<![CDATA[Artificial Intelligence (AI) integration in India’s financial sector offers transformative potential but poses challenges like algorithmic bias, data privacy risks, and regulatory fragmentation. This study employed both one-on-one interviews and surveys with various stakeholders in the financial services sector to analyse India’s AI governance framework through expert interviews and a comparative policy analysis of global models (the EU’s risk-based AI Act and the US sector-specific guidelines). Findings reveal gaps in accountability, transparency, and enforcement mechanisms, particularly for high-risk applications like credit scoring. This study proposes a hybrid regulatory model that combines binding rules for high-risk AI systems (e.g., fraud detection) with co-regulation for low-risk tools, emphasising scientific risk assessment, consumer grievance mechanisms, and iterative policymaking. While leveraging India’s existing financial laws (e.g., Reserve Bank of India guidelines), we recommend AI-specific updates to address explainability, bias audits, and systemic risk monitoring. However, this study is limited by its reliance on publicly available regulatory documents and expert interviews, and by its focus on the Indian context, which may overlook cross-border AI governance challenges. Stakeholder collaboration and phased implementation are critical to balancing innovation with ethical safeguards in India’s evolving digital economy.]]>
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