Balancing Code And Constitution: A Doctrinal–Empirical Analysis Of AI Driven Banking Fraud Detection, Regulatory Accountability, And Customer Rights In India

Lokendra Patel; Dr. Priyanka Gupta

doi:10.29284/13fx0b09

Authors

Lokendra Patel Research Scholar, Nims School of Law, Nims University, Jaipur, Rajasthan
Dr. Priyanka Gupta Associate Professor, Nims School of Law, Nims University, Jaipur, Rajasthan

DOI:

https://doi.org/10.29284/13fx0b09

Keywords:

Artificial Intelligence, Banking Fraud Detection, Customer Rights, Regulatory Accountability, Data Protection, India.

Abstract

The Indian banking industry has been rapidly digitizing, which also results in the successful implementation of a system based on artificial intelligence (AI) to detect fraud, monitor transactions, and risk profile. The technologies have the potential to increase efficiency, speed, and accuracy in detecting fraudulent transactions, especially as the amount of digital payments grows and cyber-enabled financial crimes are observed. Nevertheless, the implementation of opaque, data-intensive, and automated decision-making systems has also become a matter of serious legal and constitutional issues concerning the rights of the customers, regulatory responsibility, and data security in India.

The paper reviews the major research issue that the AI-based banking fraud detection systems in India comply sufficiently with technological efficiency and constitutional principles, including privacy, constitutional procedural fairness, and constitutional equality. The proposed research will (i) examine the current regulatory and legal framework that can be used to regulate AI in banking fraud detection, (ii) evaluate the implication of algorithmic decisionmaking on the rights of customers and (iii) explore the level of institutional and regulatory responsibility in the implementation of such systems.

The research takes a doctrinal-empirical approach in terms of which a doctrinal analysis of constitutional principles, banking regulations, data protection norms, and judicial precedents are carried out, which is supplemented by an empirical investigation of the trends in customer grievances and institutional activity in regard to automated fraud control measures. The results suggest that there is an increasing regulatory dependence on AI that is not matched by any corresponding transparency, explainability, and effective redressal structures, leading to an increase in the risks of marginalization, inaccuracy, and rights abuse. The paper contributes to the norm by suggesting a rights-based and accountability-focused AI governance in the banking industry model. It ends with policy and regulatory copulations to increase transparency requirements, customer mobilization and align AI-led financial mapping with constitutional and rules of law standards in India.

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