Exploring Gender Differences in Investment Decision-Making: The Role of AI in Identifying and Addressing Behavioral Biases

Abstract

This study investigates how Gender effects investment decision-making and AI's potential to detect and reduce behavioral biases. We utilized a 5-point Likert scale to score demographics, investment decision-making, and behavioral bias identification in 354 people who completed a self-administered online survey. The study examined gender, investment choices, and AI's impact on Behavioral Biases using descriptive correlation and SEM. Men scored slightly higher in Investment Decision-Making than women. (M = 3.7230 vs. M = 3.6784). There is no statistical significance for this difference. (t = 0.550, p = 0.583). SEM indicates gender affects behavioral biases. (β = 0.022, p < 0.05) these biases were significantly good for investment performance (β = 0.821, p < 0.05). The findings reveal how gender and behavioral biases interact, suggesting AI could improve financial decision-making.