Benchmarking CECL models

CECL will have the most significant impact on American banking since the Dodd-Frank Act was adopted. Models currently being developed indicate that bank profitability—and bank department profitability—will be affected as institutions charge for credit loss provisions on new loans and credit downgrades on existing loans.

GCD will be working with Accenture and the IIF to help U.S. financial institutions benchmark their CECL models as they are developed. GCD will conduct deep methodological and calibration surveys and benchmarking studies in 2018. Institutions that would like to participate in the CECL work should contact Steve Bennett.

Step 1 is a deep CECL Methodology survey sponsored by Global Credit Data, the IIF and Accenture. The survey is intended to provide comparative information on bank’s planned methodologies for implementation of CECL. The questions are focused on credit data and modeling for the C&I CRE and Consumer portfolios. We plan to follow the survey with a benchmarking exercise to commence in the early fall.

We expect to provide a summary report and analysis to participants by mid-August. In addition, the anonymized data can be made available so that banks can conduct their own analysis.

The survey was designed to be completed in less than 40 minutes. Respondents will be able to choose from a menu of methodologies. We received substantial input by leading practitioners to ensure that questions where relevant and methodology choices comprehensive. The deadline for completion of the survey is July 31, 2018

To participate, please use this link: https://www.globalcreditdata.com/lms/index.php/183655?newtest=Y

Interested participants are invited to follow a webinar on June 21st, 2018 which explains our approach and questions in detail: 

https://www.globalcreditdata.org/events/webinar-on-cecl-methodological-s...

 

NOTE FOR MODELLERS: 

GCD has the world largest database collecting data related to credit failures (default) and their recoveries. The data dates back to 1998, allowing for meaningful statistics in terms of type of borrower, time and size of exposure at default and collateral recovery rates.

Check our LGD & EAD platform for more information. 

 

In cooperation with: 
 

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