| With the China’s economy keep developing,the control of government agencies on economic operation is constantly improving,so money laundering activities are no longer able to rely on the traditional way,but turn to the direction of diversification,complexity and concealment.Money launderers usually transfer illegal profits through various channels to legitimize them nominally,and no matter how they are transferred,they cannot escape commercial banks as the intermediary of capital turnover.From the point of view of maintaining the national economic order,commercial banks are an indispensable part of the crime of money laundering.As for banks,they should strengthen their anti-money laundering ability in order to avoid the systemic risks that money laundering may bring or to fulfill their social responsibilities.This thesis takes G Bank as an example to analyze its anti-money laundering work.Firstly,the internal control is analyzed,and it is found that there are defects in organizational structure design,unreasonable post setting,low efficiency of assessment system and other problems.Secondly,by enumerating anti-money laundering cases involving G Bank,problems in daily anti-money laundering practice caused by problems in the internal control system are enumerated.The specific manifestations are poor accuracy of customer identification information,low efficiency of monitoring large and suspicious transactions and the existence of professional moral hazard of employees,etc.Finally,this paper analyzes in detail the customer money laundering risk assessment table currently used by G Bank and points out its shortcomings.First,lack of differentiation.Risk subitems including the age of natural person customers and the duration of non-natural person customers are not applicable to enterprises or individuals;Second,the regional risk weight ratio is too large.As a regional urban commercial bank,G Bank has a high concentration of customers and business areas,and the regional risk score is almost the same.If the weight ratio is too large,it will lower the weighted calculation result and underestimate the money laundering risk.In view of the above problems,this paper,through the analytic hierarchy process,first designated the four types of risks in the customer money laundering risk assessment table as the first-level indicators,and the risk sub-items under them as the second-level indicators,and then issued questionnaires to solicit expert opinions to obtain data.Finally,a comparison matrix is constructed after the importance of regional risk is reduced to calculate the weight of each risk subitem applicable to individuals and enterprises after adjustment.After analyzing the existing problems,this thesis puts forward the optimization suggestions.First,strengthen internal control.Improve the organizational structure of antimoney laundering,set up a professional anti-money laundering team,set up full-time posts,and revise the assessment system of anti-money laundering work.Second,improve daily practical work.Improve the effectiveness of customer identity information identification,enhance the identification of large and suspicious transactions,strengthen the cultivation of anti-money laundering awareness,and create a good anti-money laundering atmosphere.Third,adjust customer money laundering risk assessment table.The relative importance of reducing regional risk in assessing customer money laundering risk was also subdivided in customer money laundering risk assessment table.Fourth,expand anti-money laundering work.The use of scientific and technological means to assist anti-money laundering monitoring,at the same time to increase publicity,improve customer anti-money laundering literacy.The above strategies can not only optimize the anti-money laundering work of G Bank,but also provide reference for other commercial banks with similar size and institutional system,so as to improve the overall anti-money laundering level of China’s banking industry,maintain the stable operation of the financial system and ensure national economic and social security. |