A majority of North American financial institutions plan to invest in machine learning analytics to help combat fraud, according to a new report by global research and advisory firm Aite Group and authentication and fraud prevention technology provider Iovation.

It’s clear that the threat environment continues to escalate, the report said, and effective fraud prevention is an increasingly competitive issue for financial institutions. The study was compiled from interviews with 28 senior fraud and data analytics executives at 20 North American financial institutions. The interviews were conducted by Aite between August and September 2017.

“What this study highlighted is that those who are early adopters of advanced machine learning analytics will be able to greatly reduce fraud while also improving the customer experience, giving those [financial institutions] a decided edge over their competitors who lag in these advancements,” said Julie Conroy, research director for Aite Group’s Retail Banking & Payments practice.

Julie Conroy, Aite Group
Julie Conroy, Aite Group

“Data is the new currency, and creating intelligence from data at scale requires machine learning technology,” Conroy said.
With the omni-channel approach to consumer engagement in banking, there are several points of interaction for hackers to gain access to personal data, the report noted. This points to why institutions must embrace ML analytics to spot patterns and prevent fraud at each point of contact, with stronger and more convenient authentication measures that will ultimately improve the customer experience.

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Bob Violino

Bob Violino

Bob Violino is a freelance technology and business writer who covers a variety of topics, including big data and analytics, cloud computing, information security and mobile technology.