Machine learning part of Minnesota Gov. Walz’s anti-fraud legislation package

A new legislative package would build on Minnesota's efforts to curtail fraud across its social safety-net programs.

February 27, 2026

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Minnesota Gov. Tim Walz speaks during a press conference at the State Capitol building on Jan. 5, 2026 in St. Paul, Minnesota. (Stephen Maturen / Getty Images)

Minnesota Gov. Tim Walz introduced a comprehensive legislative package on Friday aimed at combating fraud in Minnesota’s state programs, including the use of predictive analytics and machine learning to identify suspicious transactions earlier in the application process.

The package, which builds on the state’s larger effort to curtail the fraud of government assistance programs that was rampant during the COVID-19 pandemic, features directives to improve detection and oversight of the programs. It specifically names the use of artificial intelligence tools, such as predictive analytics and machine learning, to identify suspicious billing.

It includes mandates to bolster the investigative authority of the state’s Bureau of Criminal Apprehension and its newly created Financial Crimes and Fraud Section, and to increase criminal penalties for those found defrauding Minnesota’s government programs.

Along with improving fraud detection and oversight through the use of AI, officials said the package would strengthen program integrity in managed care organizations, which deliver health services, primarily for Medicaid recipients. It would will also expand audit and internal control capacity to ensure funds are properly spent, and that any misused dollars are recovered.

The package would prohibit legislatively named grants — meaning lawmakers would no longer be allowed to hand-pick specific organizations to receive grant money. Instead, the package would require groups to participate in competitive processes for grant dollars to ensure fairness and transparency.

In addition to broadening the authority of the state’s BCA Financial Crimes and Fraud Unit, the proposal would also establish a centralized Office of Inspector General to lead statewide fraud prevention, set standards and refer cases for civil or criminal enforcement. Other caveats include expanding the authority for on-site investigations across Minnesota health care programs — including the allowance of authorities to investigate providers who have not yet billed claims — and enhancing capacity for fraud prevention at the state’s Department of Revenue and within the Attorney General’s Medicaid Fraud Unit.

The proposal comes after Minnesota has faced heightened scrutiny from the Trump administration for its handling of welfare fraud. Walz in January of 2025 announced several efforts to reduce fraud against the state’s assistance programs, including an experimental AI pilot. Tarek Tomes, the state’s outgoing chief information officer, also shared last summer that AI would be a key part of the state’s fraud prevention program.

“Fraud steals from the people of Minnesota and undermines the programs we all rely on,” Walz said. “This package strengthens oversight, improves detection, expands enforcement, and increases penalties to protect every dollar Minnesotans depend on. We’ve followed the experts, audits, and proven roadmaps; now it’s time for the Legislature to act.”