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Implementing artificial intelligence empowered financial advisory services: A literature review and critical research agenda

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  • Zhu, Hui
  • Vigren, Olli
  • Söderberg, Inga-Lill

Abstract

Robo-advisors, also known as robo-advisory services, significantly reshape customer service in financial advisory industries, transforming retail investor markets by substituting human financial advisory experts with artificial intelligence empowered services. However, existing literature remains scattered across disciplines, with theories on financial customer service predominantly focused on Internet banking, neglecting artificial intelligence empowered interactions. Thus, service providers need a framework for implementing robo-advisors in frontline service and researchers require an advanced agenda to stimulate future research. Through a systematic, interdisciplinary literature review based on Belanche et al.’s service robot framework, this article contextualizes service robot theories into financial advisory services, synthesizing knowledge on artificial intelligence empowered customer service. We contribute to literature on service robots by contextualizing, refining, and extending the original framework by Belanche et al. and by developing a research agenda with critical perspectives. Moreover, the study yields practical and theoretical insights into artificial intelligence empowered financial advisory services.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jbrese:v:174:y:2024:i:c:s0148296323008536
    DOI: 10.1016/j.jbusres.2023.114494
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    1. Gerlach, Johannes M. & Lutz, Julia K.T., 2021. "Digital financial advice solutions – Evidence on factors affecting the future usage intention and the moderating effect of experience," Journal of Economics and Business, Elsevier, vol. 117(C).
    2. Xusen Cheng & Fei Guo & Jin Chen & Kejiang Li & Yihui Zhang & Peng Gao, 2019. "Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    3. Ryoo, Yuhosua & Jeon, Yongwoog Andy & Kim, WooJin, 2024. "The blame shift: Robot service failures hold service firms more accountable," Journal of Business Research, Elsevier, vol. 171(C).
    4. Ankita Bhatia & Arti Chandani & Rizwana Atiq & Mita Mehta & Rajiv Divekar, 2021. "Artificial intelligence in financial services: a qualitative research to discover robo-advisory services," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(5), pages 632-654, September.
    5. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    6. Markus Blut & Cheng Wang, 2020. "Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 649-669, July.
    7. Daniel Belanche & Luis V. Casaló & Carlos Flavián & Jeroen Schepers, 2020. "Service robot implementation: a theoretical framework and research agenda," The Service Industries Journal, Taylor & Francis Journals, vol. 40(3-4), pages 203-225, March.
    8. Isaia, Eleonora & Oggero, Noemi, 2022. "The potential use of robo-advisors among the young generation: Evidence from Italy," Finance Research Letters, Elsevier, vol. 48(C).
    9. Shan, Shan & Umar, Muhammad & Mirza, Nawazish, 2022. "Can robo advisors expedite carbon transitions? Evidence from automated funds," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    10. Rishi Manrai & Kriti Priya Gupta, 2023. "Investor’s perceptions on artificial intelligence (AI) technology adoption in investment services in India," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 1-14, March.
    11. Dominik M. Piehlmaier, 2022. "Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    12. 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.
    13. Seiler, Volker & Fanenbruck, Katharina Maria, 2021. "Acceptance of digital investment solutions: The case of robo advisory in Germany," Research in International Business and Finance, Elsevier, vol. 58(C).
    14. D’Hondt, Catherine & De Winne, Rudy & Ghysels, Eric & Raymond, Steve, 2020. "Artificial Intelligence Alter Egos: Who might benefit from robo-investing?," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 278-299.
    15. Christian Hildebrand & Anouk Bergner, 2021. "Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 659-676, July.
    16. Vishaal Baulkaran & Pawan Jain, 2023. "Who uses robo‐advising and how?," The Financial Review, Eastern Finance Association, vol. 58(1), pages 65-89, February.
    17. Ruyi Ge & Zhiqiang (Eric) Zheng & Xuan Tian & Li Liao, 2021. "Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 32(3), pages 774-785, September.
    18. Xianpei Hong & Liwei Pan & Yeming Gong & Qian Chen, 2023. "Robo-advisors and investment intention : A perspective of value-based adoption," Post-Print hal-04339461, HAL.
