Attacking Identity Theft and Fraud with Analytics
According to a recent study there was a increase of more than 500,000 fraud victims to 13.1 million people in 2013, the second highest number since the study began.
Analytics that separate the real person from the fraudster using someone else’s name help provide maximum protection against identity theft. Our sources of credit, collections, and other private data, combined with your data that identifies past fraudulent activity can be run through specific analytics designed to effectively help predict true-name identity fraud.
Modeling and real-time analytics help identify suspicious activity or inconsistent information about applicants and returning users that helps predict identity fraud. When the modeling identifies suspicious activity, you can use targeted out-of-wallet questions or launch other risk-based security rules, to verify whether a request is coming from who it should be.
More prevalent, but a bit easier to spot, are fake identities created using a combination of real and fabricated information. Research has shown that these synthetic fraud scams account for over 80% of the identity fraud committed. Good data and fast analytics that can compare the made-up identities to correct information can prevent synthetic identity fraud before it gets into your system.
Detection happens best with analytics that are fast and effective. According to Equifax case studies, it is possible to capture 70 percent of the identity frauds, while only stopping 10 percent of the entire population for manual review. Working together, the predictive data sources, analytics, and technology thwart fraudsters like never before.
In the fight against fraud, there is no “cookie cutter” approach for lenders. Often the best strategy involves multiple layers of defenses. With the right mix of fraud mitigation tools, you not only minimize losses, you also improve compliance and staff productivity. That mix should include identity screening, verification and authentication tools that work in real time to minimize losses from various types of fraud.
To learn more about Equifax predictive analytics and flexible decisioning solutions for fraud prevention, contact us.
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