CECL Model Validation

Ongoing Performance Monitoring for CECL

Interested in addressing a top validation finding and boosting decision-making confidence? Learn more and request your institution's sample report.

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Lessons Learned from the Adoption of CECL (Podcast)

The DCG team shares how institutions can take ownership of their CECL models, perform sensitivity testing, and monitor model assumptions. Listen here

Maximizing Your CECL Model
Part 1: Validation

See what institutions should do next to maximize the effectiveness of their new CECL model. Video: 3 Minutes

Featured Content

Confirm your CECL reserve model can withstand the test of time.

Maintaining a reasonable and supportable reserve estimation through varying economic conditions is critical for every financial institution. As these models become increasingly complex, highly scrutinized oversight from management, risk management, auditors, regulators, and investors is the norm for institutions of all sizes. Whether you have implemented a straightforward, in-house model or a more sophisticated third-party model, DCG’s team of CECL model validation and credit risk management experts have the right combination of mathematical rigor, credit modeling expertise, and horizontal perspective to meaningfully validate and effectively challenge your CECL model and related governance.

Will your CECL model provide the right quantitative results should economic conditions worsen?

Many community institutions are using vendor CECL models that will systematically underestimate quantitative reserves in an economic downturn – exactly when reserves are needed most. Ensure reserve adequacy in the event of an adverse economic scenario with insights from a high-quality technical model validation.

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How We Help Clients

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Expert CECL Model Validation

DCG's CECL model validation team includes former credit model developers, CECL model implementers, and MRM experts. With our combined breadth and depth of knowledge, we provide comprehensive and insightful model validations tailored for your institution’s size and complexity and appropriate for any CECL approach. DCG has experience with all the major vendor provided solutions, as well as internally developed models of varying complexity.

Ongoing Performance Monitoring

How are you demonstrating that your CECL model continues to be fit for use? For many institutions, constructing a sound monitoring program with reporting can be challenging. To get started with an ongoing performance monitoring framework, or to augment an existing one, DCG offers a quarterly monitoring report that incorporates critical components including sensitivity analysis and benchmarking. For a customized sample report using your institution’s data, contact the DCG CECL team.

Reserve Benchmarking

Consistent with MRM best practices and as a complement to our CECL model validations, DCG offers a CECL benchmark analysis to provide additional independent challenge. As regulators and auditors become more familiar with existing methodologies and outcomes, they expect strong internal documentation of performance monitoring and outcomes analysis. DCG’s independent benchmark can significantly augment your internal efforts.

CECL Model Documentation

With over 3,000 pages of documentation written over the past 5 years, DCG has the technical expertise and business acumen to produce polished documentation for all types of models. With a deep understanding of regulatory requirements and the ability to make complex topics easier to understand, we can help elevate the quality of model documentation at your institution.

Lessons Learned from DFAST

DCG has validated over 500 credit-related models, relying on a deep history with DFAST, credit, and ALLL validations to develop a robust CECL validation framework. Through unmatched industry experience and horizontal perspective, DCG has developed a 12-part CECL validation scope based on our proprietary research and experience conducting trial validations on CECL test models.

“Managing your CECL model assumptions is not a set-it-and-forget-it exercise.”

Mike Guglielmo

Managing Director

Maximizing Your CECL Model

Now that you’ve gone through all that hard work and implemented CECL, what’s next? DCG Risk Management Consultant Hannah Glasrud shares lessons learned from her work on CECL model validation and model risk management consulting. She discusses how to maximize your newly developed model and optimize your program through Validation, Remediation, and Risk Ratings.

Maximizing Your CECL Model
Part 1: Validation

While CECL implementation may be behind us, it’s not time yet for people to put up their feet. Join Hannah Glasrud, DCG Risk Management Consultant, to hear what institutions should do next to maximize the effectiveness of their new CECL model, starting with a comprehensive validation.

Maximizing Your CECL Model
Part 2: Remediation

In Part 2, DCG Risk Management Consultant Hannah Glasrud continues her discussion of how institutions can maximize the effectiveness of their new CECL models through remediating their validation findings.

Maximizing Your CECL Model
Part 3: Risk Ratings

After you’ve launched your CECL model, gotten it validated, and put a remediation plan in place, it’s still not quite time to relax. In Part 3, DCG’s Hannah Glasrud discusses the next step to maximize CECL model effectiveness: risk ratings.

Examples of Client Results

Created institution-specific CECL documentation for $10B+ bank with both technical detail for modelers’ understanding and practical discussion for non-statisticians’ understanding.
Provided effective analysis and a detailed technical review of complex CECL vendor approach and documentation to give management of $25B+ institution confidence that calculations were working as intended.
Identified shortcomings of vendor macroeconomic forecasting regressions used at <$10B community bank. Helped management understand the practical implications of independent variable transformations on reasonable and supportable CECL forecasts.
Validated complex ACL/CECL solutions comprising multiple modeling components, including (proprietary and vendor) econometric forecasting regressions, migration matrixes, loan-level loss rate modeling, portfolio-level loss rate modeling, aggregator models, and qualitative adjustment frameworks.