• Annalize Seebacher
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eBook - Eliminating False Positives in Fraud Management

How to use machine learning to manage fraud and risk and power the next generation of customer experience.

It could have happened to anyone. She brought the extended family together, took everyone out to a fancy dinner in the big city, and insisted on picking up the tab. She’d just landed her dream job, and this was her chance to show everyone she’d made a success of herself. She didn’t expect to have to ask someone else to pay because her credit card was declined. It wasn’t her fault; her account was in good standing.

But the out-of-the-ordinary transaction triggered an alert, a rule kicked in, and the charge was blocked. The experience was horrible.

Incidents like this are far too common. When a false positive happens, it’s a sign something’s broken in an organization’s fraud prevention system. Good
customers should never be punished for good behavior, and good companies should never lose trust—or business—because of a poor-performing fraud solution.

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