Individualization of Robo-Advice

Abstract

Robo-advisors assign risky portfolios to individual investors using web-based investment algorithms with minimum human interaction. We provide insights into the working and current state of individualization of this new type of fintech company. Rather than singling out individual firms, our approach is use questions typically asked by robo-advisors to define a generic (average) robo-advisor as a benchmark model that we suggest can be improved upon in various dimensions. Given the missing human advisor, we believe the ability to individualize will be a distinguishing feature among robo-advisors. Our discussion aims at understanding the current state of personalization and helping users of robo-advice to better evaluate the services provided. <b>TOPICS:</b>Wealth management, quantitative methods