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How Independent Loan Reviews Strengthen CECL Model Validation

Why Loan Review Is Your Secret Weapon

Article

December 10, 2025

The Role of Independent Loan Review and CECL Validation

Having validated numerous models for leading financial institutions, Cherry Bekaert has found that independent loan reviews are crucial in model validations because they identify early risks of credit deterioration, act as a control measure to validate loan pool segmentation, and enhance model assumptions. In addition to managing newfound risks, independent loan review also provides granular, loan-level insights that inform the model.

Increasing Accuracy in CECL Loss Estimates

The Current Expected Credit Loss (CECL) accounting standard requires earlier recognition of credit losses and a forward-looking approach to estimating lifetime losses on loans and other financial assets. This demands validation of:

Reasonable and supportable forecasts for expected credit losses.
Risk segmentation of financing receivables.
Comprehensive documentation of allowance methodologies.
Governance and controls over data, modeling and reporting.

Incorporating loan review into the CECL validation process has a powerful impact on the accuracy and timeliness of lifetime loss estimates. By leveraging real-time performance monitoring and early detection of credit deterioration, loan review provides actionable insights that allow financial institutions to proactively adjust reserves and respond swiftly to changing credit conditions.

Real-time analysis of borrower financial health, payment patterns and covenant compliance ensures that emerging risks are promptly identified. Early detection of credit deterioration and collateral weaknesses enables institutions to update CECL reserves before losses materialize, supporting more resilient financial decision-making.

Aligning Loan Groups With Risk Segmentation

Regular review of reasonable and supportable forecasts is essential for meeting compliance requirements and effective risk management. Loan review supports accurate risk segmentation and dynamic pooling, ensuring that CECL models reflect the portfolio’s true risk profile.

Effective CECL modeling depends on these aspects, but loan review ensures that loans are grouped by similar credit risk characteristics, such as:

Loan type or purpose
Collateral type
Borrower type or entity
Credit score
Risk rating
Loan-to-value (LTV) ratio
Geographic Location
Historical loss experience

These groupings are foundational for Probability of Default (PD) and Loss Given Default (LGD) modeling. Most banks and credit unions rely on call report codes or segmentation based on regulatory reporting structures for loans and leases, but also sub-segment by loan grades.

Under CECL, loan pool performance is influenced by external factors, such as macroeconomic conditions, interest rates, regulatory shifts, geographic and sector-specific risks, and borrower behavior. Industry-specific risks include:

Consumer loans, which are especially sensitive to economic downturns.
Commercial real estate and commercial and industrial loans, which react to rate changes and market cycles.
Government-backed and healthcare loans, which depend on policy changes
Agricultural and energy loans, which are impacted by commodity prices and regulations.
Credit utilization and repayment capacity, which are affected by borrower trends.

Loan review detects misclassified loans and emerging risks within segments, prompting re-segmentation or individual assessment as needed. And, as credit risk evolves, loan review supports the timely reallocation of loans between pools, maintaining model accuracy.

Loan Review’s Influence on Model Assumptions

Loan review assigns or validates loan grades that directly influence model assumptions. CECL accounting standards do not require financial institutions to use a specific model to calculate estimated losses, so the best method depends on the financial institution’s available data, nature of the loan portfolio and regulatory guidance.

Common CECL methodologies include:

Discounted Cash Flow (DCF): A preferred method that estimates future cash flows for each loan or pool and discounts them to present value to calculate expected losses.
Probability of Default/Loss Given Default/Exposure at Default (PD/LGD/EAD): A loan-level or pool-level method that estimates the probability of default and the percentage of the asset lost if default occurs, often for longer-term assets.
Weighted Average Remaining Maturity (WARM): A practical option for smaller institutions, it combines average annual charge-off rates with the portfolio’s weighted average remaining life.
Static Pool or Open Pool: A method that tracks the performance of a pool of loans (or a single pool) over time to determine historical charge-off rates and applies them to current loan balances.
Vintage Analysis: A method focused on loans grouped by their origination year (vintage), analyzing the charge-off patterns of specific vintages to predict future losses.

Key Takeaway: Regardless of the chosen methodology, loan review can identify risks early and ensure segmentation and pooling integrity.

PD/LGD/EAD Methodology Example

The table below is an example of the direct relationship between loan review and its impact on PD/LGD/EAD assumptions used to calculate estimated credit loss.

