Analytics Magazine Analytics Magazine, November/December 2014 - Page 2

Ins ide story Fighting fraud with analytics A day doesn’t seem to go by without a new report of fraud via stolen identity and misappropriated credit card numbers, Internet and phone scams, good, old-fashioned employee embezzling and officialdom corruption, you name it. Is the world really crawling with fraudsters? Perhaps so. According to the Report to the Nations on Occupational Fraud and Abuse – a 2014 global fraud study – the typical organization loses 5 percent of revenues each year to fraud, which, if applied to 2013 estimated gross world product, translates to a potential projected global fraud loss of nearly $3.7 trillion. That’s some serious malfeasance. The Report also reports that 22 percent of fraud cases result in losses of at least $1 million, and many of the victims – individuals and organizations, large and small – never fully recover or, in the case of some companies, go out of business. Two articles in this issue of Analytics take a closer look at the enormous worldwide problem of fraud and explain how big data, analytics and pattern recognition are effective tools in curbing the $3.7 trillion crime. In their article “Employing big data and analytics to reduce fraud,” Drew Carter and Stephanie Anderson of AlixPartners point out that fraud doesn’t play favorites; it’s a multi-industry problem, noting 2 | a n a ly t i c s - m a g a z i n e . o r g that retail, transportation, manufacturing and telecom are all prone to fraud, along, of course, with the banking and financial sectors. Carter and Anderson go on to spell out the keys for employing analytics for proactive fraud monitoring. Warns Carter and Anderson: “Sinister schemes one can’t even imagine are happening because no one knows to look for them. Once they are uncovered and observed, their patterns can be “built into” rules-engines.” Meanwhile, in his article “Real-time fraud detection in the cloud,” Saurabh Tandon of Mu Sigma explores real-time fraud detection in the cloud, and how his company built a fraud detection framework that had up to 250 unique variables pertaining to the demographic and financial history of the financial client’s customers. Writes Tandon: “A cloud-based ecosystem can enable users to build an application that detects, in real time, fraudulent customers based on their demographic information and prior financial history.” Analytics alone can’t stop the worldwide crime spree, but it’s clearly entered the anti-fraud fight, and more and more organizations have seen it packs a powerful punch. – Peter Horner, editor peter.horner@ w w w. i n f o r m s . o r g