The Anti-money Laundering System Based On Hadoop Platform

After years of development, information systems in the banking industry has gradually matured, and has accumulated a large amount of data resources, is a very valuable customer resources. With the diversity of data, the amount of data the rapid growth of unstructured data is not only a demand, but also is a new challenge of the banking system. Hadoop provides distributed storage, parallel computing technology to provide the excellent solution. Not only effective solution to the problem of unstructured data storage, but also by large data platform to extract data from the mass of useful information, data analysis and data mining technology in the banking sector.This paper focuses on how to use the key technology platform based on Hadoop HDFS and Map Reduce to develop anti-money laundering systems. Hadoop platform uses key technologies includes a linear extension, server clusters, parallel computing,scheduling, compression. Through non-functional test, Hadoop reflects the superiority of performance. On this basis, the bank’s anti-money laundering file constructs are divided into data base layer, data processing layer, rule processing layer and data application layer. The main module includes HDFS file storage system module, Map Reduce development environment module, Hive language module,Oozie scheduling module. In theoretical innovation, this paper also realized the data mining algorithm Apriori association how to transplant on Hadoop platform, detailing the mining association data based on Map Reduce parallel algorithm design and programming processes. By parallel data mining algorithms related mining rules suspicious transactions for anti-money laundering system to identify money laundering provides the basis to judge.As competition Intensifying, the application of information technology has become an important way to establish their superiority in the future, data mining technology will continue to highlight its importance of the bank. Through the analysis and research of this topic, the author combines work, hope this makes it necessary for banks to obtain information and knowledge, not only can effectively avoid financialrisks, regulatory obligations to complete the financial institution, but also in the near future to guide future business banking market.In the end, the ideas and practices of the whole paper were summarized, and finding the application prospects data analysis and mining of development in the banking industry.