TRUST IN BANKING DECISION-MAKING: A COMPARATIVE STUDY OF HUMAN AND ARTIFICIAL INTELLIGENCE ADVISORS

Abstract

The increasing deployment of artificial intelligence (AI) in the banking sector has fundamentally transformed advisory services and customer decision-making processes. Trust remains a critical determinant in banking decisions due to the high levels of financial risk, uncertainty, and long-term implications involved. This study aims to comparatively examine customer trust in human advisors and AI-based advisors in banking decision-making contexts. Adopting a quantitative research design, data were collected from 200 banking customers using a structured questionnaire. Trust was conceptualized as a multidimensional construct comprising competence, reliability, transparency, emotional assurance, and perceived risk. Structural equation modelling (SEM) using AMOS/SmartPLS was employed to test ten hypotheses. The results reveal that emotional assurance is the most influential factor in building trust in human advisors, while competence and transparency are the strongest predictors of trust in AI advisors. Perceived risk negatively influences trust in both advisory modes. The findings highlight the complementary roles of human and AI advisors and offer valuable managerial and theoretical implications for banks implementing hybrid advisory models.