IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v182y2022ics0040162522003481.html
   My bibliography  Save this article

Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications

Author

Listed:
  • Tiberius, Victor
  • Gojowy, Robin
  • Dabić, Marina

Abstract

Robo advisors represent a digital financial advice solution challenging traditional wealth and asset management, investment advice, retirement planning, and tax-loss harvesting. Based on algorithms, big data analysis, machine learning, and other technologies, these services minimize the necessity for human intervention. Based on an international three-stage Delphi study, we provide a plausible forecast of the development of the robo advisor industry, with regards to market development, competition, drivers of growth, customer segments, challenges, services, technologies, and societal change. The results suggest that the financial advice market will experience a further increase in the number of robo advisor services available. Existing and traditional financial advice players will be forced to adjust to the changing environment of the market. Due to low fees and ease of use, robo advisors will be made available to a broad cross section of society, and will cause significant market losses for traditional investment advice companies. Ten years from now, the predominant investment class will remain Exchange Traded Funds (ETFs). Even though degrees of human intervention are expected to vary considering the complexity of advice, automation will increase in significance when it comes to the development of robo advisors.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003481
    DOI: 10.1016/j.techfore.2022.121824
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522003481
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.121824?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yonca Ertimur & Jayanthi Sunder & Shyam V. Sunder, 2007. "Measure for Measure: The Relation between Forecast Accuracy and Recommendation Profitability of Analysts," Journal of Accounting Research, Wiley Blackwell, vol. 45(3), pages 567-606, June.
    2. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
    3. Cao, Siqing & Lyu, Hanjia & Xu, Xian, 2020. "InsurTech development: Evidence from Chinese media reports," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Thakor, Anjan, 2020. "Corrigendum to: Fintech and Banking: What Do We Know?," Journal of Financial Intermediation, Elsevier, vol. 43(C).
    5. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195, January.
    6. 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.
    7. Flostrand, Andrew & Pitt, Leyland & Bridson, Shannon, 2020. "The Delphi technique in forecasting– A 42-year bibliographic analysis (1975–2017)," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    8. Cerqueti, Roy & Ciciretti, Rocco & Dalò, Ambrogio & Nicolosi, Marco, 2021. "ESG investing: A chance to reduce systemic risk," Journal of Financial Stability, Elsevier, vol. 54(C).
    9. Keller, Jonas & von der Gracht, Heiko A., 2014. "The influence of information and communication technology (ICT) on future foresight processes — Results from a Delphi survey," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 81-92.
    10. Mushonga, Master & Arun, Thankom G. & Marwa, Nyankomo W., 2018. "Drivers, inhibitors and the future of co-operative financial institutions: A Delphi study on South African perspective," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 254-268.
    11. Förster, Bernadette & von der Gracht, Heiko, 2014. "Assessing Delphi panel composition for strategic foresight — A comparison of panels based on company-internal and external participants," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 215-229.
    12. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    13. Amaral, Christopher & Kolsarici, Ceren, 2020. "The financial advice puzzle: The role of consumer heterogeneity in the advisor choice," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    14. Meijering, J.V. & Kampen, J.K. & Tobi, H., 2013. "Quantifying the development of agreement among experts in Delphi studies," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1607-1614.
    15. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    16. Christian Haddad & Lars Hornuf, 2019. "The emergence of the global fintech market: economic and technological determinants," Small Business Economics, Springer, vol. 53(1), pages 81-105, June.
    17. Pereira, Cristiano Gonçalves & Lavoie, Joao Ricardo & Garces, Edwin & Basso, Fernanda & Dabić, Marina & Porto, Geciane Silveira & Daim, Tugrul, 2019. "Forecasting of emerging therapeutic monoclonal antibodies patents based on a decision model," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 185-199.
    18. 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.
