ROLE OF ARTIFICIAL INTELLIGENCE IN FINTECH VS TRADITIONAL BANKING: A COMPARATIVE ANALYSIS OF DECISION-MAKING EFFICIENCY AND RISK ASSESSMENT MODELS

Abstract

Artificial Intelligence (AI) has transformed the global financial sector by improving operational efficiency, customer experience, fraud detection, and risk management. FinTech companies have rapidly adopted AI-driven technologies to automate financial services, while traditional banks continue to integrate AI into existing banking infrastructures. This research paper presents a comparative analysis of the role of AI in FinTech and traditional banking with special emphasis on decision-making efficiency and risk assessment models. The study examines how AI-based systems enhance credit scoring, fraud detection, predictive analytics, customer relationship management, and investment decisions. It further evaluates the differences in technological adaptability, operational flexibility, regulatory compliance, and customer trust between FinTech firms and traditional banks. The findings indicate that FinTech institutions demonstrate greater agility and innovation in AI implementation, whereas traditional banks possess stronger regulatory frameworks and customer confidence. The paper concludes that the future of financial services will depend on the successful integration of AI technologies with robust governance and ethical financial practices. Keywords: Artificial Intelligence, FinTech, Traditional Banking, Risk Assessment, Decision-Making Efficiency, Machine Learning, Financial Technology, Banking Innovation, Predictive Analytics.