This paper presents a comprehensive analysis of an artificial intelligence-driven (AI-driven) conceptual framework to generate value from the data in the banking industry. The study provides a literature review to investigate the challenges of an AI-driven conceptual framework in the banking industry. Data quality management, data privacy and security, infrastructure capability, data governance and regulatory compliance, and talent and expertise have been identified as challenges. Based on a systematic review of the literature, this paper proposes Exploration, Classification, Protection, and Value (ECPV) and Explore, Understand, Act, and Engage (EUAE) as key parts of a conceptual framework driven by artificial intelligence to get value from data in the banking industry. The ECPV and EUAE address the identified challenges and offer a structured methodology for managing an AI-driven conceptual framework in the banking industry. It emphasizes the exploration of data sources, classification based on sensitivity and relevance, implementation of comprehensive data protection and privacy measures, and value extraction from data using artificial intelligence approaches. By using an AI-driven conceptual framework called Explore, Understand, Act, and Engage (EUAE) for customer-centric analytics, we give customers a full picture of their bank account activity and more control over how they manage their money. This improves customer engagement by giving customers insights and suggestions. © 2023 IEEE.