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Artificial intelligence is breaking the economics of the traditional accounts payable fraud model. Attackers can scale cheaply, but finance teams cannot respond by scaling manual verification at the same rate.

“They are using the technology that’s out there, the AI, every tool available to them in order to make their attempts bigger, broader, faster,” Katie Elliott, senior risk and fraud officer at Bottomline, told PYMNTS during a discussion for the PYMNTS B2B Payments Event 2026, “Stopping B2B Fraud Before AI Moves the Money.”

That threat reality is turning supplier verification from a back-office control into infrastructure.

“Cybercriminals used to be more targeted. Now they can do mass spamming, mass phishing,” Elliott said.

For CFOs, the emerging problem is not just detecting more fraud but finding a verification model that can scale economically with the risks of corporate payments.

The existing situation, on paper, looks like a steep hill for finance teams to climb. Fraudsters can afford thousands of failures because only a handful of attempts need to work. Finance departments face the opposite constraint, they must evaluate more signals without slowing legitimate payments or adding armies of fraud analysts.

“Once you click that send button, once that payment is authorized, it can move in an instant,” Elliott said. A fraudster receiving the funds is “taking it out as soon as they can get their hands on it.”

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