November 2, 2017
As the number of online transactions increases significantly along with the amount of stolen data available to criminals, all kinds of fraud affecting online merchants and banks (e.g., card-not-present fraud, account takeover fraud, synthetic fraud, etc.) are rising as well. Solutions based on artificial intelligence and machine learning, which are being developed by a new vanguard of antifraud technology providers, are becoming a competitive advantage for the businesses that implement them, according to a recent report from Boston-based consultancy Aite Group.
The report, which focuses on adoption of the technology by issuers, found that retail ATO was cited by more FIs than any other type of fraud as the biggest factor driving investment in machine learning fraud prevention technology. Aite conducted interviews with executives at 20 financial institutions based in North America and found 65 percent said the priority of investing in machine-learning technologies for fraud use cases is “very high.” Thirty-five percent called machine learning moderately important and not one said it was a low-priority investment.
“Effective fraud prevention is now a competitive issue for FIs,” says Aite Group Research Director Julie Conroy. “Early adopters of advanced analytics are able to increase their fraud detection, and the associated improvements to the customer experience give them a decided edge over their competitors that lag in these investments.”
Of the banks that participated in the Aite study, 40 percent said they have a machine-learning-enabled platform for fraud prevention already deployed and another 10 percent have an implementation in progress. Twenty percent said such a platform is 1-to-2 years out and 30 percent had no plans to implement one at all.