From cognitive bias to technological intervention: A systematic and bibliometric review of technology's role in investor behavioral biases

Abstract

This study examines the evolving landscape of behavioral biases in financial decision making as technology becomes increasingly embedded in investment processes. Using a PRISMA based systematic review combined with bibliometric analysis, 166 Scopus indexed publications spanning 1991 to 2025 were analysed using Biblioshiny and VOSviewer. The review maps emerging research clusters where technology plays a central role, including fintech platforms, digital trading systems and robo advisory services that mediate biases in real time, artificial intelligence based prediction of behavioral patterns, sentiment analysis and social media analytics used to capture investor psychology, and cryptocurrency and blockchain based markets where algorithmic trading and information asymmetry intensify behavioral distortions. Temporal analysis reveals a marked acceleration in technology centric behavioral finance research after 2017, particularly around AI enabled sentiment modeling and crypto market analytics. Content analysis identifies several gaps and future research directions, including comparisons of human versus algorithmic trading decisions, investor interactions with robo advisors and AI systems, the extent to which technology shapes or amplifies biases, and the development of real time, data driven models for detecting and measuring behavioral biases using big data, machine learning and behavioral tracking. The study offers a structured foundation for understanding behavioral biases in technology driven financial markets and provides guidance for future improvements in forecasting, risk management and policy design.