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Are all robo-advisors the same? Out-group homogeneity bias in investors’ perceptions of robo-advisors

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  • Cha, Yunshil
  • Xiao, Fangjun

Abstract

Robo-advisors are becoming increasingly prevalent in financial markets, raising important questions about how investors perceive them. Using an experiment, we study whether and why investors generalize a single robo-advisor’s performance more than that of a human financial advisor. Drawing on social categorization theory, we predict and find that investors perceive robo-advisors as more homogeneous than human financial advisors. This “all robo-advisors are the same” perception leads to greater transference of both success and failure across robo-advisors compared to human advisors. These findings highlight algorithmic transference in investor decision-making and carry important implications for investors and firms offering robo-advisory services.

Suggested Citation

  • Cha, Yunshil & Xiao, Fangjun, 2025. "Are all robo-advisors the same? Out-group homogeneity bias in investors’ perceptions of robo-advisors," Finance Research Letters, Elsevier, vol. 85(PC).
    • Handle: RePEc:eee:finlet:v:85:y:2025:i:pc:s1544612325011663
    DOI: 10.1016/j.frl.2025.107908
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    References listed on IDEAS

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