Financial Crimes Enforcement Network AI System (FAIS) Identifying Potential Money Laundering from Reports of Large Cash Transactions

  • Ted E. Senator
  • Henry G. Goldberg
  • Jerry Wooton
  • Matthew A. Cottini
  • A. F. Umar Khan
  • Christina D. Klinger
  • Winston M. Llamas
  • Michael P. Marrone
  • Raphael W. H. Wong

Abstract

The Financial Crimes Enforcement Network (FIN-CEN) AI system (FAIS) links and evaluates reports of large cash transactions to identify potential money laundering. The objective of FAIS is to discover previously unknown, potentially high-value leads for possible investigation. FAIS integrates intelligent human and software agents in a cooperative discovery task on a very large data space. It is a complex system incorporating several aspects of AI technology, including rule-based reasoning and a blackboard. FAIS consists of an underlying database (that functions as a black-board), a graphic user interface, and several preprocessing and analysis modules. FAIS has been in operation at FINCEN since March 1993; a dedicated group of analysts process approximately 200,000 transactions a week, during which time over 400 investigative support reports corresponding to over $1 billion in potential laundered funds were developed. FAIS's unique analytic power arises primarily from a change in view of the underlying data from a transaction-oriented perspective to a subject-oriented (that is, person or organization) perspective.
Published
1995-12-15
How to Cite
Senator, T. E., Goldberg, H. G., Wooton, J., Cottini, M. A., Khan, A. F. U., Klinger, C. D., Llamas, W. M., Marrone, M. P., & Wong, R. W. H. (1995). Financial Crimes Enforcement Network AI System (FAIS) Identifying Potential Money Laundering from Reports of Large Cash Transactions. AI Magazine, 16(4), 21. https://doi.org/10.1609/aimag.v16i4.1169
Section
Articles