Artificial intelligence (AI), including machine learning and generative AI, is transforming financial services by improving customer engagement, credit assessment, risk management, fraud detection, and operational efficiency. Its growing deployment, however, also creates material concerns relating to data protection, operational resilience, market integrity, cybersecurity, and model governance. Against this background, the Reserve Bank of India constituted the Committee on the Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) to formulate a comprehensive framework for responsible AI adoption in the financial sector. The Committee’s Report advances seven guiding “Sutras” and six strategic pillars. The pillars combine innovation enablement through infrastructure, policy, and capacity with risk mitigation through governance, protection, and assurance. This paper undertakes a comparative legal and policy analysis of the FREE-AI recommendations alongside the regulatory approaches of the European Union and Singapore. It uses a doctrinal and comparative method to examine their respective approaches to AI governance, accountability, transparency, consumer protection, data governance, audit, and innovation across the AI lifecycle. The comparison identifies convergences in governance, transparency, and consumer protection, but differences in regulatory design and implementation. The analysis finds that the FREE-AI framework seeks to balance financial innovation with safeguards for fairness, explainability, security, and systemic stability. While the European Union adopts a more prescriptive, risk-based regime and Singapore relies substantially on principles- and guidance-based supervision, the Indian framework offers a sector-specific, phased model designed to support responsible deployment by regulated entities. The paper argues that its effectiveness will depend on clear supervisory standards, institutional capacity, reliable data governance, and robust assurance mechanisms.