Seeing Through the Algorithm: How Explainability Shapes Decision-Making on Robo-Advisor Platforms
Date : Jeudi | 2025-05-22 à 12h30 Lieu : Salle des thèses Lien TEAMS : Cliquer ici pour rejoindre le séminaire doctorant du LÉO Mehdi LOUAFI (LEO, Université d’Orléans) This paper examines how algorithmic explainability shapes user decision-making and engagement on a leading French robo-advisor platform. In a large-scale field experiment, we randomly assigned 4,646 prospective clients to one of two conditions: a treatment group that viewed a graphical breakdown of the factors driving their personalized risk-profile recommendation, or a […]