Sequence Matching for Suspicious Activity Detection in Anti-Money Laundering

Author:

Liu Xuan,Zhang Pengzhu,Zeng Dajun

Publisher

Springer Berlin Heidelberg

Reference18 articles.

1. U.S. Congress, Information technologies for the control of money laundering. Office of Technology Assessment, Report OTA-ITC-630, U.S. Government Printing Office, Washington, DC (1995)

2. Liu, X., Zhang, P.: Research on Constraints in Anti-Money Laundering (AML) Business Process in China Based on Theory of Constraints. In: Hawaii International Conference on System Sciences, Proceedings of the 41st Annual, p. 213 (2008)

3. Force, F.A.T.: Report on Money Laundering Typologies, 2000-2001 (2002) English ed. Accessed

4. Senator, T.E.: Ongoing management and application of discovered knowledge in a large regulatory organization: a case study of the use and impact of NASD Regulation’s Advanced Detection System (RADS). In: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 44–53 (2000)

5. Goldberg, H., Senator, T.E.: Restructuring databases for knowledge discovery by consolidation and link formation. In: Proceedings of 1998 AAAI Fall Symposium on Artificial Intelligence and Link Analysis (1998)

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