GovExec Editor-In-Chief Frank Konkel speaks with Chief Strategy Officer for the SSA Office of Inspector General Chad Bungard at the GovExec Government & AI Summit Sept. 15. Zaid Hamid/Nextgov/FCW

Artificial intelligence is helping to fuel more effective benefits fraud, according to a top official with the Social Security Administration’s watchdog, but federal agencies should also leverage the new technologies to better deter would-be scammers from pilfering government funds. 

During a discussion at the GovExec Government & AI Summit on Tuesday, Chad Bungard — the chief strategy officer at SSA’s Office of the Inspector General — warned that “AI is changing the game in terms of fraud threats,” which is requiring investigators to also change up their prevention efforts. 

“The government is looking towards AI to fight fraud, and the criminals are looking towards AI to commit fraud,” he said. “And so, they're doing this in a variety of ways … but agencies need to stay on top of it. They need to use AI tools. They need to get better insight into what's going on and keep up with the evolving fraud.”

Bungard cited a May 2024 report from Deloitte’s Center for Financial Services that estimated that generative AI could be responsible for roughly $40 billion in fraud by 2027. One reason for this costly projection, he said, is the development of more advanced models that fraudsters can use in their scams.

He pointed to cases in which SSA, as well as other agencies and the private sector, have had to combat increasingly complex instances of direct deposit diversion fraud, in which scammers use AI chatbots to convince operators that they are their intended victims by sharing personal data collected from the dark web, and then diverting funds to a different bank account. In another example, Bungard said fraudsters have been using AI to create legitimate-seeming SSA documents, which can include the names of real agency or OIG officials, to scam individuals. 

Bungard said SSA and the agency’s watchdog have taken some steps to crack down on AI-driven fraud. He noted that, in 2023, SSA and its OIG formed an AI fraud subcommittee — co-chaired by both himself and the agency’s chief AI officer — that meets every quarter to discuss AI use cases that are in development or already deployed, as well as “compliance with administration priorities, laws, rules and regulations.”

Although Bungard said the watchdog is pushing to “put the onus on the agency to prevent and detect AI fraud,” he cautioned that “I don't think [SSA] is there on agentic AI yet” when it comes to new capabilities that it can leverage in its fraud detection and prevention toolbox. 

“I think they are hoping to develop some AI use cases there,” he said, adding that it’s “something that they're trying to get a hold of.”

Bungard’s comments come amid the White House’s ongoing push to crack down on federal fraud. President Donald Trump signed an executive order in March that created a new anti-fraud task force charged with rooting out waste, fraud and abuse across federal benefits programs.

In line with that effort, Bungard said officials are “trying to move away from pay-and-chase to a proactive model to protect the Social Security programs that serve millions of Americans.”

That mindset, in particular, aligns with fraud prevention efforts at the Centers for Medicare and Medicaid Services, which has been increasingly turning to AI to deter scammers. 

Kim Brandt, CMS’ deputy administrator and chief operating officer, previously told Nextgov/FCW during a March interview that her agency was leveraging AI tools in its Fraud Defense Operations Center to “detect spikes or aberrancies in current claim submissions” — efforts that, she said, have resulted in over $2 billion in agency savings.

In a brief interview with Nextgov/FCW following his panel, Bungard said the watchdog has been engaging with CMS on some of the ways they have been working to combat fraud, as well as with other agencies on their respective prevention efforts. He said, however, that CMS’ use of AI is “a very specific model that worked for them.”