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The money made from illegal activities is a main threat to the global economy. If the overall welfare of the people is wanted to be increased the money laundering activities should be stopped. Many software packages which aim to detect suspicious transactions are developed and available commercially. These solutions are mostly rule based. That is a list of suspicious transactions is generated where their suspiciousness is determined by some rules. If these lists are too long, it would be very difficult to inspect them in full but if they are kept shorter then there is the risk of failing to inspect an actually fraudulent transaction. To overcome this drawback of the rule based solutions, we suggest a two phase anti money laundering system which provides more flexibility with the use of data mining.
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