The rapid digital transformation of the banking sector has accelerated the deployment of artificial intelligence enabled conversational agents, commonly referred to as banking chatbots. These systems are increasingly used to automate customer service, enhance operational efficiency, and provide personalized financial assistance. Despite substantial investments by financial institutions, customer adoption of banking chatbots remains uneven across markets. Existing studies largely rely on traditional technology adoption frameworks and fragmented empirical investigations, limiting theoretical integration and conceptual clarity regarding adoption drivers. This narrative review synthesizes multidisciplinary literature to identify and classify the antecedents influencing banking chatbot adoption. Drawing from information systems, consumer behaviour, service marketing, and human-computer interaction literature, the study organizes adoption determinants into technological, psychological, social, risk related, and institutional dimensions. The review further highlights emerging constructs such as algorithmic trust, AI anxiety, perceived humanness, and transparency perceptions that extend beyond conventional models. The paper proposes an integrative conceptual framework and outlines future research directions to advance chatbot adoption research in digital banking ecosystems. The findings contribute to both academia and practice by offering a consolidated understanding of factors shaping customer acceptance of conversational banking technologies.