The FinCEN Artificial Intelligence System: 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, and Raphael W.H. Wong, U.S. Department of the Treasury

The FinCEN* Artificial Intelligence System (FAR) links and evaluates reports of large cash transactions to identify potential money laundering. The objective of FAIS is to discover previously unknown, potential 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 (which functions as a blackboard), a graphical user interface, and several pre-processing and analysis modules. FAIS has been in operational use at FinCEN since March 1993 by a dedicated group of analysts, processing approximately 200,000 transactions per week, and during which time over 400 investigative support reports corresponding to over $1 billion in potential laundered funds have been developed. FANS unique analytical power arises primarily from a transformation of view of the underlying data from a transaction oriented perspective to a subject (i.e., person or organization) oriented perspective.

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