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Robo-investment aversion

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  • Paweł Niszczota
  • Dániel Kaszás

Abstract

In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be made by human investment managers rather than by algorithms (“robos”). In all of the studies we investigate morally controversial companies, as it is plausible that a preference for humans as investment managers becomes exacerbated in areas where machines are less competent, such as morality. In Study 1, participants rated the permissibility of an algorithm to autonomously exclude morally controversial stocks from investment portfolios as lower than if a human fund manager did the same; this finding was not different if participants were informed that such exclusions might be financially disadvantageous for them. In Study 2, we show that this robo-investment aversion manifests itself both when considering investment in controversial and non-controversial industries. In Study 3, our findings show that robo-investment aversion is also present when algorithms are given the autonomy to increase investment in controversial stocks. In Studies 4 and 5, we investigate choices between actual humans and an algorithm. In Study 4 –which was incentivized–participants show no robo-investment aversion, but are significantly less likely to choose machines as investment managers for controversial stocks. In contrast, in Study 5 robo-investment aversion is present, but it is not different across controversial and non-controversial stocks. Overall, our findings show a considerable mean effect size for robo-investment aversion (d = –0.39 [–0.45, –0.32]). This suggests that algorithm aversion extends to the financial realm, supporting the existence of a barrier for the adoption of innovative financial technologies (FinTech).

Suggested Citation

  • Paweł Niszczota & Dániel Kaszás, 2020. "Robo-investment aversion," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
  • Handle: RePEc:plo:pone00:0239277
    DOI: 10.1371/journal.pone.0239277
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    Citations

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    Cited by:

    1. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Niszczota, Paweł & Białek, Michał, 2021. "Women oppose sin stocks more than men do," Finance Research Letters, Elsevier, vol. 41(C).
    3. Gregory Weitzner, 2024. "Reputational Algorithm Aversion," Papers 2402.15418, arXiv.org, revised Jul 2024.
    4. Niszczota, Paweł & Abbas, Sami, 2023. "GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advice," Finance Research Letters, Elsevier, vol. 58(PA).
    5. Alexia GAUDEUL & Caterina GIANNETTI, 2023. "Trade-offs in the design of financial algorithms," Discussion Papers 2023/288, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.

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