基于大数据技术的商业银行反洗钱风险识别“穿透”研究

Research on Penetration of Anti-Money Laundering Risk Identification of Commercial Banks Based on Big Data Technology

从国内商业银行反洗钱工作面临的现状和挑战出发,通过回溯近年来国内外对于反洗钱监测识别方法的相关研究成果,结合目前最新的国际反洗钱监管要求标准,通过搭建反洗钱大数据综合分析平台,完善客户尽职调查,并通过引入人工智能中的复杂股权关系路径算法和自然语义分析算法,有效识别企业的最终受益人(UBO),实现风险“穿透”,促使商业银行反洗钱领域核心竞争力的提升。

This analysis starts from the current situation and challenges faced by domestic commercial banks in anti-money laundering.With reviewing the relevant research results of anti-money laundering monitoring and identification methods at home and abroad in recent years,and combining the latest international regulatory standards for antimoney laundering,a comprehensive analysis platform for anti-money laundering big data is urgently needed for improving customer due diligence.We should also effectively identify the ultimate beneficiary(UBO)of the enterprise to realize risk"penetration"and promote the core competitiveness of commercial banks in the field of anti-money laundering through introducing the complex equity relationship path of AI(Artificial Intelligence)and NPL(Natural Language Processing).