Augmenting Investment Decisions with Robo-Advice

Abstract

We study the introduction of robo-advising on a large representa- tive sample of Employee Saving Plans. Dierently from many services that fully automate portfolio decisions, our robo-advisor proposes in- vestment 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 re- balancing so to stay closer to the target. These eects are robust across various specications accounting for the endogeneity of the take-up de- cision, and they are stronger for investors with smaller portfolios, lower baseline returns and stock market participation. Our results suggest that automated advice can promote nancial inclusion, and they high- light how human-robot interactions can in uence investors' portfolio decisions and possibly improve nancial capability.