International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Artificial Intelligence for Anti-Money Laundering Compliance: Emerging Technologies, Explainability and Regulatory Perspectives

Author(s) M Ravi Kumar
Country India
Abstract Money laundering is a major financial and regulatory challenge that requires financial institutions to continuously monitor transactions, identify suspicious activities and comply with reporting obligations. Traditional rule-based anti-money laundering (AML) systems remain widely used but can generate large numbers of false-positive alerts, increase compliance costs and struggle to identify sophisticated and evolving patterns of financial crime. Artificial Intelligence (AI), including machine learning, deep learning, natural language processing, anomaly detection and graph analytics, offers opportunities to improve the efficiency and accuracy of AML compliance.
This research paper examines the role of AI in AML compliance with particular emphasis on emerging technologies, explainability and regulatory perspectives. The present analysis indicates that AI can improve transaction monitoring, anomaly detection, customer risk assessment and suspicious-activity identification. However, the adoption of AI also introduces challenges relating to explainability, data quality, privacy, bias, model governance, cybersecurity and regulatory accountability. Explainable Artificial Intelligence (XAI) is particularly important because AML investigators and regulators need to understand why a transaction or customer has been classified as high risk. The study proposes an integrated AI-enabled AML framework combining data integration, risk-based modelling, explainability, human oversight, continuous monitoring and regulatory governance. The research concludes that AI should complement rather than completely replace AML professionals and that responsible AI governance is essential for achieving effective, transparent and legally defensible AML compliance.
Keywords Artificial Intelligence, Anti-Money Laundering, Machine Learning, Explainable AI, Transaction Monitoring, AML Compliance, Regulatory Technology.
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-09
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E-ISSN 2582-2160
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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