The Research On Applying Intelligent Data Classification Algorithm To Assess The Money Laundering Risks Of Bank Client

Application of information technology in the financial field, at the same time accelerating the operation of economic activities, but also to the financial monitoring has brought many difficulties. This makes money-laundering crimes increasingly rampant after year 2000 when the network era began.Money laundering usually relates to conceal the illegal source and nature of those revenue generated through the drug-related crimes, Mafia-type organized crimes, terrorist crimes, smuggling or other illegal proceeds of crimes by various means of business deal. The behavior does serious harms to society. But the traditional manual review is no longer practical under today's technology environment. And the traditional rule based system is also compatible to the changing situation.To face the problem, governments around the world are all in the development of an intelligent anti money-laundering systems. Our country's research and development in this area has entered a second generation, which will adopt a large number of artificial intelligence technologies. Based on the fact of current academic researches, system on money laundering risk assessment using customer information needs some attentions. In this dissertation we make the use of three intelligent classification technologies in data mining area for the upper question, which are logistic regression, neural networks and support vector machine. We will describe in detail the theory of algorithms, data process and implementation process in the dissertation and analyze the advantages and disadvantages of various algorithms. Some suggestions on building a real system component are also provided.