Study On The Visualization Of Monitoring Of Abonrmal Capital Flow In Financial Intermediation Network System

Different kinds of abnormal capital flow in financing networks will bring risk to the financial institutions of each country, which not only makes the national wealth reduce and huge loss, but also makes various social unstable factors and crime rate on the rise. So we must strengthen monitoring and supervision of these various abnormal funds to ensure economic and social order stability of our country.In the abnormal capital flow monitoring system of financing network, it's out of the question to improve the efficiency of monitoring and detection facing large-value and suspicious payment transactions and complicated relationship among accounts reported by financial institutions. In addition, But the visualization software tools of complex network in present do not accommodate visualization requirements of financing network, because it is difficult to express various complicated characteristics and attributes of the financing network. However in reality the visualization research in abnormal capital flow of financing network is the key issue that concerned and supported to be solved in the future for both academic community and China anti-money laundering monitoring center.This paper studies the visualization based on the development of MapX component technology geographic information system (GIS), which has incomparable advantage comparing with other development methods. At present, the application of geographic information system has been more and more widespread, which plays a decision support role in application management and development of various industries and may cause it to become the trend and the hot spot in geographic information system development.This paper established the visualization systems of monitoring abnormal capital flow, which mainly focus on the visualization and algorithm of nodes and the main contents summarized as follows:(1) Summarize and analyze abnormal flow behavior of funds in financing network from the perspective of operability and practicability, which may facilitate implementation of computer information visualization and enhance analysis and monitoring capabilities to suspicious payment transactions data to make observers free from massive data and improve decision-making efficiency. (2) An algorithm for visual support based on MapX is implemented, including the following researches: a method for achieving financing network, the visualization layout of financing network and representation method of regional factors of intelligent nodes. This paper also breaks through the expressing number limitation of nodes and further completes the unlimited number expressing of node accounts in financing network, which not only may enlarge, reduction and drag arbitrarily similar to Google Earth, but also realize the preliminary graphical visualization to the account node, regional distribution visualization, and achieve localization and tracking to abnormal nodes. There is still another network visualization to display abnormal capital flow chain and more conductive to anti-money laundering decision; Finally, showing the geographical composition trade data on the map by means of MapX, thus make the observers understand mode and relationship of massive displayed information more quickly and simply.(3) Proposed a one-way movement bribery model based on the visualization system monitoring abnormal capital flow, which could calculate the flow among any two nodes, provide one train of thought for analyzing the deposited fund and is a further application in visualization.(4) This thesis conducts a more comprehensive analysis on movements of abnormal fund in terms of trading relations, social relations and capital stock three aspects. Then this paper analyzes the important function of the three aspects (especially the crucial role of social relations) in the process of anti-money-laundering decision-making in detail by taking Chen Shui-bian's family money-laundering case for example, which not only validates the theoretical research of this paper, but also provides a certain degree of technical support to anti-money-laundering decision makers.