Augmenting Investment Decisions with Robo-Advice

Abstract

We study the introduction of robo-advising on a large representative sample of Employee Saving Plans. Differently from many services that fully automate portfolio decisions, our robo-advisor proposes investment and rebalancing strategies, leaving investors free to follow or ignore them. We focus on the resulting human-robot interactions and show that with the robo-service investors increase their attention to the portfolio, their investment in the plan, their equity exposure. They experience higher risk-adjusted returns, mostly by changing their rebalancing so to stay closer to the target. These effects are robust across various specifications accounting for the endogeneity of the take-up decision, and they are stronger for investors with smaller portfolios, lower baseline returns and stock market participation. Our results suggest that automated advice can promote financial inclusion, and they highlight how human-robot interactions can influence investors' portfolio decisions and possibly improve financial capability.

Keywords: Robo-Advising, Human--robot Interaction, Financial Inclusion, Portfolio Dynamics, Long-Term Investment.

JEL Classification: G11, G51, G41, G23, D14