关键词: 反洗钱, 模式识别, 行为特征, 聚类方法

Abstract: Aiming at money laundering through financial institutions, the combination of intelligence information technology and KYC Standard provides a new way for anti-money laundering work to increase the recognition rate of suspicious client. To apply the pattern recognition technology to anti-money laundering field, a clustering based method for client transaction behavior pattern recognition is proposed to identify the suspicious client who has the abnormal transaction behavior through judging whether the client transaction behavior pattern is normal. The experimental results verify the feasibility and validity of the method.

Key words: clustering method, anti-money laundering, pattern recognition, behavior character