THE IMPACT OF FINANCIAL LITERACY ON ROBO-ADVISOR ADOPTION DURING ECONOMIC CRISIS: EVIDENCE FROM MALAYSIA
DOI:
https://doi.org/10.35631/AIJBAF.825001Keywords:
Economic Crisis, Financial Literacy, Malaysia, Perceived Usefulness, Retail Investor, Robo-Advisors, Technology Acceptance Model, JEL Classification: M40Abstract
Despite the potential benefits of robo-advisors, their adoption in Malaysia lags other East Asian developing economies, particularly during the recent economic crisis. The connection between the dimensions of financial literacy and the use of robo-advisors has not been adequately studied in the context of AI-assisted services in the past. This gap highlights the need to explore underlying behavioral and perceptual factors influencing the adoption of robo-advisors. This study builds upon the Technology Acceptance Model (TAM) by adding the financial literacy dimensions as external antecedents of perceived usefulness and behavioural intention to adopt robo-advisors. This addition expands the traditional TAM by showing that the adoption of robo-advisors is not only influenced by the perceptions of the users towards the technology itself, but also by their financial capabilities and orientations. A survey questionnaire was used to collect data on 380 Malaysian retail investors, which was analyzed by Partial Least Squares Structural Equation Modeling (PLS-SEM). Financial knowledge (β=0.613, p<0.05) and financial attitude (β=0.292, p<0.05) were found to have significant positive effects on perceived usefulness, and perceived usefulness exhibited a significant positive effect on intention to use (β=0.671, p<0.05), confirming its central role as a determinant of behavioral intention in this model. The model was observed to have a moderate predictive ability of behavioral intention to use by 53.2%. The results add to the existing literature on the adoption of financial technologies in emerging markets and have a number of practical implications. The providers must make conscious efforts to demonstrate the practical worth of their services by case studies, live demonstrations and interactive simulations that display the performance of robo-advisors in volatile markets. To policymakers and regulators, the findings highlight the importance of focusing on how individuals can use their skills with technology to deal with risk and improve financial decision-making in crisis situations.
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References
Aggarwal, N. (2021). The norms of algorithmic credit scoring. Cambridge Law Journal, 80(1), 42-73.
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139.
Allgood, S., & Walstad, W. B. (2015). The effect of perceived and actual financial literacy on financial behaviors. Economic Inquiry, 54(1), 675–697. https://doi.org/10.1111/ecin.12255
Arner, D. W., Barberis, J., & Buckley, R. P. (2016). The evolution of Fintech: A new post-crisis paradigm. Georgetown Journal of International Law, 47, 1271-1319.
Beketov, M., Lehmann, K., & Wittke, M. (2018). Robo advisors: Quantitative methods inside the robots. Journal of Asset Management, 19(6), 363-370.
Belanche, D., Casaló, L. V., & Flavián, C. (2019). Artificial intelligence in FinTech: Understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119(7), 1411-1430.
Bhatia, A., Chandani, A., & Chhateja, J. (2021). Robo-advisory and its potential in addressing the behavioral biases of investors—A qualitative study in Indian context. Journal of Behavioral and Experimental Finance, 30, 100466.
Boustani, N.M. (2020). Artificial intelligence impact on banks clients and employees in an Asian developing country. Journal of Asia Business Studies, 16(2), 267-278.
Caron, M.S. (2019). The transformative effect of AI on the banking industry. Banking and Finance Law Review, 34(2), 169-214.
Cheng, X., Guo, F., Chen, J., Li, K., Zhang, Y., & Gao, P. (2019). Exploring the trust influencing mechanism of robo-advisor service: a mixed method approach. Sustainability, 11(18), 4917.
Cheng, Y. M. (2020). Understanding cloud ERP continuance intention and individual performance: A TTF-driven perspective. Benchmarking: An International Journal, 27(4), 1591-1614.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
Das, A., & Das, D. (2023). Adoption of FinTech services amidst COVID-19 pandemic: empirical evidence from Assam. Managerial Finance, 49(6), 1075-1093.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Financial Education Network. (2019). Malaysia National Strategy for Financial Literacy 2019-2023. https://fenetwork.my/wp-content/uploads/2020/07/National-Strategy-ENG-F.pdf
Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. V. (2021). Intention to use analytical artificial intelligence (AI) in services–the effect of technology readiness and awareness. Journal of Service Management, 33(20), 293-320.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Fu, J., & Mishra, M. (2022). Fintech in the time of COVID− 19: Technological adoption during crises. Journal of Financial Intermediation, 50, 100945.
