Abstract
The applying of data mining techniques in banking is growing significantly. The volume of transaction data in banking is huge and contains a lot of useful information. Detecting money laundering is one of the most valuable information which we can discover from transaction data. This paper will propose the approaches on money laundering detection techniques by using clustering techniques (a technique of data mining) on money transferring data of banking system. Besides, we present an implemented system for detecting money laundering in Viet Nam’s banking industry by using CLOPE algorithm.
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© 2012 Springer-Verlag Berlin Heidelberg
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Cao, D.K., Do, P. (2012). Applying Data Mining in Money Laundering Detection for the Vietnamese Banking Industry. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28490-8_22
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DOI: https://doi.org/10.1007/978-3-642-28490-8_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28489-2
Online ISBN: 978-3-642-28490-8
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