With the continuous deepening of global anti-money laundering efforts, big data technology has gradually become an important tool for financial institutions to enhance compliance management efficiency. This paper explores the application and challenges of big data technology in anti-money laundering compliance management, combining the current development trends of big data technology. By analyzing the practical applications of big data in data collection, suspicious transaction detection, and customer identity verification, this paper points out that big data technology has significant advantages in improving anti-money laundering efficiency, reducing manual monitoring pressure, and strengthening risk prediction capabilities. However, issues such as data quality, the complexity of technical implementation, regulatory constraints, and cross-border cooperation still pose key challenges to the comprehensive application of big data technology in the anti-money laundering field.
Jianfeng Yao (Mon,) studied this question.
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