Recently, PYMNTS sat down with an array of experts and innovators in the artificial intelligence (AI) field to get their thoughts on how the technology will transform the payments and commerce sectors in the years ahead.
Not surprisingly, a multitude of ideas and predictions were shared detailing how AI will enhance information gathering, workflows, corporate governance and more.
When asked specifically how AI could improve efficiencies in financial services, Akli Adjaoute, founder and general partner at venture capital fund Exponion, said financial institutions (FIs) will benefit by using AI in their AML (anti-money laundering) and fraud prevention efforts.
Adjaoute is correct: The future is here. As PYMNTS Intelligence’s data confirms, AI is already proving to be a tool of choice for FI executives looking to combat money laundering, bank fraud and other illicit activities.
As our report, “Financial Institutions Revamping Technologies to Fight Financial Crimes” — which was created in collaboration with Hawk AI — revealed, financial crimes are on the upswing. More than 40% of FIs surveyed say incidents of fraud are increasing, and 7 in 10 told us they now are using AI and machine learning (ML) to fend off fraudsters.
AI and ML make up only a portion of the tools bank executives rely on to fight fraud. Of the 10 North American FIs we surveyed, all say they rely on a mixture of in-house fraud prevention systems, third-party resources and new technologies to protect their institutions and customers.
But that mixture varies from one institution to the next.
For instance, when it comes to alerting customers about questionable transactions, half of the FIs surveyed develop 50% or less of their alert technologies in-house, while 30% develop more than half in-house. Only 20% create those tools entirely in-house.
Regardless of which fraud-fighting technologies they are asked about, this pattern is similar with most FIs saying they use a fluid mix of in-house and third-party developments. (The biggest exception is call center-based multifactor authentication, which is primarily outsourced.)
Ninety percent of FIs surveyed say they use fraud prevention application programming interfaces (APIs) to mitigate fraud; 80% deploy adaptive authentication and web-based multifactor authentication. But AI and ML technologies continue to gain ground.
Seventy-one percent of FIs now use both AI and ML in their fraud-fighting efforts, and this finding is in line with an ongoing trend. Last September, when PYMNTS Intelligence compiled 2023’s “The State of Fraud and Financial Crime in the U.S.,” 66% of banking executives reported using AI and ML to combat fraud, which was up from 34% in 2022.
But developing AI and ML tools can be costly, which explains why only 14% of FIs say they build their own fraud-fighting AI and ML technologies. Nearly 30% say they rely entirely on third-party vendors to provide these tools. Similarly, just 11% of FIs develop their own APIs in-house, while 22% rely entirely on third-party API solutions.
These percentages reflect another pattern in the report: FIs are increasingly integrating third-party technologies into their fraud-fighting efforts. Eighty percent say they use both in-house resources and third-party technology to identify and mitigate fraud. The remaining 20% prefer integrating third-party technology rather than developing their own.
Two key takeaways stand out in “Financial Institutions Revamping Technologies to Fight Financial Crimes.” One, AI and ML continue to win over industry executives who are seeking effective fraud-prevention tools. Two, while some FIs use in-house technologies, far more leverage third-party solutions.
This trend will likely continue. Those third-party fraud prevention vendors who wish to stand out in the coming months will be those that can point to a track record of successfully developing AI and ML-powered fraud prevention tools.
