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Mining Framework w7.docx ITS- 632 Detection of Suspicious Transaction in Anti-Money La

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Mining Framework w7.docx ITS- 632 Detection of Suspicious Transaction in Anti-Money Laundering(AML) Using Data Mining Framework Intro to Data Mining (ITS- 632) University of Cumberlands Abstra... ct Today, money laundering has become a major threat for financial institutions and also to the country. These criminal activities are becoming more sophisticated and seem to have shifted from drug trafficking to terrorist financing and personal gain will not be forgotten. Many international financial institutions continue to implement anti-money laundering solutions to combat investment fraud. Data mining methods have been developed recently and are considered as an appropriate strategy to identify money laundering activities. A joint venture aimed at developing a new solution for anti-money laundering units at the International Investment Bank provides a simple and effective solution based on data mining to combat money laundering. This document discusses a solution that works as a tool and proposes some data mining techniques for money laundering. Introduction Money laundering is the act of inserting income into assets through unrecognizable crimes amid fraudulent offenses while hiding the source of the money. Identifying suspicious financial transactions is a necessity and a key element in the fight against money laundering. These types of criminal activities seem to be becoming more sophisticated and have shifted from the grip of drug trafficking to terrorist financing and, of course, personal gai. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . . [Show More]

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