TY - JOUR AU - Senator, Ted E. AU - Goldberg, Henry G. AU - Wooton, Jerry AU - Cottini, Matthew A. AU - Khan, A. F. Umar AU - Klinger, Christina D. AU - Llamas, Winston M. AU - Marrone, Michael P. AU - Wong, Raphael W. H. PY - 1995/12/15 Y2 - 2024/03/28 TI - Financial Crimes Enforcement Network AI System (FAIS) Identifying Potential Money Laundering from Reports of Large Cash Transactions JF - AI Magazine JA - AIMag VL - 16 IS - 4 SE - Articles DO - 10.1609/aimag.v16i4.1169 UR - https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/1169 SP - 21 AB - 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. ER -