By Ken Musante
Napa Payments and Consulting
AI is fantastic! The use cases are endless, and therein lies the problem. Fraudsters appreciate the ease it allows them to infect the internet and steal data. Cybercriminals are able to multiply their subterfuge exponentially. Every week, there's a new way to falsify documents or create a fake back story.
Consequently, the good guys need to up their arsenal, fortify every transaction and identify the bad actors and threats—all in real time while minimizing false positives. Banks and processors must upgrade outdated technology with AI-driven solutions built on modern technology stacks.
We need not look far for justification. This year alone, major data breaches occurred at AT&T, Ticketmaster, Change Healthcare and, ironically, at online background check and fraud prevention service National Public Data.
AI’s ability to train and learn has helped reduce false positives while throttling the onslaught of fraud attacks. Visa and Mastercard are in an arms race with fraudsters, and they have the war chest to fund it. Both card networks made recent acquisitions in the space. Visa stated it will acquire Featurespace, a developer of real-time artificial intelligence payments protection technology that prevents and mitigates payments fraud and AML risks. Visa expects the acquisition will complement and strengthen its portfolio of fraud detection and risk-scoring solutions.
Mastercard, in turn, expanded its cybersecurity services with an agreement to acquire Recorded Future. Recorded Future provides real-time visibility into potential threats by analyzing multiple data sources. The acquisition expands Mastercard’s existing collaboration with Recorded Future on an artificial intelligence service that alerts banks when a credit or debit card has likely been compromised.
The card networks need to solve both the merchant-side payment transaction fraud and issuer-side account takeover and fraudulent application. They both must also eliminate money laundering through transaction monitoring. Ideally, the data will be harnessed from one side to train the models on the other. A risk based, machine learning rules engine is only as good as the data the model is digesting.
Herein lies the issue. Acquirers and merchants need data from issuers to hone their transaction monitoring, and issuers need transactional data to ferret out money laundering. That’s why even though we are in an arms race and Visa and Mastercard have the largest war chest, they will need to continue to buy companies and solutions.
Individually, companies will not be able to keep up. Fraudsters and their schemes are too dynamic and the datasets too large. Even the largest companies will have competing road maps that will prevent them from staying at the fore.
Visa and Mastercard understand this and will continually buy tools to avail to their clients. Like most card brand solutions, however, they will be good but watered down and blind to corner cases. I expect the next and greatest to emanate from smaller companies, building on existing infrastructure.
Some former associates from my WePay days started Coris, a risk scoring and fraud platform designed to assist fintechs and payfacs evaluate and monitor merchants. While Coris is a fraction of the size of Visa and Mastercard, it is the type of firm that will engineer the solution. It will do this by utilizing the anonymized data from both publicly available databases and proprietary data sources. The Coris team will know the data better because they were operators. They will build AI driven models to surpass the fraudsters.
Other competitors like Middesk, Signifyd, Sardine, Agreement Express and BankIQ have developed their own solutions. Each will pursue a solution set and strive to increase the value of their dataset and efficiently serve it to their clients. When I was a child, my grandfather stopped a purse snatcher in San Francisco. He yelled, "Freeze or I’ll blow your brains out!’" He didn’t have a gun, but his bluff was successful in subduing the perpetrator.
Unfortunately, we are past the days when perpetrators run away from the crime scene. Today they disguise themselves to look like every other customer, and we are reliant on multiple data points from a multitude of data sets, trained by risk operators to thwart fraud while not inconveniencing the rest of us.
As founder of Humboldt Merchant Services, co-founder of Eureka Payments, and a former executive for such payments innovators as WePay, a division of JPMorgan Chase, Ken Musante has experience in all aspects of successful ISO building. He currently provides consulting services and expert witness testimony as founder of Napa Payments and Consulting, www.napapaymentsandconsulting.com. Contact him at kenm@napapaymentsandconsulting.com, 707-601-7656 or www.linkedin.com/in/ken-musante-us.
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