Preparing for CECL: It’s Time to Tackle the Hard Part

The Hard Part: Preparing for CECL | Baker Hill

There certainly are several schools of thought as to what needs to be addressed in preparation for CECL. At this point in the game, implementing CECL is starting to become a reality. Most banks have started their preparations but come to a screeching halt when faced with tackling what is quickly becoming known as the hardest challenge of CECL: defining economic drivers.

My advice? Do the prep work and tackling the hard stuff won’t seem as intimidating.

Key Steps to Prepare For CECL

Where do you start preparing for CECL? Most banks with whom I’ve discussed this topic agree, that first and foremost it is imperative to clean up your portfolio data. The second most common preparation step is performing a thorough review of your loan categories to ensure a cohesive segmentation approach is taken for like-kind products. Most commonly used general ledger category descriptions such as “Personal Loans” or “CRE Non-Owner Occupied” won’t suffice under CECL. Each item in the segmented group will be impacted equally when applying the economic drivers and projecting the future losses.  You will need to narrow the scope when segmenting to ensure a more homogenous view within each segment.

After cleaning your data and loan categories, it’s time to determine the appropriate credit loss measurement method and how it conforms to the bank’s credit and risk analysis processes. The amount of “expected loss” in a portfolio should be driven by that credit analysis. While some believe certain methods may be best applied to certain consumer loan portfolios and other methods are better for commercial portfolios, different methods and analysis provide different aspects of a more comprehensive credit risk analysis.

Methods Will Likely Differ By Product Segments:

Vintage analysis of charge-offs may best enable analysts to observe how underwriting standards and the economic cycle impact a current loss expectation.
A credit migration analysis may help identify deteriorating credit performance outside charge-off data.
Tracking defaults and loss severity patterns may help analysts estimate exposure in collateralized loans and also supplement observations from credit migration analysis.

After your credit and risk analysis process is adequately disseminated and aligned, it’s time to tackle the hard part of CECL implementation. For me, the hard part centers around what economic drivers to rely upon and what level of influence they will have within your defined segments and differing methodologies.

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Understanding a Key Challenge of CECL: Economic Drivers

Forward-looking estimates depend on the mapping of historical loan data to economic trends, such as rising or falling interest rates, a thriving or struggling economy, or a healthy or weak real estate market. You’ll need to correlate key economic metrics and associated losses while identifying historical credit quality changes, loss patterns, or prepayment changes. Risks specific to a loan type or even to the level of a geographic area also must be considered.

Macroeconomic considerations should include national or local trends in unemployment rate, real median income, changes in gross domestic product, changes in housing prices, changes in real estate values, housing starts. All of these factors need to be considered as identifiers of trends and can act as telltales for monitoring future expectations. As if cleaning up your data, segmenting, and identifying the credit risk analysis methodologies wasn’t enough!

Identifying the appropriate economic drivers for CECL can be a monumental task. Don’t be surprised if  it requires several iterations once you see the impact on capital. How you prepare for CECL may not look exactly the same as the bank down the street and that’s okay. What’s important is understanding the challenges of CECL and how it impacts your institution.

It’s time to start tackling the hard part of CECL implementation.

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