FT: When Tech Negatives Begin To Outweigh Tech Positives
“ReD concludes a failure to account for these human (and economic) motivations encourages gaps of understanding regarding the best processes to use to combat the human phenomena. This makes perfect sense. What technologists often forget when trying to combat fraud with ever fancier algorithms, digital tools or grandiose consulting services is that better digital resilience doesn’t necessarily do much to solve the overarching problem, which remains a societal issue”
Exploring cyber crime, Izabella Kaminska of the Financial Times, found inspiration in a recent study on credit card fraud ReD Associates had undertaken together with Cognizant. Wanting to see how thick, contextual data could help inform algorithms, the two firms decided to explore the world of credit card fraud. What’s it like to be a credit card fraudster? And how can that understanding help build better fraud detection algorithms?
“The study revealed a David-and-Goliath portrait of a low risk and low barrier criminal system operating at an enormous scale — all below the radar of some of the most powerful institutions in the country and, in the minds of many fraudsters, without victims. Take, for example, Dillon, a self-proclaimed “black Robin Hood” we met in Harlem who runs a four-person fraud ring — buying high-value retail goods with the help of three to five “swipers” (discrete shoppers who fit a convincing customer profile for the targeted retailer), and then reselling those goods on a secondary discount market online and in person in his community. On a good day, Dillon’s team may make more than $10k in fraudulent bulk purchases of items from luxury clothing and shoes to liquor, baby clothes, and electronics. In Boston, we also met Donald, a specialist in hacking and fraudulent online purchases who sends deliveries to unoccupied properties he finds on Zillow for pickup. Donald’s purchasing, like that of Dillon’s physical shopping operations, is marked by a distinct speed and rhythm: faster website navigation than that of the typical consumer, progressively larger charges, and shopping at unusual times. The types of goods he purchases are a clear tip-off, too: men’s and women’s clothing, one-size-fits-all items, the same good in multiple sizes. While credit card fraud detection algorithms are attuned to some of these behaviours, like flagging the purchase of ten shirts in size L, they tend to miss Donald’s subtler efforts, like buying two shirts in every size in order to build a comprehensive inventory for warehousing and resale.”
The article can be read in full on FT.com here.