Software providers are responding to credit unions’ increasing interest in data analytics.
Deep Future Analytics (DFA) uses its data warehouse to combine data from multiple credit unions so it can provide a more accurate forecast of where and when loan losses are likely to occur than a credit union could obtain using only its data, says Dale Fosselman, president/CEO.
“It’s a way to let credit unions participate in data analytics even if they cannot afford a data warehouse,” Fosselman says. DFA is a credit union service organization owned equally by $2.2 billion asset NuVision Federal Credit Union in Huntington Beach, Calif., and Prescient Models, which specializes in credit risk forecasting.
DFA’s software for loan losses is designed to help credit unions anticipate the demanding current expected credit loss (CECL) accounting standards, which will require financial institutions to increase their reserves for loan losses starting in 2021.
“To obtain a defensible, robust model for loan losses, you need about 100 losses per year in a given loan category,” Fosselman says. DFA meets that standard by collecting data on new and existing loans, exceeding $50 billion each month from participating financial institutions.
Overall, DFA’s anonymous, shared data pool contains data on more than $2.5 trillion in loans dating back to 2001. That data includes interest rates, current balances, loan-to-value ratios, borrowers’ FICO scores, and other factors that predict the timing and amount of loan losses based on a life-cycle model.
Using the software will help credit unions take steps to optimize their loan portfolios in a CECL-compliant way, Fosselman says. In the second quarter of 2019, DFA plans to introduce a loan participation platform to allow credit unions that sell loans to find buyers that benefit the most from a given pool.
“The idea is to use analytics so credit unions know which loans to sell to better optimize their portfolio,” Fosselman says.