The US Treasury has announced machine learning AI is being used as part of its fraud detection process, helping it save a record amount of money for the department.

Through this, the department claims to have recovered over $4 billion in improper payments, and $1 billion of that is said to be as a direct result of the machine learning AI that identifies likely instances of check fraud.

Also included, the department claims to have prevented $2.5 billion by identifying and prioritizing high risk transactions, and by expanding risk-based screening which resulted in $500 million in prevention.

Enhanced capabilities

Government departments across the country are adopting AI in their processes. For example, the Nevada state employment department is using AI in the benefit appeals process, which critics say could be less effective but just as time consuming.

Recent reports have revealed AI has made financial fraud significantly easier, so using AI to combat criminals does seem to be the natural next step.

“Treasury takes seriously our responsibility to serve as effective stewards of taxpayer money. Helping ensure that agencies pay the right person, in the right amount, at the right time is central to our efforts,” said Deputy Secretary of the Treasury Wally Adeyemo.

The AI process are likely inspired by similar fraud detection used in the banking industry, which the Treasury department has been quietly utilising for the last two years.

This is likely to be just the start of a new era of machine bureaucracy, as the Treasury and Department of Labor announced a data-sharing partnership,

“We will continue to partner with others in the federal government to equip them with the necessary tools, data, and expertise they need to stop improper payments and fraud.” added Adeyemo.

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