In Wired today, Ex-Googlers Train Machine Army to Sift Out Crooks:
Here’s a tidbit for the online retailers out there: If a shopper on your website is using Firefox with Windows XP, the odds of him being a fraudster go up sixfold.
That’s a trend mined by the machine learning geeks at Sift Science, a San Francisco startup that’s taking some of the same techniques that Google uses to cut down on abuse on its ad network and making them available to smaller websites, such as Airbnb, Uber, and Listia. All three of these are early customers.
“The point of this is really to make online commerce safer and more efficient,” says Brandon Ballinger, Sift’s founder and chief technical officer. “Machine learning lets you adapt to the different fraud patterns you see on different websites.”
Sift Science, a Y Combinator-backed startup founded by former Google engineers, is today launching its fraud-fighting service based on machine learning – a system designed to adapt to the ever-changing techniques used by criminals online. The company is also announcing $4 million in Series A funding, led by Union Square Ventures. As a part of the funding, Union Square’s Albert Wenger is joining the company’s board.
Sift Science had previously raised $1.5 million in seed funding, bringing its total raise to $5.5 million.
Other investors in Sift Science include Max Levchin (PayPal, Slide, Affirm), Chris Dixon (SiteAdvisor, Hunch), Marc Benioff (Salesforce CEO), First Round Capital, Y Combinator, Founder Collective, SV Angel, Start Fund, Alex Rampell (SiteAdvisor, TrialPay), Kevin Scott (AdMob, Google, LinkedIn), Lee Lindon (Karma Science, Facebook), Harj Taggar (Y Combinator), Garry Tan (Posterous, Y Combinator), Alexis Ohanian (Reddit, Y Combinator), and Rich Barton (Zillow, Expedia).
Read the full article on Techcrunch, and additional coverage in Wired, The Next Web, VentureBeat, GigaOm, AllThingsD, and Silicon Valley Business Journal
Use Sift Science now to catch fraudsters using machine learning on your website »