‘WARM’ing Up: Pros and Cons of Using WARM for CECL Implementation

By Kylee Wooten

As the Current Expected Credit Loss model’s effective date for SEC filers nears, the pressure to find the right CECL methodology is on. The remaining life—also known as Weighted-Average Remaining Maturity, or WARM—methodology, first introduced in February 2018, is one of the newest methodologies on the scene. The methodology has been building steam in recent months, specifically for community institutions that are seeking simpler, more practical methodologies for implementing CECL than those being used by larger institutions.

While the WARM methodology has some similarities to other CECL methodologies, there are also significant differences that are important to address if your institution is considering applying this method.

When should you use the remaining life methodology?

The WARM methodology, while not appropriate for all institutions, can be applicable in some circumstances. Data has consistently been one of the biggest challenges for financial institutions transitioning to CECL. For institutions struggling with gaps in their data or lacking in loan-level data, the WARM method may be a viable option. Since the WARM method uses an average annual charge-off rate, institutions are able to use aggregated data from Call Reports or peer data.

“While we might prefer something that’s a little bit more robust, we’re asked to do this in a reasonable manner, and for an institution that doesn’t have a bunch of quality assurance analysts on staff to be able to do this, I think that the WARM method can be a viable option,” says Jared Mills, a senior consultant at Abrigo, which offers two American Bankers Association Endorsed Solutions for CECL. “This methodology has some upsides to it compared to some of the more historically driven approaches.”

One of the advantages of WARM is the fact that it is forward-looking, similar to the discounted cash flow method, for example. However, the WARM method takes a more simplistic way of applying loss rates. It requires less data than other methodologies, which can be beneficial for institutions that don’t have enough loan-level data and need to use pool-level data.

Institutions and segments best-suited for the remaining life methodology

No CECL methodology is a one-size-fits-all solution, and the WARM methodology is no exception. Since some components of this methodology seem more simplistic than other methods, it may be subjected to more scrutiny than others. It’s important to ensure that your institution or portfolio segment is suited to use the WARM methodology.

Less complex portfolios or segments. The WARM method is not as sophisticated as other methods for calculating CECL. Therefore, WARM is most applicable to less complex portfolios or segments. This includes institutions that lack significant loan-level data or loss history.

“It’s going to be critical for each institution to define what a ‘complex’ portfolio or segment is, as it pertains to them,” says Baker Eddraa, senior manager for advisory services at Abrigo. “This should be well-documented and supported in order to be able to defend this methodology election to your auditors and regulators.”

Segments with potential data limitations. Data limitations, both operational and numerical, are a primary driver for employing the WARM method. If an institution recently went through a conversion and had its data purged, this could be an example of an operational limitation. A numerical limitation would include situations in which an institution lacked statistical data or had not observed enough historical losses to derive meaningful loss rates.

Immaterial acquired portfolios. Even if this methodology isn’t a fit across the board, it may make sense for a particular segment within the portfolio. For example, the WARM methodology can offer a temporary solution for institutions that have acquired an immaterial portfolio. Oftentimes, these institutions may not have all the data necessary to perform one of the other methodologies on a less material acquired portfolio. In the interim, institutions can use Call Report data to help with CECL compliance until the institution is able to gather all of the necessary data components.

New lines of business and de novos. If the financial institution has a new product, a new line of business, or, perhaps, the institution itself is brand new, then it may not have sufficient data for more robust methodologies. In these situations, the WARM methodology can be a more fitting method than those that require a large quantity of loan-level and historical data. This is especially true for de novo banks. These banks have limited loan information and can leverage the WARM method and be more reliant on peer data.

Steps to building a WARM calculation

There are several steps institutions have to take in order to conduct the WARM method:

Determine the remaining life. One way to go about building a remaining life projection is through an attrition analysis, where the institution would observe and evaluate exit events and develop an annual percentage to represent the frequency of loans exiting the portfolio. The analysis would be completed on a quarterly basis, and then converted into an annual percentage to determine the attrition rate. This analysis helps determine the average life of a particular loan pool that the WARM method would be applied to.

An attrition analysis helps anticipate how long a portfolio would take to runoff. Some exit events that an institution would track in this analysis include: payoffs, matured loans, renewals (per the guidance), and charge-offs. A benefit to the attrition analysis is that it captures—and adjusts for—prepayments as part of the payoff factor.

To calculate the estimated remaining life, the institution would take the inverse of the annualized attrition rate (1/Annual Attrition Rate).

Calculate and apply loss rates. It’s recommended to calculate an annual or quarterly net loss rate “through-the-cycle.” In other words, deriving a long-running average that accounts for a full economic cycle, including good and volatile economic conditions. The long-running average allows for compliance with the guidance’s terms of reverting to historical losses. Call Report data and peer data can be used to produce this loss rate.

Adjust for reasonable and supportable forecasts. In this approach, for each quarterly line item of the remaining life schedule, adjustments will be made based on forecasted conditions. Economic indicators, such as unemployment, will inform adjustments. This will assess economic variables against trends to determine possible correlations and predictors of losses. This assessment should be done at the segment level, since each segment might have different factors that influence it, such as region, environment, risk profile, etc.

“The factors used should be based on mathematical results, but they should also make sense intuitively to the institution. It should pass the smell test,” says Mills.

And while using economic indicators to inform adjustments is important, Mills warns institutions to not go overboard. Make sure that the economic indicators you choose are reasonable. “For example, we might be able to prove we’re correlated to precipitation if it’s an ag portfolio, but how reasonably can we predict the weather is kind of the conundrum there,” Mills explains.

After forecasting, reversion will help inform how an institution reverts to its long-run historical averages. According to the guidance, there are several ways to revert, including immediate reversion and straight-line reversion.


While the WARM method is certainly not the most robust methodology, it can be a fitting choice for smaller, less complex banks or segments within the portfolio. The WARM method is a simpler model compared to others and is quick to execute and implement, and for institutions lacking in loan-level and historical data, it has minimal data requirements. However, it does have its share of shortcomings, such as how it can be punitive to longer-term portfolios. A key takeaway for financial institutions considering the WARM methodology is to keep in mind that it can be subjected to scrutiny and is not a good fit for sophisticated portfolios.

“If you elect to implement the WARM methodology, where your loan level data is available, sensible, and statistically relevant, auditors will be challenging your election, so be ready to defend it—that’s the piece that I’d be the most concerned about,” Eddraa notes. “Why would you use a simple approach if you have relevant data that allows you to implement a more sophisticated, forward-looking approach such as discounted cash flow? Be sure to fully document why you’re electing the WARM methodology.”

Whether a financial institution is considering implementing WARM or any other CECL methodology, it’s important to challenge your models. Consider how different methodologies can be applied to various segments of their portfolios and don’t simply rely on one model. While CECL is imminent, it is still subject to changes, and much is still unknown until it goes into effect for SEC filers in the first quarter of 2020. Being vigilant in testing and challenging various models will be critical for a successful transition and implementation of CECL.

Kylee Wooten is a content marketing manager at Abrigo, which offers two ABA Endorsed Solutions for CECL.