Research On The Construction Of Bank Anti Money Laundering System Based On Clustering Mining Algorithm And Outlier Mining Algorithm

Money laundering is mainly the act of concealing the proceeds obtained in criminal activities,which encourages the vice of illegally obtaining money.The continuation of money laundering activities poses a huge threat to the management of the market financial order in the later stage,and causes great harm to the stable development of society.At present,money laundering is becoming increasingly large-scale and money laundering methods are becoming more and more intelligent,which brings great difficulties to banks' anti-money laundering work.Therefore,some algorithms are needed to identify suspicious money laundering behavior.In the bank's anti-money laundering system,it is necessary to select a reasonable data mining algorithm to better meet the needs of anti-money laundering work.This paper mainly studies the construction of bank anti-money laundering system based on clustering mining algorithm and outlier mining algorithm.It describes the writing background of this topic and the current basic research status at home and abroad,and further clarifies the research theme of this article;expounds the data Related theories about mining and anti-money laundering provide theoretical support for this article;the application of clustering mining algorithms and outlier mining algorithms in bank anti-money laundering systems is analyzed,and the applicability of the two data mining algorithms is analyzed;Under the background of similar mining algorithms and outlier mining algorithms,a suspicious money laundering behavior recognition module is created,which is generally based on accidental suspicious money laundering behaviors and usual suspicious money laundering behaviors.The bank's anti-money laundering system is experimentally analyzed.The results were discussed.Through analysis,it is found that the cluster mining algorithm and the outlier mining algorithm have high applicability and can be used in the construction of anti-money laundering systems.Through experimental analysis,it is found that the cluster mining algorithm and the outlier mining algorithm can better identify suspicious money laundering behaviors,but some data is difficult to identify,so based on the importance of anti-money laundering work,it is necessary to make further improvements based on the actual situation.