Trustworthy Chatbots in Finance: A Framework For Explain Ability, Accessibility, and AI Governance

Abstract

The integration of AI-powered chatbots into the banking sector has transformed how financial institutions engage with customers, streamline operations, and enhance security. While early chatbot implementations focused on automation and convenience, modern systems must now meet higher expectations in terms of transparency, accessibility, regulatory compliance, and ethical alignment. This research investigates the current limitations of banking chatbots and proposes an expanded framework for developing intelligent, inclusive, and secure conversational AI systems. Key areas explored include the application of explainable AI for decision transparency, design strategies for accessibility and inclusive interaction, mitigation of algorithmic bias, and compliance with global data protection laws. The study also examines the role of adaptive learning, voice interfaces, and blockchain in enhancing user trust and operational integrity. Through a synthesis of technical best practices and ethical considerations, this paper provides actionable recommendations for developers and banks to build chatbot ecosystems that are not only efficient but also responsible and future-ready.