Behavioral Finance Through Time: Tracing the Past, Analyzing the Present, and Forecasting the Future in the Age of AI

Abstract

This paper traces the evolution of behavioral finance from classical economic assumptions of rational agents to the integration of psychological insights that highlight biases and heuristics in decision-making. It then examines how the rapid rise of artificial intelligence (AI) is reshaping the field, particularly in investment contexts. While AI promises precision and freedom from human emotion, the persistence of human oversight raises questions about whether biases will be eliminated or simply transformed.

Drawing on survey data from 379 Indian investors across three age groups, this study explores attitudes toward AI-driven financial decision-making. Using regression and nonparametric analyses, we find that investors demonstrate conditional trust in AI: they are willing to follow AI recommendations when backed by a proven track record, but remain reluctant to rely on AI exclusively. Notably, higher familiarity with AI reduces unconditional acceptance, suggesting that informed investors approach AI with greater caution.

The findings highlight the emergence of meta-biases—cognitive patterns that arise when humans evaluate or intervene in machine-generated decisions—signalling that behavioral finance will continue to evolve rather than disappear in the age of AI.