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Abrigo: Current Expected Credit Loss (CECL) Solutions


Provider: Abrigo


Abrigo’s allowance technology gives financial institutions flexibility in achieving CECL compliance by offering two ABA-endorsed solutions, Loan Loss Analyzer and Sageworks ALLL. The technology also acts as a data warehouse to help banks collect the information needed to produce forecasts and inform directors of the credit risk they face.

Both solutions automate the allowance calculation to maintain compliance with GAAP. The solutions give banks a host of loss rate methodologies and segmentation options to create the most defensible and representative model of credit loss in their portfolio.

Loan Loss Analyzer (LLA) is an automation tool tailored to the bank, which calculates and documents the Allowance for Credit Losses (ACL) under CECL to help satisfy regulatory and audit requirements. Sageworks ALLL similarly offers a compliant solution for GAAP, but it also affords banks flexibility  to quickly and easily test different CECL scenarios to see the estimated impact on the allowance and capital. The Sageworks solution is also integrated into Abrigo’s origination, stress testing, and asset/liability solutions.

When First & Farmers National Bank began searching for a CECL solution in 2020, the top priorities for a good fit were cost and integration support. And with a 2023 deadline fast approaching, they wanted stability, knowledgeable staff, and peace of mind that their vendor wouldn’t be bought or sold during the implementation process. They chose Abrigo; read about their story.

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  • Best practices learned from supporting more than 1000+ institutions through CECL
  • Time savings, as bankers do not have to track down data, reconcile balances in several spreadsheets or manually update formulas
  • Auditor and examiner satisfaction through a defensible and documented allowance process
  • Flexibility to quickly try different scenarios and segmentation strategies without overhauling the calculation
  • Robust loss rate methodologies, including discounted cash flow, that allow the bank to choose the best model for their loan pools and portfolio
  • Integration with any core system as well as additional interfaces such as general ledger, charge-off and recovery, credit card, Small Business Administration (SBA) data and others
  • Full-service support team offering quick, unlimited technical support
  • Hosted in the institution behind your firewall or in the cloud



Abrigo: Current Expected Credit Loss (CECL) Solutions


CECL in 2023: Best Practices Learned from SEC Filers

March 17, 2021 | 02:00 PM ET

In this presentation, tailored for financial institutions that have not yet adopted the standard -- or those who may feel the need to take a second look at their practices given the realities of the pandemic economy - we will discuss lessons learned from implementing the standard at more than a hundred such institutions, working with scores of different audit and validation firms across the spectrum of size, resources, and sophistication.


CECL Implementation Best Practices – A Discussion with Community Banks

March 01, 2022

Most community banks with assets under $1 billion will implement CECL in 2023. But, where to start? Peter Albero, EVP and CFO of Salisbury Bank, and Candace L. Richardson, internal audit manager and CECL officer for Security State Bank, share their recent CECL implementation strategies. The discussion will also include time for FAQs about the implementation process from CECL experts.


CECL Implementation FAQs: Progress as 2023 Approaches

November 22, 2022

With less than a few months to comply with the current expected credit loss model (CECL), many still have outstanding questions and concerns about their efforts to prepare. Whether your bank is rushing to implement or are already running in parallel, much can be learned from the experiences of those that have already adopted.


Model Risk Management Implications for CECL: Monitoring Strategic Risks

April 13, 2023 | 02:00 PM ET

During this session, DCG’s leading CECL model management experts will provide meaningful insights into practical ways to identify model performance issues and share leading approaches to assumption management that can drive model reliability, consistency, and strategic insights.



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Helen N. Sullivan

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