    19. Melander, Lisa & Dubois, Anna & Hedvall, Klas & Lind, Frida, 2019. "Future goods transport in Sweden 2050: Using a Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 178-189.
    20. 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).
    21. Thakor, Anjan V., 2020. "Fintech and banking: What do we know?," Journal of Financial Intermediation, Elsevier, vol. 41(C).
    22. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    23. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40, January.
    24. de Loë, Rob C. & Melnychuk, Natalya & Murray, Dan & Plummer, Ryan, 2016. "Advancing the State of Policy Delphi Practice: A Systematic Review Evaluating Methodological Evolution, Innovation, and Opportunities," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 78-88.
    25. Pan, Xuefeng & Wu, Weixing & Zhang, Xuyang, 2020. "Is financial advice a cure-all or the icing on the cake for financial literacy? Evidence from financial market participation in China," International Review of Financial Analysis, Elsevier, vol. 69(C).
    26. Shanmuganathan, Manchuna, 2020. "Behavioural finance in an era of artificial intelligence: Longitudinal case study of robo-advisors in investment decisions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    27. Spickermann, Alexander & Zimmermann, Martin & von der Gracht, Heiko A., 2014. "Surface- and deep-level diversity in panel selection — Exploring diversity effects on response behaviour in foresight," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 105-120.
    28. von der Gracht, Heiko A. & Darkow, Inga-Lena, 2010. "Scenarios for the logistics services industry: A Delphi-based analysis for 2025," International Journal of Production Economics, Elsevier, vol. 127(1), pages 46-59, September.
    29. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    30. Lisa-Marie Semke & Victor Tiberius, 2020. "Corporate Foresight and Dynamic Capabilities: An Exploratory Study," Forecasting, MDPI, vol. 2(2), pages 1-14, June.
    31. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
    32. Bollaert, Helen & Lopez-de-Silanes, Florencio & Schwienbacher, Armin, 2021. "Fintech and access to finance," Journal of Corporate Finance, Elsevier, vol. 68(C).
    33. Min Dai & Hanqing Jin & Steven Kou & Yuhong Xu, 2021. "Robo-advising: a dynamic mean-variance approach," Digital Finance, Springer, vol. 3(2), pages 81-97, June.
    34. Weijters, Bert & Millet, Kobe & Cabooter, Elke, 2021. "Extremity in horizontal and vertical Likert scale format responses. Some evidence on how visual distance between response categories influences extreme responding," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 85-103.
    35. von der Gracht, Heiko A., 2012. "Consensus measurement in Delphi studies," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1525-1536.
    36. Kerr, Norbert L. & Tindale, R. Scott, 2011. "Group-based forecasting?: A social psychological analysis," International Journal of Forecasting, Elsevier, vol. 27(1), pages 14-40.
    37. Makkonen, Marika & Hujala, Teppo & Uusivuori, Jussi, 2016. "Policy experts' propensity to change their opinion along Delphi rounds," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 61-68.
    38. Lee, In & Shin, Yong Jae, 2018. "Fintech: Ecosystem, business models, investment decisions, and challenges," Business Horizons, Elsevier, vol. 61(1), pages 35-46.
    39. Schuckmann, Steffen W. & Gnatzy, Tobias & Darkow, Inga-Lena & von der Gracht, Heiko A., 2012. "Analysis of factors influencing the development of transport infrastructure until the year 2030 — A Delphi based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1373-1387.
    40. Palmié, Maximilian & Wincent, Joakim & Parida, Vinit & Caglar, Umur, 2020. "The evolution of the financial technology ecosystem: An introduction and agenda for future research on disruptive innovations in ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    41. Victor Tiberius & Laura Lisiecki, 2019. "Stock Price Forecast Accuracy and Recommendation Profitability of Financial Magazines," IJFS, MDPI, vol. 7(4), pages 1-8, October.
    42. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    43. von Briel, Frederik, 2018. "The future of omnichannel retail: A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 217-229.
    44. Mauksch, Stefanie & von der Gracht, Heiko A. & Gordon, Theodore J., 2020. "Who is an expert for foresight? A review of identification methods," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    45. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Calof, Jonathan & Colton, Brian, 2024. "Developing foresight that impacts senior management decisions," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    2. Tamaki Welply, Yuko & Lechevalier, Sébastien, 2024. "‘Social’ robot and social relations in care settings: Undefined positionality and fixed temporality," Technology in Society, Elsevier, vol. 77(C).
