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

Santa Fe, NM  |   (505) 670-7670  |  info@deepfutureanalytics.com

FOR IMMEDIATE RELEASE: Minnesota Credit Union Network and Deep Future Analytics Announce Partnership

St. Paul, MN (January 11, 2020) – Minnesota Credit Union Network (MnCUN) and Deep Future Analytics (DFA) announced their partnership today. MnCUN will make available DFA’s Prescient Manager™ software to its membership. Prescient Manager™ is an easy-to-use, web-based credit risk forecasting and stress testing solution for credit unions and community banks. The software’s functionality includes: • Accurate, scenario-based, account-level FAS 5 ALLL and CECL forecasts including discounted cash flow functionality. • New loan pricing optimization leveraging the same cash flow model as for CECL. • Scenario-based loan valuations for purchases and sales of loan participations.

Joseph Breeden, founder and CEO of Deep Future Analytics said, “We are excited to be partnering with MnCUN. We share a common vision that our accurate, scenario-based, account level cash flow models can create value across many functions in the FI. These solutions are integrated and coordinated in a way that a collection of independent models cannot be. MnCUN will be a great partner for bringing this capability to Minnesota credit unions.”

“Deep Future Analytics will help best position Minnesota credit unions to manage and anticipate risk. The all-in-one software calculates the necessary lifetime loss forecasts for CECL, but also provides accurate and actionable information for portfolio management, account management, and loan pricing,” said John Ferstl, Chief Operations Officer for MnCUN.

ABOUT DEEP FUTURE ANALYTICS Deep Future Analytics is a joint operational venture of Prescient Models, LLC and Nuvision CUSO Holdings, LLC, a CUSO operated by Nuvision FCU. Dr. Joe Breeden, founder of Prescient Models, brings more than 20 years of experience leading financial institutions through predictive financial modeling, allowing clients to achieve a real understanding of portfolio dynamics for retail lending. Nuvision FCU was founded nearly a century ago as the credit union of Douglas Aircraft, its values were forged in the factories and plants that made the region prosper. Now with assets well-over $2B, Nuvision is a multi-state Credit Union, with branches in Southern California, Arizona, Wyoming, Alaska and Washington.

About the Minnesota Credit Union Network

The Minnesota Credit Union Network is the statewide trade association that works to ensure the success, growth and vitality of Minnesota credit unions. With approximately $25 billion in assets, Minnesota credit unions are local, trusted financial cooperatives that serve more than 1.8 million members at nearly 400 branch locations around the state. As not-for-profit institutions, credit unions give back to the communities they serve. For more information, visit www.mncun.org.

Media Contact: Charles Hoy, Director of Business Development Deep Future Analytics LLC choy@prescientmodels.com (505) 690-7195

Webinar Summary: Comparing CECL to FAS5 Results

Webinar Summary: Comparing CECL to FAS5 Results

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.

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.

Click Here to view the Webinar