Boston, April 13, 2017 – Machine learning analytics is one of the biggest buzzwords in fraud prevention, but there is a lot of substance behind this particular buzzword. Fraud is moving too fast for legacy approaches, and global financial institutions and merchants need advanced analytics technology to keep up. Machine learning is proving quite effective, but as it’s the marketing slogan du jour, it means many different things to many different people.

This report cuts through the vendor hype and marketing fluff to help readers truly understand the use of machine learning in the fraud mitigation arena. Based on 28 interviews with fraud analytics vendors as well as FI and merchant fraud executives from October 2016 to March 2017, it puts forth a definition of the technology, maps various vendor approaches, and describes concrete use cases and proof points that illustrate its value.

This 18-page Impact Note contains seven figures and four tables. Clients of Aite Group’s Fraud & AML service can download this report, the corresponding charts, and the Executive Impact Deck.

This report mentions Amazon, BioCatch, Brighterion, ClearSale, DataVisor, Easy Solutions, Equifax, Experian, Feature Analytics, Featurespace, Feedzai, FICO, First Data, Forter, Guardian Analytics, IBM, ID Analytics, InAuth, iovation, iSoft, LexisNexis Risk Solutions, Mastercard, NuData, Oracle, Pindrop Security, Radial, Risk Ident, Riskified, RSA, SAS, Sift Science, Signifyd, Simility, ThetaRay, ThreatMetrix, TransUnion, Vesta, Visa, and Wipro.