Money laundering behavior recognition was a process of knowledge discovery in databases (KDD). Data Mining was an important technique of KDD. In this paper, the characteristics of Chinese foreign exchange money launde...
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Money laundering behavior recognition was a process of knowledge discovery in databases (KDD). Data Mining was an important technique of KDD. In this paper, the characteristics of Chinese foreign exchange money laundering activities, and combine decisiontree approach with financial domain knowledge were analyzed. The suitable money laundering transaction recognition strategy and method were chosen. By making full use of the real transaction data to carry on the experiment, useful rules of money laundering were discovered. Experimental results on SAS demonstrated that our algorithm could be extremely useful in money laundering recognition.
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