Chatbots and Conversational AI in Banking: Assessing Operational Efficiency and Customer Trust

Abstract

The integration of chatbots and conversational AI in the banking sector represents a major shift toward digital service delivery, aimed at enhancing operational efficiency and improving customer experience. This study examines the relationship between chatbot-induced operational efficiency, customer trust, and overall satisfaction from a project management perspective. Using a structured questionnaire, data were collected from 400 banking customers who have interacted with chatbot services. Reliability analysis confirmed the internal consistency of the instrument (Cronbach’s Alpha = 0.808). Pearson correlation analysis revealed a strong positive relationship between operational efficiency and customer trust (r = 0.602, p < 0.01). Further, multiple regression analysis demonstrated that operational efficiency and customer trust significantly predict overall user satisfaction and intent to use, explaining 55.7% of the variance (R² = 0.557). These findings underscore the importance of efficient system design and trust-building in project planning and execution. The study contributes to the field of project management by emphasizing that technological success in banking is not solely measured by cost and time metrics but also by user perception and adoption.