Role of artificial intelligence in financial decision-making among investors: A quantitative study
TL;DR
The research finds that AIPA, DPS, BR, and CS considerably enhance FDMQ and the utility of incorporating AI into investment decisions aimed at enhanced precision, speed, and justice of decisions is confirmed.
Abstract
The study aims to examine the impact of artificial intelligence (AI) on the quality of financial decision-making of investors in Maharashtra, India. Specifically, it examines the impact of AI predictive analytics (AIPA), data processing speed (DPS), bias reduction (BR), and cost savings (CS) on financial decision-making quality (FDMQ) and the moderating effect of investor experience (IE). Data was gathered from 228 investors in Maharashtra through a closed-ended questionnaire administered through Google Forms and WhatsApp. Structural Equation Modeling (SEM) was employed using SmartPLS 4 to examine the hypothesized relations. The research finds that AIPA, DPS, BR, and CS considerably enhance FDMQ. Moreover, investor experience positively moderates these connections and strengthens the role of AI on decision quality. This research confirms the utility of incorporating AI into investment decisions aimed at enhanced precision, speed, and justice of decisions. Moreover, experience-led training and tactful usage of AI aids become necessary to benefit from various profiles of investors. This study contributes to the current body of research on AI in finance and provides actionable recommendations for investors, financial institutions, and policymakers with empirical evidence from one of India's leading financial hubs.