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Human-Robot Interactions in Investment Decisions

Author

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  • Milo Bianchi

    (Toulouse School of Economics, 31000 Toulouse, France; and Toulouse School of Management (TSM), University of Toulouse Capitole, 31000 Toulouse, France; and Institut Universitaire de France, 75231 Paris, France)

  • Marie Brière

    (Amundi, 75015 Paris, France; and Paris Dauphine University, 75016 Paris, France; and Université Libre de Bruxelles, 1050 Bruxelles, Belgium)

Abstract

We study the introduction of robo-advising on a large set of employee saving plans. Different from many services that fully automate portfolio decisions, our robo-advisor proposes investment and rebalancing strategies, leaving investors free to follow or ignore them. The resulting human-robot interactions occur both at the time of the subscription and over time, as the robot sends alerts when the investor’s portfolio gets too far from the target allocation. We show that the robo-service is associated with an increase in investors’ attention and trading activities. Following the robot’s alerts, investors change their rebalancing behaviors so as to stay closer to their target allocation, which results in larger portfolio returns. Counterfactual returns induced by automatic rebalancing by the robot would be only slightly higher, suggesting that, on average, the financial cost of letting investors retain control is not large.

Suggested Citation

  • Milo Bianchi & Marie Brière, 2026. "Human-Robot Interactions in Investment Decisions," Management Science, INFORMS, vol. 72(1), pages 14-31, January.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:1:p:14-31
    DOI: 10.1287/mnsc.2022.03886
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    References listed on IDEAS

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    1. Dean Karlan & Margaret McConnell & Sendhil Mullainathan & Jonathan Zinman, 2016. "Getting to the Top of Mind: How Reminders Increase Saving," Management Science, INFORMS, vol. 62(12), pages 3393-3411, December.
    2. Erik Brynjolfsson, 2022. "The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence," Papers 2201.04200, arXiv.org.
    3. Laurent E. Calvet & John Y. Campbell & Paolo Sodini, 2009. "Fight or Flight? Portfolio Rebalancing by Individual Investors," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(1), pages 301-348.
    4. Berk, Jonathan B. & van Binsbergen, Jules H., 2015. "Measuring skill in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 118(1), pages 1-20.
    5. Annamaria Lusardi & Olivia S. Mitchell, 2008. "Planning and Financial Literacy: How Do Women Fare?," American Economic Review, American Economic Association, vol. 98(2), pages 413-417, May.
    6. Antonio Gargano & Alberto G Rossi, 2018. "Does It Pay to Pay Attention?," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4595-4649.
    7. Ruyi Ge & Zhiqiang (Eric) Zheng & Xuan Tian & Li Liao, 2021. "Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 32(3), pages 774-785, September.
    8. Milo Bianchi, 2018. "Financial Literacy and Portfolio Dynamics," Journal of Finance, American Finance Association, vol. 73(2), pages 831-859, April.
    9. Francesco D’Acunto & Nagpurnanand Prabhala & Alberto G Rossi, 2019. "The Promises and Pitfalls of Robo-Advising," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1983-2020.
    10. Reher, Michael & Sokolinski, Stanislav, 2024. "Robo advisors and access to wealth management," Journal of Financial Economics, Elsevier, vol. 155(C).
    11. Paweł Niszczota & Dániel Kaszás, 2020. "Robo-investment aversion," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
    12. Brigitte C. Madrian & Dennis F. Shea, 2001. "The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(4), pages 1149-1187.
    13. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    14. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    15. Francesco D'Acunto & Alberto G. Rossi, 2023. "Robo-Advice: Transforming Households into Rational Economic Agents," Annual Review of Financial Economics, Annual Reviews, vol. 15(1), pages 543-563, November.
    16. Greenwood, Robin & Nagel, Stefan, 2009. "Inexperienced investors and bubbles," Journal of Financial Economics, Elsevier, vol. 93(2), pages 239-258, August.
    17. Gonzalo Maturana & Jordan Nickerson, 2019. "Teachers Teaching Teachers: The Role of Workplace Peer Effects in Financial Decisions," The Review of Financial Studies, Society for Financial Studies, vol. 32(10), pages 3920-3957.
    18. Paige Ouimet & Geoffrey Tate, 2020. "Learning from Coworkers: Peer Effects on Individual Investment Decisions," Journal of Finance, American Finance Association, vol. 75(1), pages 133-172, February.
    19. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
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    1. Bernd Irlenbusch, 2026. "Human Trust in AI: Evidence from Experimental Economics," ECONtribute Discussion Papers Series 417, University of Bonn and University of Cologne, Germany.

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