Sequence matching for suspicious activity detection in anti-money laundering

Xuan Liu, Pengzhu Zhang, Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations

Abstract

Developing effective suspicious activity detection methods has become an increasingly critical problem for governments and financial institutions in their efforts to fight money laundering. Previous anti-money laundering (AML) systems were mostly rule-based systems which suffered from low efficiency and could can be easily learned and evaded by money launders. Recently researchers have begun to use machine learning methods to solve the suspicious activity detection problem. However nearly all these methods focus on detecting suspicious activities on accounts or individual level. In this paper we propose a sequence matching based algorithm to identify suspicious sequences in transactions. Our method aims to pick out suspicious transaction sequences using two kinds of information as reference sequences: 1) individual account's transaction history and 2) transaction information from other accounts in a peer group. By introducing the reference sequences, we can combat those who want to evade regulations by simply learning and adapting reporting criteria, and easily detect suspicious patterns. The initial results show that our approach is highly accurate.

Original languageEnglish (US)
Title of host publicationIntelligence and Security Informatics - IEEE ISI 2008 International Workshops
Subtitle of host publicationPAISI, PACCF, and SOCO 2008, Proceedings
Pages50-61
Number of pages12
DOIs
StatePublished - Jul 1 2008
EventIEEE International Conference on Intelligence and Security Informatics, ISI 2008 Workshops: PAISI, PACCF, and SOCO 2008 - Taipei, Taiwan, Province of China
Duration: Jun 17 2008Jun 17 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5075 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherIEEE International Conference on Intelligence and Security Informatics, ISI 2008 Workshops: PAISI, PACCF, and SOCO 2008
Country/TerritoryTaiwan, Province of China
CityTaipei
Period6/17/086/17/08

Keywords

  • Anti-money laundering
  • Euclidean distance
  • SARs
  • Sequence matching
  • Suspicious activity detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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