| With the accelerating process of globalization and integration,the frequency of capital flow is accelerating,and the crime of money laundering is rampant,which seriously endangers China’s economic order and financial security.As an important channel of capital circulation and an important link in the whole money laundering chain,commercial banks are facing a severe situation of anti-money laundering.With the rapid development and wide application of IT technologies such as big data and cloud computing,human society has irreversibly entered the era of big data.The era of big data has brought profound changes to various industries and brought great opportunities and challenges to the anti-money laundering reform of China’s commercial banks.Based on the research theory of risk management,taking commercial banks as the research object and combined with the actual situation of anti-money laundering work of commercial banks,this paper will discuss how to apply big data technology to improve the anti-money laundering prevention and control system.Firstly,this paper explains the risk management theory,information asymmetry theory and social computing theory used in the topic selection,and briefly introduces the connotation of related concepts such as money laundering,anti-money laundering and financial big data.On this basis,taking bank A as the research object,this paper analyzes and discusses the current situation of its anti-money laundering obligations.From the perspective of regulatory punishment,taking the regulatory ticket received by bank a as a warning,combined with the interview results and data access,this paper analyzes the deficiencies and problems existing in bank A’s anti-money laundering work from the dimensions of risk identification,risk assessment,risk monitoring and risk control.Then it compares and analyzes various practical practices of the banking industry in developed countries in using big data to carry out anti-money laundering,so as to draw advanced work experience.Finally,based on the concept of big data application,this paper puts forward improvement strategies for improving the anti-money laundering prevention and control system of bank A,including strengthening the identification of money laundering risk by building a unified and standardized big data warehouse,building a cross industry big data platform,using data verification to strengthen the governance of customer identity basic data and other measures;Optimize the money laundering risk assessment system by improving the customer money laundering risk assessment model and building an online product money laundering risk assessment system;Improve the level of anti-money laundering monitoring and analysis by using big data mining and analysis technology to develop anti money laundering intelligent analysis,optimize anti-money laundering monitoring system tools,and cultivate compound talent team;Improve the money laundering risk control mechanism by using big data technology to build an integrated risk customer control system,improve the cross line information sharing mechanism,strengthen training and improve the awareness of all staff in money laundering risk prevention and control. |
