A customer makes a card transaction that looks odd compared to her historical behavior patterns. Is this change the first sign her account has been compromised by a fraudster? Or just new behavior by the legitimate customer?
Making the right call in a fraction of a second is absolutely critical today as banks compete neck-and-neck to deliver superior customer experiences. Reducing false positives—legitimate transactions declined as potentially fraudulent—has a direct and immediate impact on cardholder perceptions of service quality.
Keep in mind that few cardholders differentiate which part of the bank—fraud management, mobile banking, a service center—they’re interacting with. It’s all part of the same experience. Every touch shapes their perception of how well the bank knows them and how well they’re being treated. Because fraud management is one of the key real-time interactions they may experience, it can play a central role in strengthening those customer relationships.
Recently, I’ve been blogging about two new analytic technologies that can greatly reduce false positives, while increasing fraud detection precision and speed. (For a recap, see here and here.) Both of these analytics operate in the stream of transactions to help determine in real time what any variation in customer behavior truly means.
If you're interested in learning more, I invite you to download a new Insights white paper that explores these analytic techniques in greater detail (requires registration).
