AN SEM-BASED ANALYSIS OF CUSTOMER TRUST AND ACCEPTANCE OF BANKING CHATBOTS FOR SENSITIVE TRANSACTIONS IN CHENNAI CITY

Abstract

The rapid adoption of artificial intelligence in the banking sector has led to the increased use of chatbots for customer service delivery. While banking chatbots offer convenience and efficiency, customer trust and acceptance remain critical concerns, particularly when chatbots are used for sensitive financial transactions. This study examines the factors influencing customer trust and acceptance of banking chatbots for sensitive transactions in Chennai City. A descriptive research design was adopted, and primary data were collected from 180 banking customers using a structured questionnaire. Structural Equation Modelling (SEM) using AMOS was employed to test the proposed conceptual framework. The results reveal that perceived security, privacy concerns, perceived usefulness, and ease of use significantly influence customer trust, which in turn has a strong positive effect on customer acceptance of banking chatbots. The findings confirm the mediating role of customer trust in the relationship between technology-related factors and chatbot acceptance. The study offers valuable theoretical and managerial implications for banks aiming to enhance trust and encourage customer adoption of AI-enabled chatbot services for sensitive transactions.