Data Analytics: More Than Just Numbers

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Aim to Solve Big Problems 

A major challenge for credit unions in 2021 will be proactive credit risk management by projecting which loans are likely to become delinquent, says Suchit Shah, founder and chief operating officer of CUES Supplier member CU Rise Analytics, based in Vienna, Virginia.

“Every credit union and bank in the United States has granted payment deferments, so members who’ve suffered pandemic-related income loss could skip payments,” Shah says. “Those missed payments are not being reported to credit bureaus to protect members’ credit standing, making the aggregated credit scores they produce essentially irrelevant for the time being.”

To fill that information gap about members’ current credit standing, CU Rise Analytics has developed a risk score based on behavioral attributes from credit unions’ internal account data that goes well beyond loan delinquency status. Have members’ payroll deposits stopped? Are they making lower payments on their credit card balances? Have they begun tapping into home equity lines of credit and credit cards that previously didn’t carry balances?

“We’ve created a statistical algorithm that gives higher weight to recent events as the basis for a robust internal credit risk score,” he notes. “It utilizes the credit union’s view of changes in income and changes in payment behavior to present a realistic, real-time view of credit risk, which is much more relevant in the current situation.”

Equipped with that information, credit unions can guide portfolio management and outreach to members who may be struggling financially to offer assistance with personal financial management and options for loan payments.

The above is an excerpt from a CUManagement article. To find what Suchit Shah has to say about credit unions using predictive analytics for formulating member retention and cross-selling strategies and predicting the next best product for their members, read the complete article here.