The Effect of Humanizing Robo-Advisors on Investor Judgments

Abstract

We examine the effect of humanizing (naming) robo-advisors on investor judgments. In our first experiment, we find that investors are more likely to rely on the investment recommendation of an unnamed robo-advisor, whereas they are more likely to rely on the investment recommendation of a named human advisor. Theory suggests one reason that naming a roboadvisor may have drawbacks pertains to the complexity of the task the robo-advisor performs. We explore the importance of task complexity in our second experiment. We find that investors are less likely to rely on a named robo-advisor when the advisor is perceived to be performing a relatively complex task, consistent with our first experiment, and more likely to rely on a named robo-advisor when the advisor is perceived to be performing a relatively simple task, consistent with prior research on human-computer interactions. Our findings contribute to the literature examining how technology influences the acquisition and use of financial information and the general literature on human-computer interactions. Our study also addresses a call by the SEC to learn more about robo-advisors. Lastly, our study has practical implications for wealth management firms as they increase their use of robo-advisors.

Keywords: Humanizing Technology, Financial Advisors, Investment Decisions, Robo-Advisors