Working paper

Augmenting Investment Decisions with Robo-Advice

Milo Bianchi, and Marie Brière


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.


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

JEL codes

  • G11: Portfolio Choice • Investment Decisions
  • G41:
  • G23: Non-bank Financial Institutions • Financial Instruments • Institutional Investors
  • D14: Household Saving; Personal Finance
  • G51:


Milo Bianchi, and Marie Brière, Augmenting Investment Decisions with Robo-Advice, TSE Working Paper, n. 21-1251, September 2021.

See also

Published in

TSE Working Paper, n. 21-1251, September 2021