"Card issuers walk a fine line between alerting and alarming consumers who could become victims of cardholder fraud because of breaches."
Using more sophisticated technology to manage potential compromised card fraud was the basis of the latest article featured on FIS Payments Leader, titled "New Machine Learning Tools Advance the Fight Against Card Fraud." Dondi Black, VP of Payment Strategy for FIS, details how machine learning tools can deliver greater accuracy when it comes to fighting card fraud — and in a way that lessens the impact on the customer experience. The key to achieving the outcomes desired today by bank and credit union fraud and risk managers? Early detection.
"Machine learning can be applied to substantially decrease the time that it takes between networks alerting issuers about what cards have been involved in breaches and to automate labor-intensive processes around reissuance. With early detection tools, based on machine learning, issuers are provided with a quantified level of risk of future fraud involving specific cards months ahead of traditional alerts," Black writes. "Financial institutions can then make strategic decisions about what cards to block and reissue. Continuous updating of the algorithms that quantify risk levels provide financial institutions the power to stay on top of their card portfolios."
Bank leaders, she notes, must balance "alerting and alarming customers" in order to keep customers feeling safe about their own financial data. Blindly reissuing can trigger a process that is both ineffective and expensive, which can also create more customer churn. Relying on fraud detection tools that leverage the power of machine learning to enhance this process can make all the difference in spotting potential compromised card faster and more effectively.
"By simplifying, streamlining and automating the process of fraud detection, institutions reduce the impact of fraud on customers and continue to build their trust," she writes.
Black points to one key problem across the financial institution ecosystem — determining which compromised cards will actually go fraudulent. Since data indicates that just 5 percent of all cards involved in a breach is then used for a fraudulent transaction, there's no need to reissue every one of those cards from that incident. The real trick is knowing which of those impacted cards are actually at the greatest risk and highly likely to experience fraud.