Algorithmic overconfidence, financial literacy, and decision quality: comparative evidence from Morocco and France

The growing adoption of algorithmic financial technologies, including robo-advisors, automated trading platforms and artificial-intelligence-based decision tools, raises a fundamental question regarding their actual contribution to investor rationality. This study investigates the extent to which algorithmic overconfidence, understood as an excessive reliance on automated systems, affects the quality of financial decisions. It also evaluates the direct and moderating role of financial literacy in this relationship. A comparative research design is employed to contrast Morocco, an emerging market characterized by lower literacy levels and a developing regulatory environment, with France, a mature financial ecosystem marked by stronger institutional structures and advanced digital integration. The empirical analysis relies on data collected through a questionnaire administered to 312 individual investors, split almost evenly between the two countries, and the relationships are tested using partial least squares structural equation modeling. The results show that algorithmic overconfidence significantly undermines financial decision quality, whereas financial literacy improves it and bmitigates the negative effect of overconfidence. Multi-group comparisons reveal that this harmful effect is more pronounced in Morocco, while the protective influence of literacy is stronger in France. Overall, the findings suggest that technology does not eliminate behavioral biases but instead reshapes their magnitude depending on the market context. The study contributes to behavioral finance by incorporating the technological dimension into the analysis of cognitive mechanisms and by highlighting financial literacy as a key protective factor. From a practical perspective, the evidence supports the need to reinforce financial education in emerging markets and to promote greater algorithmic transparency within advanced financial systems.