Aspect	Loan Review Support	Impact on CECL
PD Sensitivity: How this model’s output changes with various factors, such as economic cycles	Downgrades (loan modification) increase PD, upgrades (refinance) reduce PD	Lender’s reserve levels are affected, triggering an adjustment to expected loss
LGD Calibration: Aligning a model's predicted LGD with a long-term average	Assesses collateral adequacy, identifies deterioration	Higher quality collateral lowers LGD, increasing reserves as collateral deteriorates
LGD Adjustment: Involves applying a specific, often conservative, overlay to the calibrated LGD	Evaluates recovery expectations based on borrower behavior, market conditions, etc.	Provides early signals for reserve adjustment
EAD Considerations: Factors financial institutions evaluate to estimate the total outstanding amount a lender would face if a borrower defaults	Identifies off-balance-sheet exposures and draw risks	Affects exposure at default calculations

Loan Review Strengthens Individual Loan Analysis

Loans are individually assessed when they show signs of elevated credit risk or possess unique characteristics that make pooled analysis inappropriate. These typically include:

Non-performing loans or those on nonaccrual status.
Loans with payment delinquencies, covenant breaches or adverse borrower developments.
Large or complex credits with unique terms or collateral.
Loans in industries or segments vulnerable to environmental or economic shifts.

Loan review teams play a critical role in identifying these loans early, often flagging issues such as payment delays or borrower-specific risks that warrant individual evaluation. For individually assessed loans, CECL requires a forward-looking estimate of expected credit losses. Common methodologies include:

Discounted Cash Flow (DCF): Estimates future cash flows expected from the borrower and discounts cash flows using the loan’s effective interest rate.
- The reserve is recorded as the difference between the amortized cost and the present value of expected cash flows.
Collateral-based Approach: Used when repayment is primarily expected through collateral liquidation.
- The reserve is based on the fair value of collateral (less costs to sell), compared to the loan balance.

Loan Review Enhances Model Validation and Governance

Loan review serves as a crucial checkpoint in the ongoing assessment and validation of credit risk models such as those used for CECL. By systematically evaluating individual loans and portfolio segments, loan review teams generate independent observations that can be compared against model-generated outputs.

This process creates a feedback loop, where discrepancies between predicted outcomes and actual portfolio performance help institutions identify and address model weaknesses.

Model Output Verification

Loan review practitioners analyze the accuracy of risk ratings, loss estimates and other metrics produced by the institution’s models. When inconsistencies arise, these findings prompt recalibration of model assumptions, segmentation logic and Q Factor adjustments. Such continuous oversight ensures that models remain aligned with the institution's evolving risk profile.

Internal Control and Governance

Loan review serves as a second line of defense, alongside internal audit, to validate the adequacy of reserve levels, the completeness of credit risk assessments and the robustness of processes governing data integrity. This independent perspective enhances transparency and strengthens the institution’s overall risk governance.

Periodic Model Validation: Loan review findings guide institutions in fine-tuning model parameters, reducing bias and enhancing predictive accuracy.
Governance Frameworks: Comprehensive reporting from loan review supports board and executive oversight, demonstrating effective risk management for regulators and examiners.
Regulatory Alignment: Well-documented loan review processes underpin defensible Q Factor adjustments that meet OCC, FDIC and FRB expectations.
Continuous Feedback Loop: Regular input from loan review enables timely updates to model logic, ensuring ongoing relevance and compliance.

The integration of loan review in model validation and governance equips institutions to adapt to market changes, regulatory shifts and emerging risks. By providing actionable insights and independent scrutiny, loan review not only fosters model accuracy but also supports the long-term soundness and sustainable growth of the portfolio.

How Cherry Bekaert Can Guide You Forward

The lessons learned in the wake of CECL implementation highlight the critical role of loan review in model validation, risk segmentation and reserve management. By consistently providing objective assessments, validating model assumptions and supporting regulatory compliance, loan review ensures that CECL reserves truly reflect your institution’s credit risk profile. As regulations and market conditions evolve, maintaining a robust loan review program is essential for sound risk management and sustained growth.

At Cherry Bekaert, our Risk Advisory and CFO Advisory teams offer independent, experience-driven portfolio reviews tailored to your financial institution’s unique needs. With a dedicated CECL validation and review team that leverages extensive hands-on banking industry experience, we deliver actionable insights and practical solutions to streamline your implementations, strengthen your risk oversight and meet your compliance objectives.

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