CECL: Remaining Life Method

September, 2018

In order for an institution to have a smooth CECL implementation, it is important that they are either in the “Scenarios & Modeling” phase (or beyond) or are taking the proper steps to soon be in this phase.

The key decision in this phase is which methodologies to explore and select for the various loan pools. The methodology an institution selects will have a significant impact on the amount of work required to gather the proper data, develop processes and develop the nature of the qualitative (Q) factors for each loan pool. Complexity is not a requirement. Less complex models are acceptable under the standard as long as institutions can demonstrate that they have adequately considered the relevant factors that impact their credit losses and that the requirements under ASU 2016-13 have been met.

Choosing a method for each loan pool is probably going to be a multiple-step process. An institution will need to narrow down the options to a limited number of methods based on the characteristics of a given pool and then understand and document how each pool reacts to various methods. This “shocking” will help Audit Committees, Boards of Directors, auditors and regulators gain comfort that proper due diligence was performed in selecting the method(s). An institution cannot simply select a method based on which approach requires the lowest level of allowance; however, they should evaluate the reasonableness of the outcomes of various methodologies and factor those into their decisions.

There are several methods that may be acceptable models under CECL such as (but not limited to): the cumulative loss rate (also known as snapshot), vintage loss rate, migration analysis, probability of default/loss given default, discounted cash flow, remaining life, etc. In this article, we will discuss the remaining life method.

The remaining life method is viewed as one of the practical methods that smaller and less complex institutions can use as a starting point for CECL. Following are the steps for this method:

  • Calculate an average annual loss rate for the loan pool (which is essentially the same average annual loss rate used by many today). The institution will need to consider the same factors it currently does to determine the look-back period and the weighting it places on each year when it calculates the average annual loss rates.
  • Estimate the outstanding pool balance at each subsequent reporting period, which is probably going to be more challenging and may require new processes. Balloon payments will need to be treated as payoffs, prepayment estimates will need to be considered and expected future originations will need be to be excluded.
  • Multiply the average annual loss rate by the current and each projected report balance of the loan pool and sum the results to derive the expected lifetime loss estimate of the pool.
  • Like existing incurred loss methods, perform additional analysis of Q factors to estimate the impact of current conditions. Additionally, analysis will need to be done to come up with reasonable and supportable forecasted changes that could impact lifetime losses. Institutions can apply the Q factors to the calculated loss amount or they could adjust the average annual loss rate for each future reporting period based on the forecasted changes in expected losses. Either way, the institution will need to support and document the judgments it uses to determine the appropriate Q factors.

An example calculation is shown below:

Fact pattern and assumptions – calculate the allowance for credit losses as of December 31, 2020. This is a middle-market residential loan pool for a specific geographical region with a current amortized cost basis of $15 million and an average life of 7 years, which includes estimates for prepayments. Management has reasonably forecasted (and supported) that real estate values will decrease and that the unemployment rates will rise within this geographic location over the next two years. Management believes that they cannot reasonably forecast beyond a two year period. Management has determined that a .30% qualitative adjustment is appropriate to account for both current conditions and reasonable and supportable forecasts.

(Dollars below are in 000’s)

CECL banking table

As you’ve probably already noticed, this methodology appears to be a relatively easy CECL methodology and looks very similar to existing credit loss models, but there are some critical differences that must be considered before choosing and adopting this method. To that end, careful consideration and attention needs to be paid relating to how much time, effort and cost there will be to develop processes necessary to reasonably project future outstanding pool balances as well as supporting and documenting Q factors and related adjustments. For developing the projection of future outstanding loans pools, institutions should consider looking into leveraging the data already gathered for its asset and liability management systems. This method is less precise in nature compared to some other methods and therefore it may lead to higher allowances compared to other methods under certain circumstances.

For a refresher of our previously prepared timeline and example calculations for the open-pool cumulative loss-rate method and closed-pool vintage loss-rate method, you can visit BNN’s CECL toolkit on our website.

The professionals in BNN’s financial institutions practice are dedicated to remaining current with the regulatory and accounting trends impacting our clients, and to keeping our clients informed of those trends and how they might impact their businesses. Should you have questions about CECL or the implementation systems and procedures in preparation for it, please contact your BNN advisor at 1.800.244.7444.

Disclaimer of Liability: This publication is intended to provide general information to our clients and friends. It does not constitute accounting, tax, or legal advice; nor is it intended to convey a thorough treatment of the subject matter.