The SCALE Method for CECL: A Streamlined Approach to Expected Credit Losses 

by: Dave Bodiford, CPA 

The Current Expected Credit Loss (“CECL”) standard significantly altered the way financial institutions estimate loan losses. CECL replaced the traditional incurred loss model, emphasizing a forward-looking approach that accounts for expected future losses over the life of a loan. Although the CECL standard affected all businesses using generally accepted accounting principles in the U.S. (commonly known as “U.S. GAAP”) for accounting purposes, financial institutions were particularly affected due to the long-term nature of their loan portfolios. 

One challenge of implementing CECL, particularly for smaller and medium-sized financial institutions, has been the complexity of gathering the data, the large amount of time needed to implement and continue to comply with CECL, as well as the cost of compliance – causing small institutions to consider the need to invest in costly software and hiring additional staff. This is where the SCALE method developed by the Federal Reserve offers a practical, simplified, and cost-effective solution for small community banks.

What is the SCALE Method?

SCALE stands for “Scaled CECL Allowance for Losses Estimator”, a method developed primarily for smaller community banks and credit unions that might not have the extensive historical data, staff, or resources larger institutions can leverage. The method was proposed by regulators such as the Federal Deposit Insurance Corporation (“FDIC”) and the National Credit Union Administration (“NCUA”) to help streamline CECL adoption while maintaining compliance with the standard.

The key feature of the SCALE method is that it allows institutions to rely on industry-level data or peer group data to estimate their own credit losses. By using publicly available data, smaller institutions can estimate their lifetime expected losses more efficiently and accurately without needing to develop their own models from scratch or investing in expensive software and/or staff to maintain compliance.

How the SCALE Method Works

The SCALE method operates on a fundamental principle: institutions can scale the publicly available credit loss experience of larger, more complex financial institutions to reflect their own asset size, risk profile, and loan portfolio composition.

Using the SCALE method involves no additional software purchases – to start, an institution can begin by simply  downloading and utilizing the spreadsheet from the Federal Reserve’s resource center at this link: https://www.supervisionoutreach.org/cecl/scale

Here’s a basic outline of how the method works:

  1. Gather Peer Group Data: Financial institutions obtain peer group data from call reports, which provide publicly available credit loss information. These peer groups are typically selected based on similar characteristics, such as asset size, geographic region, and business model. Generally, the current peer data used in the model in the SCALE tool spreadsheet will be from the most recent quarter’s aggregated call reports Schedule RI-C, and is available here: https://www.supervisionoutreach.org/cecl/ric.
    For example, if you are preparing the SCALE model for September 30, 2024, you would likely use the last quarter’s data (6/30/24).  However, some institutions may choose to use different peer data.
  2. Adjust Peer Loss Data: The loss data from peer groups is then adjusted to reflect the institution’s specific loan mix, risk levels, and historical credit performance. These adjustments ensure the loss estimates are more applicable to the institution’s unique circumstances.  In addition to considering your own institution’s historical credit performance versus your peers, you should also consider the local economy specific to your loan portfolio and multiple other factors that are specific or unique to your loan portfolio versus your peers. Note that adjustment percentages used specific to the institution can be positive (effectively increasing the amount of loss estimates vs. peer data) ornegative (effectively decreasing the loss estimates vs. peer data).  Disaggregate, or “split out”, your loan portfolio as much as needed, adding additional rows if necessary and different adjustments to the peer losses for larger groups if needed.  Most importantly, the adjustments need to be supportable (see #5 below).
  3. Scale to Portfolio Size: The institution applies these adjusted credit loss rates to its own loan portfolio, scaling the data proportionally to its asset size and specific characteristics.  As with #2 above, be sure to consider unique factors related to your institution and split out your loan portfolio.
  4. Consider Reasonable and Supportable Forecasts: Similar to traditional CECL models, the SCALE method requires institutions to incorporate forward-looking economic forecasts into their loss estimates. This step involves assessing potential future economic scenarios and how these could affect loan performance (and document these thoroughly– see #5 below). 
  5. Document Assumptions and Adjustments: Institutions using the SCALE method must document all assumptions, adjustments, and methodologies in their CECL calculations. Be sure to thoroughly document the reasoning and any necessary data comprising the adjustments that are unique to your financial institution.  This ensures that the approach is transparent, and that examiners and auditors can understand the reasoning behind the credit loss estimates.

Benefits of the SCALE Method

The SCALE method offers several benefits to institutions, especially smaller ones:

  1. Simplicity: For many community banks and credit unions, building a fully customized CECL model from scratch is daunting. The SCALE method simplifies the process by allowing them to leverage existing peer data.
  2. Cost Efficiency: Developing internal models requires significant investment in data infrastructure, personnel, and consulting services. By using industry data, the SCALE method reduces the need for extensive resources.
  3. Regulatory Compliance: The method was developed with input from regulatory bodies like the FDIC and NCUA, ensuring that institutions adopting the SCALE approach are compliant with CECL standards. This reduces the burden of developing models that meet regulatory scrutiny. 
  4. Flexibility: Although the SCALE method relies on peer data, institutions can still make adjustments to reflect their specific risk profiles and forward-looking economic assumptions. This flexibility ensures that loss estimates remain relevant and accurate.
  5. Time-Saving: Given its streamlined nature, the SCALE method allows institutions to implement CECL more quickly than if they were to develop custom models. This is particularly beneficial for institutions with limited staff dedicated to accounting and financial reporting.

The Federal Reserve has also released an Expected Loss Estimator (“ELE”) tool for institutions that might consider the commonly used Weighted-Average Remaining Maturity (“WARM”) method of estimating CECL more appropriate. 

Resources for the ELE tool can be found at this link: https://www.supervisionoutreach.org/cecl/ele.

Contact Dave Bodiford, CPA with questions (803) 753-5259 or [email protected].