CO-OP Launches Industry-First Machine Learning Fraud Scoring Model Built Specifically For Credit Unions

Real-time Scoring Enables Credit Unions to Reduce False Positives, Fraud Chargebacks and Fraud Losses, Delivering an Exceptional Payments Experience for Members

RANCHO CUCAMONGA, California – CO-OP Financial Services has added a new tool to its expanding suite of COOPER-branded machine learning fraud detection and prevention solutions. COOPER Fraud Score is a credit union-focused, real-time scoring tool designed to accurately detect more fraud, helping credit unions react quickly to emerging trends, ultimately building member confidence in their credit union-issued cards. 

COOPER Fraud Score creates a risk score in real-time that is then applied to transaction authorization requests. This score is delivered to a range of decisioning tools within CO-OP’s fraud prevention ecosystem, with CO-OP fraud prevention consultants setting custom strategies for individual credit unions. 

CO-OP’s launch of the solution is well-timed, as analysts predict the pandemic-related increase in digital payments will lead to a dramatic rise in payments fraud risk into 2022. The tool enables a predictive approach to fraud prevention through a supervised machine learning model fully focused on the credit union industry. COOPER Fraud Score addresses problematic vulnerabilities, such as BIN attacks, which have plagued many card issuers since the COVID-19 outbreak.  

WestStar Credit Union in Las Vegas, Nevada, served as a beta test site for COOPER Fraud Score. According to Rick Schmidt, President/CEO of the credit union, COOPER outperformed WestStar’s current fraud solution on all transactions where both systems scored suspicious transactions. “There was a lift of up to 30 percent in the set of velocity checking data where the other system tried and failed,” said Schmidt. “We didn’t know we could engage with something as sophisticated as COOPER.”  

According to Bruce Dragt, Chief Product Officer for CO-OP, speed is a critical capability in today’s dynamic threat environment.  

“The beauty of real-time transaction data and machine learning technology is immediacy,” said Dragt. “The technology generates cost savings from reduced false positives, fraud chargebacks and fraud losses. Just as importantly, though, is the increased trust and reliability members gain when they experience fewer hiccups in the day-to-day movement of money. COOPER Fraud Score’s advanced fraud-fighting technology helps buoy the primary financial relationships credit unions are working so hard to earn and maintain.” 

COOPER Fraud Score is platform-wide, meaning it is integrated into CO-OP's real-time decisioning tools across credit, signature/PIN debit and ATM transactions. When a transaction is identified as potentially fraudulent, the credit union receives “reason codes” that explain why the solution assigned it the scores it did. Credit unions may choose to relay this unique level of intelligence to members, helping them understand why a particular transaction was declined, improving the payments experience while adding to the trust members have in their credit unions.   

“A key differentiator for COOPER Fraud Score is the integrated team of credit union-centric experts working alongside the technology,” said Dragt. “CO-OP’s fraud team consists of data scientists, prevention consultants and detection analysts, all working to monitor COOPER Fraud Score and apply its use in fraud-fighting strategies. Continually learning from the solution’s data feedback loop, as well as emerging fraud trends and use cases, the team is highly focused on outcomes and model efficacy. Because they understand credit unions as much as they do fraud risk, the member experience is always a top priority.”  

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