An Application Research On Key Node Discovery Within Network In Anti-money Laundering

Financial crime is one of the thorniest issues in financial industry, because money-laundering activities are becoming increasingly rampant, it's a serious threat to the global economic development and national security. Currently money-laundering network is increasingly large and complex and diverse, how to identify the critical nodes of money-laundering networks, effectively combating money-laundering crime, anti-money laundering has become a major topic. In response to this problem, through link discovery technology based on suspicious transactions network, suspicious transactions network nodes importance measure to be effective in identifying suspicious transactions of key network nodes.Social network analysis theory, the method that researching importance of the nodes there are two main categories: First is the social network analysis method that the node will "importance" equivalent to "significant" will not undermine the integrity of the network and usually do not consider the importance of the node sets; The second is to delete nodes research methods, nodes will "importance" equivalent to "destruction after the deletion of nodes on the network", actually consider the plan before and after the deletion of nodes connected to the changes in conditions. Based on the network destructive perspective, presents a suspicious key network nodes link discovery without guidance: Importance Measurement for the Node within Non-weighted Network Algorithm base on node removed method. Quantification of the calculation the impact of network connectivity status after a network node removed, as an important node, in order to identify the key network nodes.Based on Network Node Important Measurement Algorithm Base on Node Removed Method, presents Importance Measurement for the Node within Node-edge Weighted Network Algorithm (IMN Algorithm). This is suspicious network key nodes link discovery with guidance, It solves the current research has not yet come to the node-edge weighted network nodes importance of the measure; By introducing weights transaction losses attenuation coefficient and the weights transactions loss function, Algorithm makes a better scalability and adaptability. IMN Algorithm avoids that the results of node within non-weighted network removed is not very reliable, it's more accurate under the guidance of the field knowledge.Under this approach, we applied IMN Algorithm to analysis of suspicious transactions intelligent monitoring system, and validated the effectiveness of the method through the actual data.