CECL Methodologies Series: Cumulative Loss Rate
In a recent article, CECL: Getting Started, we looked at setting specific milestones to help guide management teams through the CECL implementation process. The first milestone we suggested was to investigate available CECL methodologies. In the next several articles, we will explore some of the different methodologies and their pros and cons, starting in this article with the cumulative loss rate methodology.
Overview
Most would agree that the cumulative loss rate methodology (“loss rate method”) is the simplest CECL methodology available to financial institutions. It requires the least amount of data and can be completed in a spreadsheet with relative ease, but it will be a significant change from the incurred loss model used by financial institutions today.
The loss rate method measures the amount of loan charge-offs net of recoveries (“loan losses”) recognized over the life of a pool and compares those loan losses to the outstanding loan balance of that pool as of a specific point in time (“pool date”). Loans in the pool at the pool date will have been originated at different times. Some loans may have only a few days remaining before they mature, while others may have been just originated and will have virtually the entire loan term to pay off. Since the loss rate method captures all of the material loan losses over the life of the loans in the pool, the pool date selected must precede the date of the CECL analysis (“reporting date”) by at least the same amount of time as the maximum loan term of the pool. For example, if we want to estimate a CECL allowance for loan losses as of 12/31/2017 (“2017”) and the pool consists of balloon notes with terms ranging from 3 to 5 years, the pool date used would be 12/31/2012 (“2012”) so that all of the loan losses on loans outstanding as of the pool date can be captured in the analysis.
How it Works
To estimate a CECL loss rate for the pool, management first identifies the loan losses recognized between the pool date and the reporting date for the pool and determines which loan losses were related to loans outstanding at the pool date. Continuing our previous example, let’s assume a financial institution recognized $3.5 million of loan losses on the loan pool between 2012 and 2017. After looking at the origination date of each loan with a loan loss, management determines only $2.8 million of loan losses were on loans actually outstanding as of 2012.
The loss rate method then divides the loan losses recognized on loans outstanding as of the pool date by the outstanding loan balance as of the pool date. Assuming the outstanding loan balance in our example was $120 million as of 2012, the initial CECL loss rate would be $2.8 million ÷ $120 million, or 2.33%.
The loss rate calculated above simply tells management that the loss rate on the 2012 loan pool was 2.33% of the 2012 pool balance. This gives us a starting point for estimating a CECL loss rate for the 2017 pool balance, but the calculated rate will need to be adjusted for qualitative differences in the current pool balance. Qualitative factors to consider will include many of the same factors currently used in the incurred loss methodology plus some additional factors that will be used to help forecast changes to the pool in the future.
Pros and Cons
As previously discussed, the loss rate method is the simplest methodology to develop an initial CECL loss rate. The only data required to complete a loss rate method includes:
- Pool loan balance as of the pool date.
- The date and amount of loan losses (charge-offs net of recoveries) between the pool date and the reporting date.
- The origination date of loans that had loan losses during the period.
While the loss rate method itself is relatively easy to calculate, typically much more effort must go into analyzing qualitative factors in the loss rate method than in other methodologies because the data used can be rather stale. (In the preceding example, the information used was 5 years old.) Changes in credit quality of the pool from the pool date to the reporting date are not captured in the methodology. Imagine using data from 2012, the tail end of the recession, to support an estimate of expected future losses in the 2017 loan pool, which presumably comprises higher quality loans. The 2.33% loss rate calculated in our example is probably too high for the 2017 portfolio and needs to be adjusted downward through qualitative factors. The question is: How much adjustment is needed? A lot of analysis will likely be needed to come up with a reasonable and supportable answer.
Another consequence of the loss rate method is that it will likely result in a higher CECL loss rate than other methodologies because of the imprecision used to come up with appropriate qualitative adjustments. Since it can be difficult to come up with supportable ranges for qualitative adjustments, management will likely have to err on the side of more conservative qualitative estimates, which logically ends up with a more conservative overall CECL estimate for the allowance for loan losses.
Pros |
Cons |
Relatively easy initial CECL loss rate calculation |
More analysis needed for qualitative (Q) factors |
Least amount of data needed |
Will likely result in a higher CECL allowance for loan losses balance |
Concluding Thoughts
Many institutions, especially smaller, less complex institutions, may strongly consider using the loss rate method to estimate their CECL allowance for loan losses because of its relative simplicity.Even larger institutions may consider using this methodology for insignificant loan pools. However, management teams must also weigh the cost of more complex analysis of qualitative factors that comes along with this methodology.
We will continue to look at other available CECL methodologies in future articles, but if you would like to discuss any or all of the available methodologies in more detail at any time, please contact Brett Schwantes or your Wipfli relationship executive, and we will be happy to set up an appointment with you!
For more information on CECL, please check out some of our recent articles:
Measuring Credit Impairment of Financial Instruments (Sept 2016)