Habibullah, M. S., Saari, M. Y., Maji, I. K., Din, B. H., & Saudi, N. S. M. (2024). Modelling volatility in job loss during the COVID-19 pandemic: The Malaysian case. Cogent Economics & Finance 12: 2291886.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Prentice Hall.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA: Sage.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), New challenges to international marketing (pp. 277-319). Emerald Group Publishing Limited.
Hentzen, J. K., Hoffmann, A., Dolan, R., & Pala, E. (2022). Artificial intelligence in customer- facing financial services: a systematic literature review and agenda for future research. International Journal of Bank Marketing, 40(6), 1299-1336.
Huston, S. J. (2010). Measuring financial literacy. Journal of Consumer Affairs, 44(2), 296-316.
Ismail, K., Isa, C. R., & Mia, L. (2018a). Market competition, lean manufacturing practices and the role of management accounting systems (MAS) information. Jurnal Pengurusan (UKM Journal of Management), 52, 47-61.
Ismail, K., Isa, C. R., & Mia, L. (2018b). Evidence on the usefulness of management accounting systems in integrated manufacturing environment. Pacific Accounting Review, 30(1), 2-19.
Jung, D., Dorner, V., Weinhardt, C., & Pusmaz, H. (2018). Designing a robo-advisor for risk-averse, low-budget consumers. Electronic Markets, 28(3), 367-380.
Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as feelings. Psychological Bulletin, 127(2), 267-286.
Lopez, J. C., Babcic, S., & De La Ossa, A. (2015). Advice goes virtual: How new digital investment services are changing the wealth management landscape. Journal of Financial Perspectives, 3(3), 156-164.
Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5-44.
Mardhiah, A. (2022, October 19). SC: Malaysia recorded 1,800 investment scams for 9M22. The Malaysian Reserve.
Mhlanga, D. (2021). Financial inclusion in emerging economies: the application of machine learning and artificial intelligence in credit risk assessment. International Journal of Financial Studies, 9(3), 1-16.
Mogaji, E., Soetan, T. O., & Kieu, T. A. (2021). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, 29(3), 235-242.
OECD (2016). OECD/INFE international survey of adult financial literacy competencies. OECD, Paris, www.oecd.org/finance/OECD-INFE-International-Survey-of-Adult- Financial-Literacy-Competencies.pdf
Phoon, K. F., & Koh, F. C. (2018). Robo-advisors and wealth management. Journal of Alternative Investments, 20(3), 79-94.
RinggitPlus. (2021). Malaysian Financial Literacy Survey 2021.
Robb, C. A., & Woodyard, A. (2011). Financial knowledge and best practice behavior. Journal of Financial Counseling and Planning, 22(1), 60-70.
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.
Singh, S., & Srivastava, R. K. (2018). Predicting the intention to use mobile banking in India. International Journal of Bank Marketing, 36(2), 357-378.
Statista. (2022). Robo-advisors | Statista market forecast. https://www.statista.com/
Tai, Y. M., & Ku, Y. C. (2013). Will stock investors use mobile stock trading? A benefit-risk assessment based on a modified UTAUT model. Journal of Electronic Commerce Research, 14(1), 67-84.
Tut, D. (2023). FinTech and the COVID-19 pandemic: Evidence from electronic payment systems. Emerging Markets Review, 54, 100999.
van Rooij, M., Lusardi, A., & Alessie, R. (2011). Financial literacy and stock market participation. Journal of Financial Economics, 101(2), 449-472.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Woodyard, A., & Robb, C. (2016). Consideration of financial satisfaction: What consumers know, feel and do from a financial perspective. Journal of Financial Therapy, 7(2), 41-61.
Zhang, L., Pentina, I., & Fan, Y. (2021). Who do you choose? Comparing perceptions of human vs robo-advisor in the context of financial services. Journal of Services Marketing, 35(5), 634-646.
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