Artificial Intelligence And Anti-Money Laundering Laws: A Legal-Tech Approach To Socio-Economic Crime Prevention

Written by: Abhinav Kumar, B.A.LL.B, Lovely Professional University, Punjab

Abstract

The spread of socio-economic crimes, especially money laundering has become a major risk to the financial systems across the globe. The current anti-money laundering (AML) systems are too reliant on manual monitoring and compliance frameworks that are rule-based and cannot detect complex and layered money transfers executed through advanced technologies. As digital financial systems have multiplied exponentially, artificial intelligence (AI) has emerged as a game-changer to enhance AML compliance, proactive detection, real-time monitoring, and risk-based profiling. In this paper, the author critically analyzes the convergence of AI and AML law, with emphasis on how it has been used in the fight against socio-economic crime. It examines legislation in India that regulates AML as envisioned by the Prevention of Money Laundering Act, 2002 (PMLA), and contrasts this with regulatory measures in the United States, with an eye towards FinCEN and artificial intelligence-based compliance procedures. Finally, the paper also addresses the ethical and legal consequences of AI adoption such as privacy, algorithmic responsibility, and the right to due process. The paper, using a conceptual and analytical lens, finds gaps in the current legal framework and presents a roadmap on how AI-based solutions can be incorporated into the Indian AML framework with balancing between innovation and ethics. The results underscore the importance of a coordinated international approach that integrates technology and strong legal controls to achieve transparency, accountability and financial integrity within an ever more digital economy.

Keywords: Artificial Intelligence, Anti-Money laundering, Socio-Economic Crimes, Financial Fraud, Legal-Tech, Compliance, Privacy, Ethical AI.

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