In the seemingly never-ending war to protect their customers and institutions from fraud, an increasing number of financial institutions (FIs) are deploying machine learning (ML) and artificial intelligence (AI) tools to fight back.
And according to PYMNTS Intelligence’s “Leveraging AI and ML to Thwart Scammers,” a report created in collaboration with Hawk, those efforts appear to be working.
The report, which is based on surveys with 200 FIs with more than $1 billion in assets under management, revealed that those FIs that now use ML or AI to mitigate fraud are seeing steep declines in common forms of fraud.
For instance, tech support impersonation and IRS imposter scams are two of the most frequently reported scams, yet FIs using ML or AI anti-fraud solutions were 17% less likely to report experiencing these leading scams than FIs relying solely on more traditional fraud prevention tools. Likewise, they were 18% less likely to report IRS imposter scams as a top concern.
They also reported lower rates of lottery, romance, utility, rental and Social Security scams. In fact, as the figure illustrates, FIs leveraging the ML and AI technology reported lower incidents of nearly every common form of fraud.
The data also finds there is some room for improvement in both ML- and AI-based solutions. The tools were less successful in identifying charitable-donation scams. They also missed some fake debt-collection scams. This could be because these two scams are less common (and there would thus be less data for the solutions to work from).
Despite these small hurdles, FIs are apparently impressed. Fifty-two percent of the FIs we surveyed plan to implement or increase their use of ML or AI fraud prevention models. In fact, FIs using AI or ML are 17% more likely to have plans in place to implement additional ML or AI solutions than their counterparts that do not use ML or AI fraud prevention solutions. In other words, many of the FIs now using the advanced technologies are ready to expand their ML and AI tool chest.
Our study also found that by adopting ML or AI fraud-prevention models, FIs are not only stopping more bad actors from inflicting damage but also increasing the confidence their customers have that their accounts are protected. So, in turn, customer satisfaction rates are likely to increase as fraud levels decline.
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