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.

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DOI: http://dx.doi.org/10.1609/aimag.v16i4.1169

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