Keywords : AI-driven banking fraud; comparative financial regulation; Regulation E; Payment Systems Regulator; Reserve Bank of India; legal transplants; algorithmic accountability; fintech governance

Abstract : Generative artificial intelligence has altered the way banks are defrauded, though not, in most jurisdictions, the legal text that governs it. This paper offers a comparative doctrinal analysis of the legal and regulatory framework for AI-driven banking fraud in India, the United States, and the United Kingdom against four benchmarks: coverage (whether legal definitions capture AI-specific fraud mechanisms), attributability (whether liability can be fixed on a human actor or institution when AI is involved), enforceability (whether investigative and supervisory tools can handle AI-mediated evidence), and proportionality (whether penalties and remedies match the harm AI-enabled fraud causes). Applying these benchmarks to primary law, regulatory instruments, and decided and pending case law, the paper finds that no jurisdiction scores strongly on all four. The United Kingdom leads on coverage and enforceability but is only partial on attributability and proportionality; the United States is strong on enforceability but unsettled on the other three; and India is weak on enforceability and proportionality while, like the United States, untested rather than deficient on coverage and attributability. The paper argues that the binary of a 'reactive' India against 'proactive' Western comparators is misleading: the three jurisdictions are converging on a sectoral, regulator-led model and differ chiefly in the institutional durability of their rule-making processes, not in the protectiveness of the rules those processes produce.

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