Enhancing anti-money laundering capabilities: The strategic use of AI and cloud technologies in financial crime prevention

Cedrick Agorbia-Atta * and Imande Atalor

Kelley School of Business, Bloomington, Indiana University, IN, USA.
 
Research Article
World Journal of Advanced Research and Reviews, 2024, 23(02), 2035–2047
Article DOI: 10.30574/wjarr.2024.23.2.2508
 
Publication history: 
Received on 12 July 2024; revised on 19 August 2024; accepted on 21 August 2024
 
Abstract: 
Integrating Artificial Intelligence (AI) and Cloud Technologies is transforming the fight against money laundering in the financial sector. As digital financial platforms become more prevalent, traditional Anti-Money Laundering (AML) methods are proving inadequate against increasingly sophisticated criminal tactics. This study examines how AI and Cloud Technologies can enhance AML capabilities by improving real-time threat detection, reducing false positives, and ensuring compliance with global regulatory standards. Through a qualitative analysis of recent literature and case studies, the research highlights the effectiveness of AI in identifying complex, suspicious activity patterns that traditional systems often miss. Cloud Technologies complement AI by offering scalable, flexible, and secure solutions, enabling financial institutions to manage evolving risks and regulatory demands better. The findings suggest that the strategic use of these technologies represents a significant advancement in financial crime prevention. However, the study also notes challenges, including concerns about data privacy and the need for specialized skills to manage AI systems. The conclusion emphasizes that while AI and Cloud Technologies provide powerful tools for enhancing AML frameworks, ongoing research, and development are needed to address these challenges and fully realize their potential in safeguarding the financial system. This strategic adoption of technology marks a critical shift in combating financial crimes, ensuring that financial institutions remain resilient against the dynamic threats from money laundering.
 
Keywords: 
Anti-Money Laundering (AML); Artificial Intelligence (AI); Cloud Computing; Financial Crime Prevention; Regulatory Compliance; Transaction Monitoring
 
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