Abstract

The rapid integration of financial technology (FinTech), particularly through data science and artificial intelligence (AI), has revolutionized traditional banking systems by improving operational efficiency, enhancing customer satisfaction, and optimizing risk management processes. This study examines the transformative role of AI and data science in key banking operations, including fraud detection, credit scoring, customer service, risk management, and regulatory compliance. Results demonstrate significant improvements in customer satisfaction, fraud detection accuracy, and credit scoring precision, with AI-driven systems reducing processing times and operational costs across various banking functions. Specifically, fraud detection accuracy increased by up to 25%, credit scoring models improved by up to 27%, and regulatory compliance costs were reduced by up to 40%. These findings underscore the potential of FinTech solutions to not only streamline traditional banking operations but also offer enhanced security and tailored services. Despite the benefits, challenges such as data privacy, transparency, and workforce adaptation remain critical considerations for widespread AI adoption in banking