Implementing CECL: The WARM method
The Financial Accounting Standard Board’s new Current Expected Credit Loss (CECL) model for recognizing credit losses is a significant reporting change for financial institutions.
The implementation date is drawing near. Except for the large SEC filers who have already adopted CECL, the new standards are set to become effective for years beginning after December 15, 2022. If you’re a calendar-year-end institution, you’ll need to adopt on January 1, 2023, and start reporting this on call reports, beginning with the March 2023 report.
CECL timeline
Regardless of the methodology or approach you take to CECL, there are going to be very real benefits to getting your calculation in front of key stakeholders in advance of implementation. The more people you give the opportunity to review and the more process documentation you put in place, the smoother that initial implementation process is going to go.
What your financial institution should be doing in calendar year 2022:
- Finalize initial CECL calculation
- Run calculations parallel
- Have CECL calculation reviewed by key stakeholders (management, board, auditors)
- Calibrate model accordingly
- Verify new data activity
- Document methodology and controls
- Measure the impact as of Dec. 31, 2022, and record adjustment as of Jan. 1, 2023
Choosing the WARM method
Organizations can choose from various measurement approaches to estimate expected credit losses. In working with financial institutions, we’ve seen the weighted-average remaining maturity (WARM) approach gain a lot of traction.
We surveyed financial institutions in November 2021. At that point, 43% of respondents were planning to utilize the WARM method, 31% were planning to use the SCALE methodology put out by the Fed, and 15% were planning to use the probability of default method.
Figure 1: Anticipated CECL methodology, Wipfli survey of financial institutions, November 2021
One significant advantage to WARM is that it correlates to how most institutions are currently calculating their allowance — using an average annual historical loss rate. The WARM CECL methodology allows you to keep that framework and continue to use that same average annual loss rate that you’re calculating today. (Most other CECL methodologies require the calculation of a lifetime loss rate.)
Where the change comes in with the new CECL WARM model is in how you now need to project out how your current loan portfolio is expected to pay down over time.
WARM method overview:
- Calculate an average annual loss rate
- Estimate future outstanding balances based on contractual maturities and estimated prepayments
- Multiply the average annual loss rate by the estimated outstanding balance at each future reporting period
- Add up the estimated losses for each period
WARM method example
Future Year End | Estimated Paydown (000s) | Projected Balance (000s) | Average Annual Loss Rate | CECL Loss Estimate (000s) |
---|---|---|---|---|
2021 | 234,000 | 0.20% | 468 | |
2022 | 75,027 | 158,973 | 0.20% | 318 |
2023 | 63,835 | 95,138 | 0.20% | 190 |
2024 | 43,910 | 51,228 | 0.20% | 102 |
2025 | 51,228 | 0 | 0.20% | 0 |
1,078 |
Figure 2: WARM sample calculation overview
In this example, we have a loan portfolio with $234 million outstanding as of the end of 2021. For this loan pool, we’ve calculated that the average annual loss rate is 20 basis points. (The first row of the table is how most financial institutions are doing their allowance calculations today — taking the current loan balance x average annual loss.)
But under CECL, we need to forecast how that $234 million is going to pay down over time. Here, we’re determining that we expect that balance to be down to $159 million in 2022, $95 million in 2023 and, finally, by 2025 we’re expecting that entire loan portfolio to be paid down.
To make this a lifetime loss calculation, as required by CECL, we take the expected balance at the end of each year x the average annual loss rate. The sum of those products becomes our lifetime loss estimate.
Historical lifetime loss rate = 1,078 / 234,000 = 0.46%
Tips for CECL readiness
As you prepare to implement your CECL approach, you’ll need to make some key decisions and assumptions in areas like these:
1. Estimating paydown
The primary challenge is trying to calculate and support how that loan portfolio is expected to pay down. Some common techniques:
- Using asset liability management data (possibly setting growth rate to 0)
- Analyzing historical paydown percentages (requires access to historical data)
- Assuming even paydowns over WARM with prepayment factor applied
2. Qualitative factors
The allowance for credit loss (ACL) calculation under CECL will need to consider qualitative factors. Essentially, you’ll begin with your historic loss rate then adjust +/- for current and forecasted economic conditions. Financial institutions should be aware, however, that the impact of conservative qualitative assumptions will be magnified under the WARM method.
3. Historic loan data
Some organizations may struggle to obtain historic loan data. One resource we’ve seen work is to consider loan data that has been provided for asset-liability management reports. Alternately, you may be able to piece this together from historic monthly board reports.
4. Forecasting
CECL requires entities to make reasonable and supportable forecasts of expected losses. This is generally considered an additional component of the analysis, beyond regular qualitative factors.
Supporting forecasting adjustments can be challenging. Many entities are attempting to correlate key economic indicators to loss history to help develop and support forecasting adjustments. Example indicators include:
- Unemployment data (national or regional)
- Consumer confidence index
- Housing price index
5. Unfunded commitments
CECL requires entities to estimate expected credit losses for off-balance sheet credit exposures over the contractual period. Credit losses don’t need to be evaluated if the commitment can be unconditionally cancelled by the issuer. Entities should consider utilization estimates in this analysis.
Loss rates estimated on unfunded commitments are classified in other liabilities (different than the ACL reserve on outstanding loans, which is an offset to loans). Our advice: Don’t underestimate the potential impact of unfunded commitments on the CECL analysis.
Wipfli’s Excel-based CECL solution
Wipfli has developed an Excel-based CECL solution that is simple to populate. The spreadsheet tool requires no special software or ongoing subscription fee. It is designed so that financial institutions can fulfill CECL accounting and regulatory requirements — including paydown assumptions, forecasting and unfunded commitments.
For most organizations, the timeline to implement will be less than one quarter. Designed as a one-time expense, your investment would include initial consultation and setup support from Wipfli.
We believe most organizations will be able to continue utilizing the tool without additional support or expense — however, we will be available if future needs arise.
Learn more about the model, or watch our recorded demo.
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