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Today, money laundering poses a serious threat not only to financialinstitutions but also to the nation. This criminal activity is becoming moreand more sophisticated and seems to have moved from the clichy of drugtrafficking to financing terrorism and surely not forgetting personal gain.Most international financial institutions have been implementing anti-moneylaundering solutions to fight investment fraud. However, traditionalinvestigative techniques consume numerous man-hours. Recently, data miningapproaches have been developed and are considered as well-suited techniques fordetecting money laundering activities. Within the scope of a collaborationproject for the purpose of developing a new solution for the anti-moneylaundering Units in an international investment bank, we proposed a simple andefficient data mining-based solution for anti-money laundering. In this paper,we present this solution developed as a tool and show some preliminaryexperiment results with real transaction datasets.

A data mining-based solution for detecting suspicious money laundering cases in an investment bank