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The Effect of Humanizing Robo‐Advisors on Investor Judgments

Author

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  • Frank D. Hodge
  • Kim I. Mendoza
  • Roshan K. Sinha

Abstract

We examine the effect of humanizing (naming) robo‐advisors on investor judgments, which has taken on increased importance as robo‐advisors have become increasingly common and there is currently little SEC regulation governing key aspects of their use. In our first experiment, we predict and find that investors are more likely to rely on the investment recommendation of an unnamed robo‐advisor, whereas they are more likely to rely on the investment recommendation of a named human advisor. Theory suggests one reason that naming a robo‐advisor may have drawbacks pertains to the complexity of the task the robo‐advisor performs. We explore the importance of task complexity in our second experiment. We predict and find that investors are less likely to rely on a named robo‐advisor when the advisor is perceived to be performing a relatively complex task, consistent with our first experiment, and more likely to rely on a named robo‐advisor when the advisor is perceived to be performing a relatively simple task, consistent with prior research on human‐computer interactions. Our findings contribute to the literature examining how technology influences the acquisition and use of financial information and the general literature on human‐computer interactions. Our study also addresses a call by the SEC to learn more about robo‐advisors. Lastly, our study has practical implications for wealth management firms by demonstrating the potentially negative effects of making robo‐advisors more humanlike in an attempt to engage and attract users. L'incidence de l'humanisation des robots‐conseillers sur les jugements des investisseurs Les auteurs étudient l'incidence de l'humanisation (la dénomination) des robots‐conseillers sur les jugements des investisseurs, un sujet dont l'importance croît, compte tenu de la multiplication des robots‐conseillers et du peu de réglementation à laquelle la SEC soumet actuellement les principaux aspects de leur utilisation. Dans une première expérience, les auteurs formulent et confirment l'hypothèse selon laquelle les investisseurs sont davantage susceptibles de s'appuyer sur la recommandation de placement d'un robot‐conseiller sans dénomination, alors qu'ils sont davantage susceptibles de s'appuyer sur la recommandation de placement d'un humain désignée par son nom. La théorie laisse supposer que les inconvénients que peut présenter la dénomination d'un robot‐conseiller s'expliquent notamment par la complexité de la tâche accomplie par ce dernier. Les auteurs se penchent sur l'importance de la complexité de la tâche dans une seconde expérience. Ils formulent et confirment l'hypothèse selon laquelle les investisseurs sont moins susceptibles de s'appuyer sur la recommandation d'un robot‐conseiller désigné par un nom lorsqu’à leurs yeux, le conseiller accomplit une tâche relativement complexe, observation conforme aux résultats de la première expérience, et davantage susceptibles de s'appuyer sur la recommandation d'un robot‐conseiller portant un nom lorsqu’à leurs yeux, ce dernier accomplit une tâche relativement simple, observation conforme aux résultats d’études précédentes sur les interactions humain‐ordinateur. Les constats des auteurs viennent enrichir la documentation portant sur l'analyse de l'influence de la technologie sur l'acquisition et l'utilisation d'information financière de même que la documentation générale relative aux interactions humain‐ordinateur. Les auteurs traitent également de l'appel à l'approfondissement des connaissances au sujet des robots‐conseillers lancé par la SEC. Enfin, les résultats de l’étude ont des conséquences pratiques pour les sociétés de gestion de patrimoine, puisqu'ils nous renseignent sur les répercussions négatives potentielles de l'humanisation des robots‐conseillers afin de retenir l'attention et de susciter l'intérêt des utilisateurs.

Suggested Citation

  • Frank D. Hodge & Kim I. Mendoza & Roshan K. Sinha, 2021. "The Effect of Humanizing Robo‐Advisors on Investor Judgments," Contemporary Accounting Research, John Wiley & Sons, vol. 38(1), pages 770-792, March.
  • Handle: RePEc:wly:coacre:v:38:y:2021:i:1:p:770-792
    DOI: 10.1111/1911-3846.12641
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    1. Ibrahim Filiz & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2022. "Algorithm Aversion as an Obstacle in the Establishment of Robo Advisors," JRFM, MDPI, vol. 15(8), pages 1-25, August.
    2. Li, Emma & Mao, Mike Qinghao & Zhang, Hong Feng & Zheng, Hao, 2023. "Banks’ investments in fintech ventures," Journal of Banking & Finance, Elsevier, vol. 149(C).
    3. Zhu, Hui & Vigren, Olli & Söderberg, Inga-Lill, 2024. "Implementing artificial intelligence empowered financial advisory services: A literature review and critical research agenda," Journal of Business Research, Elsevier, vol. 174(C).

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