    3. Tigges, Maximilian & Mestwerdt, Sönke & Tschirner, Sebastian & Mauer, René, 2024. "Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Cardillo, Giovanni & Chiappini, Helen, 2024. "Robo-advisors: A systematic literature review," Finance Research Letters, Elsevier, vol. 62(PA).
    5. 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).
    6. Ko, Hyungjin & Byun, Junyoung & Lee, Jaewook, 2023. "A privacy-preserving robo-advisory system with the Black-Litterman portfolio model: A new framework and insights into investor behavior," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    7. Choudhary, Priya & Thenmozhi, M., 2024. "Fintech and financial sector: ADO analysis and future research agenda," International Review of Financial Analysis, Elsevier, vol. 93(C).
    8. Liao, Xia & Zheng, Yu-Hao & Shi, Guicheng & Bu, Huimei, 2024. "Automated social presence in artificial-intelligence services: Conceptualization, scale development, and validation," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    9. Frank, Darius-Aurel & Otterbring, Tobias, 2023. "Being seen… by human or machine? Acknowledgment effects on customer responses differ between human and robotic service workers," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    10. Byun, Junyoung & Ko, Hyungjin & Lee, Jaewook, 2023. "A Privacy-preserving mean–variance optimal portfolio," Finance Research Letters, Elsevier, vol. 54(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peppel, Marcel & Ringbeck, Jürgen & Spinler, Stefan, 2022. "How will last-mile delivery be shaped in 2040? A Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Frevel, Nicolas & Beiderbeck, Daniel & Schmidt, Sascha L., 2022. "The impact of technology on sports – A prospective study," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    3. Geissler, Dominik & Beiderbeck, Daniel & Schmidt, Sascha L. & Schreyer, Dominik, 2024. "Emerging technologies and shifting consumer motives: Projecting the future of the top-tier sports media product," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    4. Kopyto, Matthias & Lechler, Sabrina & von der Gracht, Heiko A. & Hartmann, Evi, 2020. "Potentials of blockchain technology in supply chain management: Long-term judgments of an international expert panel," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    5. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    6. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    7. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    8. Di Zio, Simone & Bolzan, Mario & Marozzi, Marco, 2021. "Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    9. Christoph Markmann & Alexander Spickermann & Heiko A. von der Gracht & Alexander Brem, 2021. "Improving the question formulation in Delphi‐like surveys: Analysis of the effects of abstract language and amount of information on response behavior," Futures & Foresight Science, John Wiley & Sons, vol. 3(1), March.
    10. Gebhardt, Maximilian & Spieske, Alexander & Birkel, Hendrik, 2022. "The future of the circular economy and its effect on supply chain dependencies: Empirical evidence from a Delphi study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    11. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
    12. Beiderbeck, Daniel & Evans, Nicolas & Frevel, Nicolas & Schmidt, Sascha L., 2023. "The impact of technology on the future of football – A global Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    13. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    14. Laura Studen & Victor Tiberius, 2020. "Social Media, Quo Vadis? Prospective Development and Implications," Future Internet, MDPI, vol. 12(9), pages 1-22, August.
    15. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    16. Förster, Bernadette & von der Gracht, Heiko, 2014. "Assessing Delphi panel composition for strategic foresight — A comparison of panels based on company-internal and external participants," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 215-229.
    17. Leypoldt, Leo & Dienhart, Christina & Caferoglu, Hüseyin & Salge, Torsten-Oliver & Antons, David, 2024. "The hydrogen field in 2035: A Delphi study forecasting dominant technology bundles," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    18. Shoukohyar, Sajjad & Seddigh, Mohammad Reza, 2020. "Uncovering the dark and bright sides of implementing collaborative forecasting throughout sustainable supply chains: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    19. Prommer, Lisa & Tiberius, Victor & Kraus, Sascha, 2020. "Exploring the future of startup leadership development," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    20. Pandey, Dharen Kumar & Hassan, M.Kabir & Kumari, Vineeta & Zaied, Younes Ben & Rai, Varun Kumar, 2024. "Mapping the landscape of FinTech in banking and finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 67(PA).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003481. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.