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Robo-Advice: Transforming Households into Rational Economic Agents

Author

Listed:
  • Francesco D'Acunto

    (Department of Finance, McDonough School of Business, Georgetown University, Washington, DC, USA)

  • Alberto G. Rossi

    (Department of Finance, McDonough School of Business, Georgetown University, Washington, DC, USA)

Abstract

Robo-advice uses big and open data to provide consumers with fully informed and rational-expectation benchmarks in all realms of household finance, including consumption, saving, investment, and debt management choices. It also minimizes the monetary, cognitive, and psychological costs that households face in economic transactions. We review recent research on the features and effects of robo-advice on individual and aggregate economic outcomes through the lens of its differences from traditional human advice. We discuss the distributional implications of robo-advice, its potential role in increasing the effectiveness of economic policies, the role of providers’ incentives, and several questions that are still wide open for researchers in finance, economics, social psychology, and related fields.

Suggested Citation

  • 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.
    • Handle: RePEc:anr:refeco:v:15:y:2023:p:543-563
    DOI: 10.1146/annurev-financial-110921-013217
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    Citations

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    Cited by:

    1. Schnorpfeil, Philip & Weber, Michael & Hackethal, Andreas, 2025. "Inflation and Trading," Journal of Financial Economics, Elsevier, vol. 173(C).
    2. Hu, Xiao & Kang, Siqin & Ren, Long & Zhu, Shaokeng, 2024. "Interactive preference analysis: A reinforcement learning framework," European Journal of Operational Research, Elsevier, vol. 319(3), pages 983-998.
    3. D’Acunto, Francesco & Rossi, Alberto G. & Weber, Michael, 2024. "Crowdsourcing peer information to change spending behavior," Journal of Financial Economics, Elsevier, vol. 157(C).
    4. Nourallah, Mustafa & Öhman, Peter & Hamati, Samer, 2024. "Financial technology and financial capability: Study of the European Union," Global Finance Journal, Elsevier, vol. 62(C).
    5. Schnorpfeil, Philip & Weber, Michael & Hackethal, Andreas, 2023. "Households' response to the wealth effects of inflation," CEPR Discussion Papers 18440, C.E.P.R. Discussion Papers.
    6. Massimiliano Stacchini & Pietro Vassallo, 2025. "The use of robo-advisors in Italy: insights from a new survey," Questioni di Economia e Finanza (Occasional Papers) 979, Bank of Italy, Economic Research and International Relations Area.
    7. Oberrauch, Luis & Kaiser, Tim, 2024. "Financial Education or Incentivizing Learning-By-Doing? Evidence from an RCT with Undergraduate Students," Journal of Behavioral and Experimental Finance, Elsevier, vol. 43(C).
    8. Tapsi Srivastava & Dr. Shishir Srivastava & Dr. Kritika Chawla, 2025. "Leaders in the Digital Age: A Systematic Review of Robo-Advisors in Wealth Management," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(10), pages 603-620, October.

    More about this item

    Keywords

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    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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