Robo Advisory Customer Groups: Who Requires Advice?The authors wish to thank Anselm Hüwe, Andreas Pfingsten (the editor), and an anonymous reviewer for their comments, suggestions, and valuable feedback.

Abstract

Prior literature has often investigated how robo advisors can broaden their customer base. This study is based on the observation that some customers value the risk elicitation of robo advisors (guidance customers), whereas others value other aspects such as the simplicity and convenience of these services. Based on empirical robo advisory data, we build machine learning models to identify guidance customers. The models make predictions based on the financial knowledge of customers to a large extent. The age of a customer, the amount invested, income, and available assets are further important determinants.