Generative AI in Banking and Financial Services: Opportunities, Challenges, and Future Directions
Abstract
Generative Artificial Intelligence has emerged as a disruptive technology capable of revolutionizing banking and financial services through intelligent automation, conversational finance, synthetic data generation, and personalized customer experiences. This review paper explores the role of generative AI models, including large language models (LLMs) and generative adversarial networks (GANs), in transforming modern financial ecosystems. The paper analyzes applications such as AI-powered financial advisory systems, automated report generation, fraud prevention, customer support chatbots, and algorithmic trading assistance. Through a comprehensive literature review, the study identifies key technological advancements, implementation frameworks, and adoption barriers across global financial institutions. Additionally, the paper investigates concerns related to privacy, hallucination risks, regulatory uncertainty, and ethical governance in AI-generated financial outputs. The findings suggest that while generative AI offers substantial operational and strategic benefits, effective governance frameworks and human oversight remain essential for sustainable adoption in financial services.
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