July 6, 2016
‘Accidental’ revenue achieved from machine-learning fraud detection
Kathryn Cave from IDG Connect, interviewed Martina King to discover how machine learning fraud detection has the beneficial side effect of increasing revenue. “The thing that has surprised me,” Martina comments “is that I thought we’d be a fraud detection company. But we’ve become a revenue generating company.”
Generating revenue with machine learning fraud detection
Cave explores how existing rules-based fraud systems block more genuine customers than fraudulent activity, causing customer friction. Martina King explains how Featurespace’s ARIC engine uses machine learning technology to understand individual customer behaviour, and consequently accurately spots events that display out-of-character behaviour. The ARIC engine can more accurately spot fraud in real-time, while also reducing the number of genuine customers caught up in the fraud systems (“false positives”) by up to 70%.
Featurespace’s expertise in the area of machine learning fraud detection is being recognised by the global financial services and gaming industries. Earlier this year, Featurespace announced a partnership with TSYS, the leading US payments processor. The UK-based company also closed a funding round of $9 million this Spring, led by US Fintech investor TTV Capital.