As financial institutions continue adjusting their Current Expected Credit Loss (CECL) models, many are encountering common challenges during validation and internal audits. In this article, we discuss common CECL findings that apply to institutions of all shapes and sizes.
Qualitative Factors
The most frequent issues institutions face relate to qualitative factors—adjustments made to account for unique risks that aren't fully addressed by the quantitative model.
- Many institutions rely on subjective judgment rather than tying qualitative factors to measurable data points.
- Without clear documentation, the relationship between external economic data and qualitative adjustments can be inconsistent.
- Establishing a clear framework—for example, defining how a 1% change in an external risk factor affects the model—can improve accuracy.
Strong Framework
- Established Anchor Points - Defines the maximum adjustment that can be applied through qualitative adjustments.
- Clearly Defined Scales – Ties qualitative factors to measurable data points, thus providing an objective and auditable approach for allocating qualitatively-derived basis point adjustments.
- Consistent Adjustments – X% change in data → Y% adjustment
- Documented Methodology – Transparent, repeatable process
- Improved Audit Readiness – Defensible and well-supported
Data Integrity
Accurate CECL modeling depends on the completeness and accuracy of historical loan and/or peer data.
- Mismatches between loan balances, historical charge-offs, and the model can distort loss rates and modeled results.
- Errors often stem from unique loan structures, incorrect mapping of loan attributes, or missing data in import files.
- Running segment-level reconciliations and validating data points within input files can catch inconsistencies before they impact the model.
Tip: Institutions using multiple data imports should standardize data fields to the extent possible and verify completeness to avoid errors in their models.
Unfunded Commitments
CECL guidance requires institutions to estimate potential losses on unfunded commitments, such as unused credit lines.
- Many institutions apply broad assumptions (e.g., assumed flat 10% reserve rate) across all loan segments without adequate support.
- Some segments, like home equity lines of credit (HELOCs) or construction loans, inherently have funding activity, yet models incorrectly assume funding expectations of 0%.
- Institutions without sufficient internal data can use peer studies or external benchmarks to refine assumptions.
Policy Documentation
Every institution should have a well-documented CECL model policy. Items we see most frequently omitted include:
- Ownership and oversight of the model.
- Frequency of model validation (internal vs. external).
- Key assumptions and frequency of sensitivity testing.
- Procedures for back-testing and outcomes analysis.
Internal Controls
Since CECL models involve multiple steps and data points, institutions should establish strong internal controls to detect and correct errors early.
Best practices include:
- Regular reconciliations between loan subledgers, general ledgers, and models.
- Documented review of manual inputs to avoid miscalculations.
- Board or committee oversight for key manual inputs or modeling adjustments.
- Recurring independent validation and/or operational assessments.
A proactive approach to internal controls helps prevent systematic errors, address regulatory risks, and respond to unexpected model results and accounting adjustments.
We Can Help
Navigating CECL compliance requires ongoing adjustments to models, documentation, and internal controls. At Elliott Davis, our Financial Services team helps institutions:
- Validate CECL models to maintain compliance with regulatory guidance and industry best practices.
- Perform operational assessments to identify process or control errors before they impact reporting.
- Perform a challenger model run, to provide additional comfort around the Institution’s modeled results.
- Provide feedback on how the institution can enhance documentation to better prepare for regulatory exams and financial statement audits.
Contact us today to discuss how our CECL validation and audit solutions can help improve your institution’s credit loss modeling.
The information provided in this communication is of a general nature and should not be considered professional advice. You should not act upon the information provided without obtaining specific professional advice. The information above is subject to change.