    19. John A. Turner & Bruce W. Klein, 2021. "Improving on Defaults: Helping Pension Participants Manage Financial Market Risk in Target Date Funds," Risks, MDPI, vol. 9(4), pages 1-14, April.
    20. Donghwan Kwon & Pilwon Jeong & Doohee Chung, 2022. "An Empirical Study of Factors Influencing the Intention to Use Robo-Advisors," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 1-24, September.
    21. Robinson, Stacey & Orsingher, Chiara & Alkire, Linda & De Keyser, Arne & Giebelhausen, Michael & Papamichail, K. Nadia & Shams, Poja & Temerak, Mohamed Sobhy, 2020. "Frontline encounters of the AI kind: An evolved service encounter framework," Journal of Business Research, Elsevier, vol. 116(C), pages 366-376.
    22. Nourallah, Mustafa, 2023. "One size does not fit all: Young retail investors’ initial trust in financial robo-advisors," Journal of Business Research, Elsevier, vol. 156(C).
    23. Krzysztof Waliszewski & Anna Warchlewska, 2020. "Attitudes towards artificial intelligence in the area of personal financial planning: a case study of selected countries," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 399-420, December.
    24. Benjamin von Walter & Dietmar Kremmel & Bruno Jäger, 2022. "The impact of lay beliefs about AI on adoption of algorithmic advice," Marketing Letters, Springer, vol. 33(1), pages 143-155, March.
    25. Farida S. Rasiwala & Bindya Kohli, 2021. "Artificial Intelligence in FinTech: Understanding Stakeholders Perception on Innovation, Disruption, and Transformation in Finance," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 12(1), pages 48-65, January.
    26. Bernd Scherer & Sebastian Lehner, 2023. "Trust me, I am a Robo-advisor," Journal of Asset Management, Palgrave Macmillan, vol. 24(2), pages 85-96, March.
    27. David R. Lewis, 2018. "The perils of overconfidence: Why many consumers fail to seek advice when they really should," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 23(2), pages 104-111, June.
    28. Félix E Mezzanotte, 2020. "An examination into the investor protection properties of robo-advisory services in Switzerland," Capital Markets Law Journal, Oxford University Press, vol. 15(4), pages 489-508.
    29. Tiberius, Victor & Gojowy, Robin & Dabić, Marina, 2022. "Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    30. Riitsalu, Leonore & Uusberg, Andero, 2021. "To double, quadruple, or keep? Semi-automated service increases micro-investments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 95(C).
    31. Russell W. Belk & Daniel Belanche & Carlos Flavián, 2023. "Key concepts in artificial intelligence and technologies 4.0 in services," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 1-9, March.
    32. Hyun Baek, Tae & Kim, Minseong, 2023. "Ai robo-advisor anthropomorphism: The impact of anthropomorphic appeals and regulatory focus on investment behaviors," Journal of Business Research, Elsevier, vol. 164(C).
    33. Andreas Oehler & Matthias Horn & Stefan Wendt, 2022. "Investor Characteristics and their Impact on the Decision to use a Robo-advisor," Journal of Financial Services Research, Springer;Western Finance Association, vol. 62(1), pages 91-125, October.
    34. Brenner, Lukas & Meyll, Tobias, 2020. "Robo-advisors: A substitute for human financial advice?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    35. 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.
    36. Brunen, Ann-Christine & Laubach, Oliver, 2022. "Do sustainable consumers prefer socially responsible investments? A study among the users of robo advisors," Journal of Banking & Finance, Elsevier, vol. 136(C).
    37. Canhoto, Ana Isabel, 2021. "Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective," Journal of Business Research, Elsevier, vol. 131(C), pages 441-452.
    38. Litterscheidt, Rouven & Streich, David J., 2020. "Financial education and digital asset management: What's in the black box?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).
    39. Dominik Jung & Verena Dorner & Christof Weinhardt & Hakan Pusmaz, 2018. "Designing a robo-advisor for risk-averse, low-budget consumers," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 367-380, August.
    40. Lourenço, Carlos J.S. & Dellaert, Benedict G.C. & Donkers, Bas, 2020. "Whose Algorithm Says So: The Relationships Between Type of Firm, Perceptions of Trust and Expertise, and the Acceptance of Financial Robo-Advice," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 107-124.
    41. Sondra G. Beverly & Marianne A. Hilgert & Jeanne M. Hogarth, 2003. "Household financial management: the connection between knowledge and behavior," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Jul, pages 309-322.
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