Artificial Intelligence and Behavioral Finance in the Moroccan Banking Sector: Toward Optimizing Investment Decisions in UCITS

Abstract

This paper examines how artificial intelligence (AI) adoption and behavioral biases jointly shape retail investors' decisions regarding undertakings for collective investment in transferable securities (UCITS) distributed through Moroccan banks. Drawing on a survey of 150 bank clients across five Moroccan regions, we estimate a multiple linear regression model in which UCITS investment decision-making is regressed on three technology-related constructs (AI adoption, perceived usefulness, trust in AI) and four behavioral constructs (financial literacy, overconfidence, herding behavior, risk aversion). The model explains 50.8 percent of the variance in investment decision-making (adjusted R2 = 0.483; F(7,142) = 20.92, p < 0.001). Positive drivers are most significantly the trust in AI (beta = 0.336), AI adoption (beta = 0.298), financial literacy (beta = 0.194) and overconfidence (beta = 0.133). Perceived usefulness is found to have a negative significant effect (beta = -0.147) and risk aversion is found to have a negative significant effect (beta = -0.184) both of which are negative. The technological block accounts for another 26.3 percentage points of variance beyond the socio-demographic block, and the behavioral block accounts for another 9.8 points of variance beyond the socio-demographic and technological blocks. Overall, the findings suggest that perceived effectiveness of the use of AI-based advisory services is not the only determinant of their added value in the Moroccan context, but also that the trust dynamic in which they are applied is a key factor, and that behavioral biases are deeply entrenched in investment decisions and will not be fully eradicated by the introduction of an AI layer.

Keywords: artificial intelligence, behavioral finance, investment decision-making, Moroccan banking sector, multiple regression, UCITS.

Received Date: June 19, 2026

Accepted Date: July 10, 2026

Published Date: August 01, 2026

Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/931