Many small community banks have yet to make their final decision regarding CECL implementation. Although there are many potential solutions to calculating the ACL, small banks seem to gravitate toward the “Weighted Average Remaining Maturity” (WARM) or “Scaled CECL Allowance for Losses Estimator” (SCALE) methods.
While the WARM method has the “incumbent” advantage, the SCALE method solves many of the shortcomings of WARM and might be a better fit for some institutions. To understand how SCALE might be more effective than WARM, it is best to evaluate the starting point for each method.
Note: The outlines below are meant to be high-level descriptions of each method – but not complete descriptions. Each method comes with nuance and complications that may not be highlighted below.
In general, the WARM method starts by aggregating actual historical loss rates for the bank’s (or a peer group’s) history and applying a ‘maturity factor’ to that number followed by a qualitative approach.
SCALE builds the basis of the ACL calculation off other peer bank’s existing reserve rates (assuming these institutions are CECL-live) and applies qualitative adjustments based on historical losses and other items.
The difficulties with WARM are well understood. Most small community banks don’t have loan losses in recent history so they’re required to look as far back as the 2008 Financial Crisis to get any meaningful result. In some cases, even going this far back doesn’t create a material loss basis for the bank due to its tight underwriting and lending practices. Not to mention that the bank’s portfolio at that time was vastly different than it is today. All these hurdles boil down to a few unfortunate truths for a WARM deployment:
The reliance on qualitative factors will continue to dominate the reserve calculation.
The bank’s ACL will not have a quantitative link to its portfolio behavior – either on a historical or pro-forma basis.
Management will continue to spend time, money, and other resources defending a calculation that they have very little quantitative basis for supporting.
SCALE comes with its own shortcomings but provides at least some basis for addressing the issues above. Because the starting point for SCALE is existing ACL rates as calculated by larger institutions, bank management can reduce the magnitude of the qualitative framework within their reserve calculation. Why? Because the larger institutions, in filing their reserve calculation, will have evaluated their own losses, applied their own qualitative framework, and considered their own forecast – minimizing the need to go through all these same steps yourself. While it is true that SCALE reserves don’t often align with historical losses (just as with WARM), most of the difference should be due to items specific to your institution (for instance, you just hired a new loan review firm) and should be easily explainable and defendable.
The difficulties with SCALE tend to pertain to peer selection and the appropriateness of the peer banks’ portfolios to your own. The need for community banks to address this question should not be ignored, but there are simple and auditable solutions for this (unlike the qualitative adjustments required for WARM). Invictus’s upSCALE tool allows for complete custom peer selection and provides portfolio information for each of the peers that you wish to select or exclude. This provides an audit trail for the eventual final calculation of your bank’s ACL.
The “historical adjustment” (as it is dubbed by the Federal Reserve in SCALE) should also not be overlooked. There are significant drawbacks to making an undefendable historical adjustment. Even more complicated – what if you must make a negative historical adjustment? The regulators will likely be triggered by this, and who wants more examiner questions?
So what can be done? Fortunately, all this data is readily available in public datasets (the FFIEC collects and maintains this data via quarterly Call Reports). Navigating the data may prove challenging, but here again Invictus can provide a solution. We’ve aggregated and stored this information in our databases, and upSCALE provides you with an easy and intuitive way to dig through your peer group’s historical losses so you can make the most informed decision possible with respect to the historical adjustment. Finally, since most of the data and analysis pertaining to SCALE is publicly available and generalized – the cost tends to be lower than an outsourced WARM solution.
You can get started with SCALE today with Invictus. Take advantage of our free trial period to see if the solution is right for your bank.