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Web Startup Sniffs Out E-Commerce Fraud Sift Science is a cloud-based service that tracks consumer e-commerce behavior patterns and assigns every user a "fraud score."

By Kristan Schiller

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The aliases were giving Listia's six-person tech team fits. An online marketplace and auction site based in Mountain View, Calif., Listia entices new customers to shop by giving them 500 credits as soon as they sign up. Predictably, there are users who abuse the offer. "All you need is a bunch of e-mail addresses," says co-founder Gee Chuang. "And you could sign up for a bunch of new accounts, with each account having [the] free credits."

The Fix
Enter Sift Science. Its cloud-based service tracks consumer e-commerce behavior patterns and assigns every user a "fraud score" that recognizes patterns of fraudulent behavior. "Most e-commerce businesses have only one engineer to defend themselves," says Jason Tan, co-founder and CEO of the San Francisco-based company. "We said, 'Why not build a third-party solution and make it available to the world?'"

Sift Science's algorithms constantly adapt to fraudsters' changing tactics, updating statistical models in real time--a process Tan calls "machine learning." In less than two months since offering its program to the public in March of this year, Sift had logged more than 1 million fraud patterns and variables in its database.

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