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Financial education and digital asset management: What's in the black box?

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  • Litterscheidt, Rouven
  • Streich, David J.

Abstract

We study the effect of a financial education intervention on the propensity to delegate financial decision-making to a digital asset management tool (robo-advisor). Our results suggest that investors are more inclined to delegate financial decision-making when they receive detailed information on the investment principles underlying the robo-advisory algorithm. The intervention also affects investors’ independent investment behavior as it increases diversification and revealed risk aversion, while it decreases self-reported risk aversion. Our findings imply that robo-advisors benefit from providing financial education to prospective investors and that financial education may indirectly affect investment outcomes by encouraging the use of financial advice.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:soceco:v:87:y:2020:i:c:s2214804319304367
    DOI: 10.1016/j.socec.2020.101573
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    2. 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).
    3. Oberrauch, Luis & Kaiser, Tim, 2024. "Digital Interventions to Increase Financial Knowledge: Evidence from a Pilot RCT," IZA Discussion Papers 16811, Institute of Labor Economics (IZA).
    4. Cardillo, Giovanni & Chiappini, Helen, 2024. "Robo-advisors: A systematic literature review," Finance Research Letters, Elsevier, vol. 62(PA).
    5. Christian Fieberg & Lars Hornuf & David J. Streich, 2023. "Using GPT-4 for Financial Advice," CESifo Working Paper Series 10529, CESifo.
    6. Bai, Zefeng, 2021. "Does robo-advisory help reduce the likelihood of carrying a credit card debt? Evidence from an instrumental variable approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    7. 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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    More about this item

    Keywords

    FinTech; Robo advisory; Financial advice; Financial education; Technology adoption; Financial decision-making;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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