Loan Participations, CECL, Stress Testing, Loan Modeling for Banks and Credit Unions

Santa Fe, NM  |   (505) 490-6094  |  info@deepfutureanalytics.com

OCTOBER 17, 2019

COMPARING RESULTS OF
CECL TO FAS5

PRESENTED BY DR. JOSEPH BREEDEN

ABOUT THE PRESENTERS

Dr. Breeden literally wrote the book on CECL in addition to the over 50 other books and trade publications in his name. He has created numerous financial models in his 25+ years, including the Mexican Peso Crisis, Asian Economic Crisis, 2001 Global Recession, Hong Kong SARS Recession, US Mortgage Crisis, and the Global Financial Crisis.

WEBINAR OVERVIEW

This Prescient Models and Deep Future Analytics October 2019 webinar reveals the results of our study on the predicted changes to reserve requirements as a result of CECL. See Full Summary at the bottom of this page.

KEY TAKEAWAYS

✓ Peer Group Comparisons of CECL Loss Reserves
✓ Comparisons of CECL to FAS5 Results
✓ Why and How to Adapt to these changes
✓ Differences in new allowance for Banks vs. Credit Unions
A MUST WATCH Webinar:
Capturing Adverse Selection
April 14, 2022
Watch Now
A MUST WATCH Webinar:
Classical and Quantum Computing
Mar, 2022
Watch Now
A MUST WATCH Webinar:
Quantifying Model Selection Risk
February, 2022
Watch Now
A MUST WATCH Webinar:
Guiding AI & ML through the Economic Cycle
January 13, 2022
Learn More
A MUST WATCH Webinar:
What is machine learning good for?
December 2, 2021
Watch Now
Previous
Next

WEBINAR SUMMARY

Credit Unions can expect at least a 22% increase and Community Banks a 59% decrease in reserves as a result of CECL?

Deep Future Analytics (DFA) and Prescient Models (PM) recently conducted a joint study across 103 CECL clients to determine how much their loss reserves could change if CECL were adopted today. The results were presented in a 10/17 webinar which we summarize in this article.

Modeling Accuracy
Since loan modeling is such a complex animal, the first question you should always ask is: “Can I trust the numbers?” For this, Dr. Joe Breeden, world renowned credit analyst and author of the “Living with CECL” book series, takes you through how advanced loan modeling works and the data and equations behind it. I provided a “stripped down” version of this below for those less familiar with loan modeling.

For the study we used a MultiHorizon Survival Model. This highly advanced method of computing credit risk is actually a two-step approach which adds to overall accuracy and application of the data. When you take multiple factors like Lifecycle, Environmental, and Credit Quality the information must be handled correctly or the results will be erratic. Therefore, this approach accounts for the changes in variable significance across multiple horizons. For example, delinquency is a very strong indicator of PD in the early months but then becomes less important. All in all, as we look at lifetime losses it is important to have a model that will stand the test as we look multiple years into the future.

Overall CECL vs. FAS5 Results
We took a look at the ratio of the output of the MultiHorizon Survival Model to what is currently being reserved under FAS 5. Among community banks, the most common result (median) was a significant reduction of -59% in reserves. For credit unions the model reveals an increase in reserves of 22%. These estimates are before any Q-Factor adjustments. While the banks may be able to add Q-Factors to bring the new requirements more in line with existing practices, the credit unions will have a much more difficult time “selling” a negative Q-Factor to their auditors.

Next, we took the client data and further stress tested using the FRB Severe scenario for a near-term recession. As a result the CECL loss reserves see a significant increase with the banks going from a -59% up to +69%, and credit unions from +22% up to +107%.

Product Results
To understand the differences by product, we are taking our model’s 12 month horizon and comparing to a lifetime horizon. This will measure the number of years of coverage you need under CECL, compared to what you would’ve had before.

The median ratio of CECL / 12Mo. loss rate for the individual products is essentially the average life of the loan. For example, we computed the average life of Consumer Loans to be 1.59, thus resulting in a 59% increase in reserves of the current 12 month horizon. For Auto loans the result was an increase of 135%, 55% for Consumer Line, 78% for Credit card, 140% for Residential RE, and 342% for HELOC. The HELOC is sort of an interesting case because it cannot be canceled. This poses many issues in how we manage loss estimates and this actual estimate could actually be understated.

On the commercial side, we show increases for all products as well: Ag Loans (197%), Ag Lines (2%), C&I Loans (93%), C&I Lines (140%), CRE Loans(251%), and CRE Lines(310%)

There are still plenty of institutions today that have yet to prepare for the new CECL standards. Based on these results we feel the time is now to find out your institution’s new reserve requirements so you can make the appropriate course corrections today to ensure a smooth transition tomorrow.

ABOUT US

At Deep Future Analytics, we arm financial institution decision makers with best-in-class loan modeling tools and guide them to healthy and sustainable growth.