Data mining in anti-money laundering field

Noriaki Yasaka

Journal of Money Laundering Control, 2017, vol. 20, issue 3, 301-310

Abstract: Purpose - This report aims to focus on how suspicious transaction report is created with data mining methods and used from the point of view of knowledge management. Design/methodology/approach - This paper considers data mining versus knowledge management in the anti-money laundering (AML) field. Findings - In the AML field, the information and knowledge gained are not necessarily used for or shared with the related shareholders. Creating and co-evolving the network of “knowledge professionals” is the impending assignment in this industry. The first and most important task is knowledge management in the global AML field. Originality/value - The report considers the creation with data mining methods and utilization from the point of view of knowledge management.

Keywords: Knowledge management; Community; Anti-money laundering; Data mining; HS-KCSU model (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jmlcpp:jmlc-09-2015-0041

DOI: 10.1108/JMLC-09-2015-0041

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