EAR model from scratch, but this lesson should provide enough expertise to allow you to interpret EAR output and ask the right kinds of questions about the assumptions that underlie it.

Lesson Objectives

After you complete this lesson, you should be able to:

• Understand the basic technique for constructing EAR models
• Interpret EAR output to assess the exposure of your bank’s earnings to interest-rate changes.

Use the following text links to navigate through the lesson material:

Earnings at Risk (EAR) Calculations
Earnings at Risk (EAR) Summary Reports

• Example 1
• Example 2
• Example 3

Once you have reviewed the EAR model lesson, complete the Try This at Your Bank exercise: EAR Models.

Earnings at Risk (EAR) Calculations

Earnings At Risk (EAR) models simulate various possible interest rate scenarios to determine their potential effect on earnings. If most of the likely scenarios result in earnings ratios that are considered acceptable, then interest rate exposure is probably low. Scenarios that result in unacceptable changes in earnings can be studied more closely to determine possible hedges or solutions.

A typical EAR model might look at dozens of different scenarios over time spans as long as several years. To make this discussion more concrete, the worksheet below shows the behind-the-scenes calculations for a simple EAR model that includes nine interest-rate scenarios over only one quarter. In particular, it considers what happens if three-month Treasury-bill rates settle at various values between 2 percent and 6 percent, in 50-basis-point, or .5 percent, increments.

For more information about the EAR model calculations below, move your mouse pointer over the chart.

Once you have reviewed the EAR model lesson, complete the Try This at Your Bank exercise: EAR Models.

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Earnings at Risk (EAR) Summary Reports

EAR models will usually include several quarters’ worth of projections for changes in several types of interest rates (short-term rates, long-term rates, risk spreads, etc.). As the quarters proceed, income and expense are calculated based on assumed interest rates and the bank’s evolving balance sheet. The analysis may be done for a variety of hypothetical interest rate changes, relative short- and long-term interest rate changes, bank growth trends, bank strategies and customer behavior.

Generally, the EAR reports provided to management will not include all of the intermediate calculations. The entire analysis may be presented as a few simple lines on a graph or a few cells in a summary table.

Frequently in the summary, you will see analyses for 100 to 300 basis point changes in interest rates (one to three percentage points). Almost always, you will see an analysis for a 200 basis point (2 percentage point) rise and fall in interest rates, as recommended by the federal banking agencies. The interest rate changes may be modeled as a one-time up or down bump in rates or a gradual rise or fall in rates—once again, a federal banking agency recommendation.

This chart shows Insights Bank’s net interest income and net income over the next year under assumed interest rates changes ranging from -300 basis points (-3%) +300 basis points (3%). Note that 100 basis points equals 1 percent.

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EAR calculations may also be summed up in a couple of numbers, such as most likely Return On Assets (ROA) or a confidence interval on a summary report. Though Example 2 is not built from Insights Bank and Trust data, it shows an alternate format for a summary EAR report. An example of such a report is provided here:

Note the confidence interval information for both Treasury rates. To better understand the confidence interval, compare it to the likely case. If you think about the most likely and confidence interval percents on a number range, there are possibilities between the two amounts. The confidence interval shows one end, and you can be 90% sure the interest rate will be at that point or closer to the most likely case. If the confidence amount is a higher number, then everything in between the most likely case and confidence interval would be lower than the confidence amount. The confidence amount indicates "higher" or "lower than" depending on which way would move closer to the likely scenario. In this example, Treasury rates show the high-end rate. The ROA shows the low-end rate.

In the first quarter ahead, we can be 90 percent confident that the three-month Treasury rate will be under 5.3 percent, and under 7.2 percent for the 10-year Treasury rate. The last columns indicate that it is 90 percent probable that the return on assets will be more than .12 percent.

The same information may also be provided in graphical form, tracking the most likely values and confidence bounds over time. This line graph (Example 3) shows the same data as the table in Example 2.

For three quarters ahead, a 4.3 percent interest rate is the most likely case for the Return on Assests (ROA), and we can be 90 percent confident it will be under 5.7 percent.

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Assumptions: “Base Case” or Most Likely Scenario

Because EAR models differ dramatically from institution to institution, the report you receive may give only some of the information or include other values. The important thing to remember is that all of the projections are based on assumptions about the behavior of the balance sheet under different conditions and the probabilities of these conditions occurring.

EAR models provide forecasts based on assumptions about what will happen to interest rates and how the bank will respond. The best way to assess the output from such a model is to ask a lot of questions about the underlying assumptions and the level of confidence associated with the forecast. Though you will not be responsible for selecting or defending the assumptions surrounding an EAR model, you need to verify that the creators of these models have thoughtfully considered all of the underlying issues.

Earnings at Risk summary information may be compared to a base case analysis or an analysis in which the current rate environment continues into the future, and other factors that may impinge on the bank’s net income remain unchanged or are allowed to change by prescribed amounts, that is, a continuation of past trends. Most of the time, the base case will correspond to the asset and liability committee's assessment of the most likely case. Sometimes, however, some other criterion may be used to select the base case. For example, it might simply represent the situation in which interest rates continue at their current values indefinitely.

A good question to ask the committee is how they constructed their base case and, if it is not the same as the most likely case, what their rationale was for using it. A most-likely case scenario is similar to a best guess or consensus view of how the future is expected to unfold. Besides this basic information, the summary might include analyses of what might occur if the bank took certain actions in response to rate rises and falls.

The best way to assess the reliability of the output of EAR models is to ask questions about the assumptions to see if they seem realistic and cover all possibilities. Also, pay special attention to the worst-case scenarios, as shown by the confidence intervals. Although unlikely, worst-case situations often result in serious problems for banks if they occur. Management should always be thinking about new ways to hedge against these extreme situations and restructure the balance sheet to narrow the confidence intervals.

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