Factors Influencing Consumer Trust in AI-Enabled Financial Services in India

Abstract Artificial intelligence (AI) is fundamentally reshaping the financial services landscape in India, from algorithmic credit scoring and robo-advisory platforms to AI-powered chatbots handling customer queries. While the adoption of AI-driven financial products has accelerated, consumer trust remains a critical determinant of sustained uptake. This study investigates the influence of three key factors derived from the Technology Acceptance Model (TAM) on consumer trust in AI-enabled financial services in the Indian context: perceived usefulness (PU), perceived security (PS), and perceived ease of use (PEOU). A quantitative research design was employed, utilizing a structured 15-item Likert-scale questionnaire administered to 300 respondents across diverse demographic groups in India. Multiple regression analysis was used to test the hypothesised relationships. The results indicate that the model explains 73% of the variance in consumer trust (R-squared = 0.728), with all three independent variables demonstrating statistically significant positive relationships with consumer trust. Perceived ease of use emerged as the strongest predictor (standardised beta = 0.375), followed by perceived usefulness (standardised beta = 0.310) and perceived security (standardised beta = 0.236). The findings offer practical insights for fintech providers and policymakers seeking to strengthen consumer trust in AI-driven financial services across India.