Bonfring International Journal of Industrial Engineering and Management Science

Online ISSN: 2277-5056 Print ISSN: 2250-1096 Frequency: 4 Issues/Year

Impact Factor: 0.541 | International Scientific Indexing(ISI) calculate based on International Citation Report(ICR)

Identification of Money Laundering based on Financial Action Task Force Using Transaction Flow Analysis System

Dr.G. Krishnapriya


Abstract
Money laundering transaction is to be identified in the real world financial application; a new method can be proposed for detection. In this system, a laundering detection is based on the social network using transaction flow analysis system wetop-quality an appropriate classifying strategy to determine typical money laundering patterns and money laundering rules. From that state, we can quickly identify the abnormal transaction data. A part of a larger chain transactions in money laundering is to be such risk. For to overcome that risk we use a social network to connect missing links in potential transaction sequences. A financial sector independent risk assessment can be provided to submit the transaction. The potential participants can be connected to a social network. The transformation of vast quantities of data into a huge number of reports is not a perfect detection for to overcome that we use a Transaction Flow Analysis. From distributive box and collective box, the transaction mining system is to detect the money laundering. In this system, we can also use a Financial Action Task Force (FATF) to avoid a money laundering. From social network analysis money laundering of terrorist financing. We can also detect the criminal activities involve in the money laundering. The FATF can provide a static assessment of money Laundering.
Keywords The Financial Sector, Money Laundering, Potential Transaction, Sequence Mining.
Volume 10
Issue 3
Pages 1-4
Issue Date September , 2020
Open Access
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