Machine learning a growing force against online fraud - Paul McCloskey, GCN

A group of ex-Google employees has started a company that wants to expand the use of big data to spot fraud — a blight that costs taxpayers over $125 billion a year, and affects public-sector agencies involved in payments, collections and benefits — before it occurs. San Francisco-based Sift Science says it has developed an algorithm that uses machine-learning techniques to stay ahead of new fraud tactics as they are introduced into its customers’ networks. “Many anti-fraud technologies follow a set number, maybe 175 to 225 rules, against which to measure user behavior,” Sift Science co-founder Brandon Ballinger told GigaOm. “The problem is fraudsters don’t follow the rules and change all the time.” http://gcn.com/articles/2013/03/26/sift-science-machine-learning-anti-fraud.aspx