Artificial Intelligence and Cyber Fraud Prevention in Digital Banking: A Comparative Legal Analysis of India, the United Kingdom and the United States

The increasing use of artificial intelligence (AI) in digital banking has transformed the detection and prevention of financial fraud. Machine-learning algorithms, behavioural analytics, biometric authentication and automated transaction-monitoring systems enable financial institutions to identify suspicious activities at a scale that conventional rule-based systems may not achieve. However, the same technological developments have created new legal challenges, including algorithmic opacity, discriminatory outcomes, privacy risks, false-positive transaction blocking, and uncertainty concerning responsibility for AI-assisted decisions. Simultaneously, cybercriminals increasingly exploit AI to facilitate impersonation, phishing, synthetic identities and fraudulent payment instructions. This paper examines the legal and regulatory implications of AI-based cyber-fraud prevention in digital banking, with particular reference to India, the United Kingdom and the United States. It adopts a doctrinal and comparative legal methodology to analyse relevant cybercrime legislation, data-protection requirements, financial-sector regulation and institutional accountability. The paper argues that effective AI-based fraud prevention requires more than technological accuracy: financial institutions must also demonstrate lawful data processing, proportionate monitoring, appropriate human oversight, explainable decisions and accessible consumer remedies. It proposes a governance-oriented approach in which the deployment of AI is accompanied by documented risk assessments, independent validation, continuous monitoring and clear responsibility for adverse outcomes.