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CECL Model: Build or Buy?

August 21, 2017
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Compared to existing ALLL requirements, Accounting Standards Update 2016-13 (CECL) will require more inputs, assumptions, analysis and documentation, making the option to automate the process significantly more attractive for many institutions. Regardless of an institution’s approach, key consideration areas for a CECL-ready model include data management, contractual life, segmentation, methodologies, forecasting and adjustments, documentation, product evolution and enhancements, training, advisory services, and technical support.

The following recommendations are not intended to replace regulatory guidance as it relates to vendor management. Rather, the intent is to provide an understanding of a CECL-ready model and the critical elements that such a model should contain for tactical due diligence.

Data: Data serves as the foundation for historical loss experience calculations and represents a significant threat to a successful implementation. A solution provider should offer a supportive and effective integration process with institutions’ core providers and other data sources. The provider should help identify critical loan-level data gaps, provide remediation support for historical data inconsistency as well as future loan-level collection, all while providing adequate and accessible data storage.

Contractual Life: The expected life of each segment and/or prepayment behavior will need to be calculated within the solution.

Segmentation: Institutions must analyze assets on a collective or pooled basis unless unique risk characteristics exist. Designated pools should be relatively granular while maintaining statistical significance. Vendor models should easily illustrate pool size and offer a variety of segmentation and sub-segmentation elections based on customizable and dynamic logic. The model should allow institutions to automatically and manually identify and separate loans for individual analysis.

Methodologies: Vendors that do not provide for a host of methodology elections today can inadvertently limit your options for tomorrow as particular data issues will be made apparent via execution. Methodology options should include vintage analysis, probability of loss and loss given default (PD & LGD), migration analysis, cumulative loss rate, and discounted cash flow (DCF).

Forecasting and Adjustments: Vendor models should allow for swift inclusion and exclusion of all observable analysis periods and provide forecasting intelligence, support, and application.

Documentation: The new standard will require more inputs, assumptions and analysis at the pool-level; tracking, consolidating, reporting, and displaying all information necessary to review, support and recalculate is a critical function of any vendor-based solution.

Product Evolution and Enhancements: Institutions should have a clear understanding of the product roadmap and the contractual obligation to remain GAAP compliant.

Training, Advisory Services, and Technical Support: Understanding the availability, expertise and fee structure for training, advisory services, and technical support is a must. A vendor should have internal experts that have experience working for and with financial institutions and regulatory bodies.

To learn more, download the complete CECL solution buyer’s guide.

About the Author


Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

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