Abstract
Artificial Intelligence (AI) is reshaping the financial sector by revolutionizing decision-making, strengthening risk management, and enhancing fraud detection frameworks. Traditional financial systems, reliant on rule-based models, are increasingly being replaced by AI-powered predictive analytics, machine learning, and robotic process automation (RPA). Globally, AI applications are estimated to reduce fraud-related losses by 40% and optimize risk forecasting with greater accuracy (McKinsey, 2022; PwC, 2023). In India, AI adoption has accelerated in banking, insurance, and fintech ecosystems, particularly in areas such as credit scoring, anti-money laundering (AML), and digital payments. Drawing upon secondary data from RBI, World Economic Forum, KPMG, and academic studies, this paper examines how AI contributes to secure, efficient, and data-driven financial decision-making. The study identifies both opportunities and challenges, including issues of data privacy, algorithmic bias, regulatory uncertainty, and workforce displacement. Findings suggest that AI enhances accuracy and transparency in financial operations, but its benefits can be fully realized only through responsible adoption supported by explainable AI models, ethical governance, and regulatory clarity. The paper concludes with recommendations for policymakers and institutions to strengthen sustainable and inclusive AI integration in India’s financial landscape.