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

Yunshil Cha and Fangjun Xiao

Finance Research Letters, 2025, vol. 85, issue PC

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.

Keywords: Robo-advisors; Financial advisors; Out-group homogeneity bias; Social categorization theory; Algorithmic transference (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:85:y:2025:i:pc:s1544612325011663

DOI: 10.1016/j.frl.2025.107908

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