The US Treasury has announced that it is using machine learning artificial intelligence as part of its fraud detection process, which will help save a record amount of money for the department.
Through this, the department claims to have recovered more than $4 billion in improper payments, and $1 billion of that amount is said to be a direct result of machine learning AI identifying potential cases of check fraud.
Also included is that the department claims to have prevented $2.5 billion by identifying and prioritizing high-risk transactions and expanding risk-based screening, resulting in $500 million in prevention.
Enhanced capabilities
Government departments across the country are adopting AI into their processes. For example, the state of Nevada's employment department is using AI in the benefits appeal process, which critics say could be less effective but would be just as time-consuming.
Recent reports have revealed that AI has significantly facilitated financial fraud, so using AI to combat criminals seems like a natural next step.
“Treasury takes seriously our responsibility to serve as effective stewards of taxpayers' money. Helping ensure that agencies pay the right person, in the right amount, at the right time is critical to our efforts,” said Treasury Undersecretary Wally Adeyemo.
The AI process is likely inspired by similar fraud detection used in the banking industry, which the Treasury Department has been quietly using for the past two years.
This is likely just the beginning 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 tools, data and expertise needed to stop improper payments and fraud.” Adeyemo added.