Harnessing Regulatory Fit in Robo-Advisory Services: A Pathway to Mitigate Investors’ Behavioral Biases

Robo-advisors (RAs), a transformative FinTech innovation, offer digital financial advice with minimal human involvement. Despite their widespread adoption, the effectiveness of RAs in regulating investors’ maladaptive behaviors remains debated. This study applies regulatory focus theory to examine how the alignment ('regulatory fit') between investors’ motivational orientations (promotion-focused vs. prevention-focused) and robo-advisory services influences behavioral biases. Analyzing data from Ant Group’s ZhiXiaoBao, we categorize its services into two types: information-centric and advice-centric. Employing OLS estimation and addressing endogeneity with Heckman selection models and instrumental variables, our findings reveal that information-centric services may exacerbate behavioral biases while advice-centric services mitigate them. Importantly, these effects are moderated by investors' regulatory focuses. A strong regulatory fit—where advice-centric services align with prevention-focused investors and information-centric services align with promotion-focused investors—significantly enhances bias mitigation. These findings underscore the importance of regulatory fit in RA effectiveness and provide strategies for tailoring services to investor orientations.