Sift, a company that prides itself on "forgetting the rules to fight data fraud," has just closed an $18 million Series B round of funding led by Spark Capital, with participation from Max Levchin, Union Square Ventures and First Round Capital. Sift helps merchants identify credit card fraud in real time by monitoring data streams across a whole network of merchants. They achieve this by partnering an easy to understand user interface with a learning program that develops and increasingly refined ability to spot and stop fraud.
“Most fraud detection systems are based around rules,” founder Jason Tan told TechCrunch. “If the charge is more than $5,000, and from a Nigerian IP address, and the card has been rejected three times before, then the company won’t process the transaction. But we say ‘no rules, all data.’”
The rules-based method is less than wholly effective--identifying a range of 50 percent to 70 percent false positives Sift has the potential to bring that number down to 5 percent to 7 percent, relying on a computer's capacity to spot patterns in real-time and good old fashioned human intuition about certainly activities.
Apart from the $18 M in funding, Swift will additionally bring Spark Capital general partner Mo Koyfman onto its board. Sift's total fundraising to date is slightly over $23 million.
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