Combatting Fraud with AI
The Treasury Department has identified various challenges in the financial sector related to artificial intelligence (AI). These challenges include the lack of consistency in defining AI across the industry, uncertainty regarding future AI regulation in financial services, and the potential for regulatory fragmentation.
The report also emphasizes the impact of AI on fraud prevention within financial institutions. While AI technologies are reshaping fraud, they are also equipping defense teams with tools to enhance their anti-fraud measures. One example cited in the report is a large firm that developed AI models using internal data, leading to a 50 percent reduction in fraud activity.
However, the ability to develop these fraud prevention models is limited to larger financial institutions with substantial resources and access to internal data. Smaller institutions lack the necessary data, expertise, and resources to create their own models, thereby creating a gap in fraud prevention capabilities. The Treasury Department expresses concern that fraud activity prevented by models at larger institutions may shift to smaller ones lacking the same capabilities.
The report highlights the lack of fraud information sharing among financial firms, especially for smaller institutions. It suggests the need for a fraud data clearinghouse that facilitates rapid sharing of data and supports institutions of all sizes. The absence of such a platform disproportionately affects smaller institutions and undermines overall fraud prevention efforts.