Integrating Natural Language Processing (NLP) in AML Compliance and Monitoring

Abstract

The integration of Natural Language Processing (NLP) technology in Anti-Money Laundering (AML) compliance and monitoring is a critical area of research in the financial industry. This paper explores the role of NLP in enhancing AML compliance processes, automating data extraction, and improving the detection of suspicious activities in financial transactions. Through a comprehensive review of existing literature, the benefits of integrating NLP technology for improved AML monitoring are highlighted. Various applications of NLP in AML compliance, such as customer risk profiling and regulatory reporting, are discussed. The impact of NLP on AML compliance efficiency and case studies on NLP solutions for AML monitoring are presented to provide insights into the potential of NLP technology to streamline compliance procedures and enhance monitoring efficiency. The findings underscore the importance of leveraging NLP technology to strengthen AML compliance efforts and address the evolving challenges in the digital age.