Generative AI Applications in Customizing User Experiences in Banking Apps

In recent years, the banking sector has undergone a radical transformation driven by advancements in Artificial Intelligence (AI), particularly Generative AI technologies. With the growing expectations of digital-savvy customers, traditional banking interfaces are no longer sufficient to provide the level of personalization and engagement users demand. Generative AI models, such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs), have the potential to revolutionize how financial institutions interact with users by dynamically customizing content, services, and interfaces based on individual preferences and behavioral patterns. This paper explores the application of Generative AI in designing personalized user experiences in mobile and web-based banking applications. It investigates the working principles, architectural designs, and implementation strategies required to leverage synthetic content generation, natural language processing, and multimodal AI to create hyper-personalized financial services. Additionally, it examines case studies from leading banks, analyzes the effectiveness of these technologies in increasing user engagement, and discusses the ethical and regulatory considerations surrounding user data and content generation. The paper concludes with insights on future enhancements, including emotion-aware personalization, cross- platform customization, and the integration of Generative AI with voice banking interfaces.