Treasury report uncovers major AI fraud prevention gaps.


According to a report from the U.S. Treasury, larger financial institutions have an advantage over smaller ones in AI-related fraud prevention due to access to more historical data. The report highlights the need for better collaboration among financial institutions to share data for training anti-fraud AI models.

Key points:

  • Larger financial institutions have an edge over smaller ones in AI-related fraud prevention.
  • Better collaboration among financial institutions is needed to share data for training anti-fraud AI models.

The report emphasizes that there is a significant gap in data available to financial institutions for training AI models, specifically in fraud prevention. Smaller FIs lack the internal data and expertise needed to develop their own anti-fraud AI models, while bigger institutions have more historical data to work with. The lack of data sharing among FIs limits the ability to aggregate fraud data for use in AI systems. The report also discusses the cost of developing AI and ML tools, with only a small percentage of FIs building their own fraud-fighting technologies.

Additionally, the article touches on the importance of combining technology with critical thinking when dealing with financial crime. The need for a “Robocop, not Terminator” approach, which involves a combination of human expertise and machine intelligence, is highlighted.