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Data Science is Key to Protecting Banks & People from Credit Fraud #ExperianStories

Published: April 2, 2017 by Editor In United States

Arielle_Caron

Spanish Translation

I’m a Senior Product Manager in Experian’s Fraud and Identity Solutions department, which means I partner with data scientists to protect banks and their customers from fraud.

When most people think of fraud, they envision someone trying to open a bank account in someone else’s name. However, it wasn’t until I did a series of customer visits with big banks to understand their struggles and discovered a pervasive form of fraud in the finance industry called “bust-out” fraud.

In a “bust-out” fraud, an individual applies for a credit card in their own name, establishes a normal usage pattern and builds a solid repayment history. Then, when they’re ready to execute their scam, they max out all their available lines of credit from various lenders, disappear and leave the banks with the losses.

Meanwhile, the money could be funneled into funding many types of organized crime, from human trafficking to drug trading and other illicit activities. What makes this type of crime all the harder to identify and catch before it occurs is that the person applying for a credit card is who they say they are. So it’s not about identity theft.

To address this issue, my team and I created a solution called BustOut ScoreSM. We began by reviewing data from different banks to identify patterns where bust-outs occurred. From there, we built a score that predicts the likelihood that an individual will execute the scam — months before the scam occurs.

Our clients now use this tool both when opening new accounts and as part of account management. The tool flags suspicious-looking accounts, which our team then manually reviews to evaluate if the account is truly at risk for a bust-out. If it is, we work with our clients to freeze or close out those suspicious accounts.

Finding solutions to a fraud problem that hasn’t been solved is probably my favorite part of the job. I love seeing products that solve real issues affecting real people come to life — from inception to launch.

Helping protect people from identity theft and fraud is what gives me purpose and meaning in my work. I am proud to use the power of data as a force for good.

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