Are Robots Taking Over? Technological Advancements and Investor Risk Tolerance


  • Jaenre Pietersen North West University
  • Sune Ferreira-Schenk North West University
  • Zandri Dickason North West University


The banking industry is being overhauled by robots. Artificial intelligence (AI) is the most recent technological breakthrough made in the banking industry. There is a wide range of variables that influence investor risk tolerance which has previously been examined, however, the influence of technological advancements on investor risk tolerance in a South African context remains unsolved. This paper aims to investigate the influence of technological advancements on investor risk tolerance. The results of this study found technological factors contributed significantly towards explaining high risk tolerance behaviour to a rather moderate degree. Evidence suggests investors employing Robo-advisors for assistance when making investment decisions, tend to become more risk-tolerant. The results of this study procured that certain demographic variables included in this study have a significant influence on the individual investor risk tolerance levels of South African investors. It is recommended that the research study be utilised by individual investors, financial planners, investment companies and current or future researchers originating from both frontiers to be acquainted with how technological advancements influence investor risk tolerance. Therefore, ensuring technological advancements are used accordingly, to the benefit of the investor privately or in practice.


Alba, J.W. & Hutchinson, J.W. 1987. Dimensions of consumer expertise. Journal of Consumer Research, 13(4):411-454.

Aliyu, A.A., Bello, M.U., Kasim, R. & Martin, D. 2014. Positivist and non-positivist paradigm in social science research: Conflicting paradigms or perfect partners. J. Mgmt. & Sustainability, 4(3):79-95.

Amaratunga, D., Baldry, D., Sarshar, M. & Newton, R. 2002. Quantitative and qualitative research in the built environment: application of “mixed” research approach. Work study, 51(1):17-31.

Anbar, A. & Melek, E. 2010. An empirical investigation for determining of the relation between personal financial risk tolerance and demographic characteristic. Ege Akademik Bakış Dergisi, 10(2):503-522.

Andrew, G., Arora, R., Bilmes, J. and Livescu, K., 2013, May. Deep canonical correlation analysis. In International conference on machine learning (pp. 1247-1255). PMLR.

Anyasi, F.I. & Otubu, P.A. 2009. Mobile phone technology in banking system: It’s economic effect. Research Journal of Information Technology, 1(1):1-5.

Armitage, P. 2016. Bizank – SA’s first robo-adviser. Date of access: 12 Sept. 2020.

Arora, R. 2017. Banks That Don't Invest in Technology Risk Falling Behind Permanently. Forbes, 20 Jul. Date of access: 20 Nov. 2020.

Baker, H.K. & Haslem, J.A. 1974. The impact of investor socioeconomic characteristics on risk and return preferences. Journal of Business Research, 2(4):469-476.

Bátiz-Lazo, B. & Wood, D. 2002. An historical appraisal of information technology in commercial banking. Electronic Markets, 12(3):192-205.

Bazeley, P., 2013. Qualitative data analysis: Practical strategies. Sage.

Beketov, M., Lehmann, K. & Wittke, M. 2018. Robo advisors: Quantitative methods inside the robots. Journal of Asset Management, 19(6):363-370.

Bettman, J.R. & Park, C.W. 1980. Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: A protocol analysis. Journal of Consumer Research, 7(3):234-248.

BI Intelligence. 2017. The robo-advising report: Market forecasts, key growth drivers, and how automated asset management will change the advisory industry. Date of access: 23 Feb. 2020.

Bickel, P.J. & Lehmann, E.L. 2012. Descriptive statistics for nonparametric models I. Introduction. In Selected Works of EL Lehmann (465-471). Springer, Boston, MA.

Botwinick, J. 1966. Cautiousness in advanced age. Journal of Gerontology, 21(3):347-353.

Chatterjee, S. and Hadi, A.S., 2015. Regression analysis by example. John Wiley & Sons.

Chen, J. 2019. Skewness. Date of access: 6 Nov. 2020.

Clark, K. 2019. The changing face of investing: a brief history. Date of access: 14 Feb. 2020.

Coet, L.J. & McDermott, P.J. 1979. Sex, instructional set, and group make-up: Organismic and situational factors influencing risk-taking. Psychological Reports, 44(3_suppl):1283-1294.

Creswell, J.W. and Clark, V.L.P., 2017. Designing and conducting mixed methods research. Sage publications.

De Iorio, M., Müller, P., Rosner, G.L. and MacEachern, S.N., 2004. An ANOVA model for dependent random measures. Journal of the American Statistical Association, 99(465), pp.205-215.

Deloitte. 2016. Robo Advisory in wealth management. White Paper.

Dickason, Z. & Ferreira, S.J. 2018. The effect of age and gender on financial risk tolerance of South African investors. Invest. Manage. Financ. Innov, 15(2):96-103.

Dickason, Z. & Ferreira, S.J. 2018. The effect of gender and ethnicity on financial risk tolerance in South African. Gender and Behaviour, 16(1):10851-10862.

Diggory, K. 2018. Technology in the 21st Century, Blessing or curse? Date of access: 20 Nov. 2020.

Draper, N.R. and Smith, H., 1998. Applied regression analysis (Vol. 326). John Wiley & Sons.

Elton, E.J., Gruber, M.J. & Busse, J.A. 2011. Are investors rational? Choices among index funds. In Investments and Portfolio Performance, 145-172.

Embrey, L.L. & Fox, J.J. 1997. Gender differences in the investment decision-making process. Financial Counselling and Planning, 8(2):33-40.

Ferreira, S.J. & Dickason-Koekemoer, Z. 2019. The relationship between depositor behaviour and risk tolerance in a South African context. Advances in Decision Sciences, 23(3):1-19.

Franzese, M. and Iuliano, A., 2019. Correlation analysis.

Friestad, M. & Wright, P. 1994. The persuasion knowledge model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1):1-31.

Frost, J., 2017. How to interpret R-squared in regression analysis. Statistics By Jim.

Grable, J. E. 2000. Financial risk tolerance and additional factors that affect risk taking in everyday money matters. Journal of Business and Psychology, 14(2):625-630.

Grable, J. E., & Joo, S. 1999. Factors related to risk tolerance: a further examination. Consumer Interests Annual, 45(1):53-58.

Grable, J. E., & Lytton, R. H. 1998. Investor risk tolerance: testing the efficacy of demographics as differentiating and classifying factors. Financial Counselling and Planning, 9(1):61-73.

Grable, J.E. & Lytton, R.H. 2001. Assessing the concurrent validity of the SCF risk tolerance question. Journal of Financial Counselling and Planning, 12(2):43.

Grable, J.E. 1997. Investor risk tolerance: Testing the efficacy of demographics as differentiating and classifying factors (Doctoral dissertation, Virginia Tech).

Hargrave, M. 2020. Standard Deviation Definition. Date of access: 6 Nov. 2020.

Irwin, C. E. 1993. Adolescence and risk taking: How are they related? In N. J. Bell & R. W. Bell (Eds.), Adolescent risk taking (7-28). Newbury Park, CA: SAGE.

Kenton, W. 2019. Descriptive Statistics. Date of access: 10 Oct. 2020.

King, B. 2010. Bank 2.0: How customer behaviour and technology will change the future of financial services. Marshall Cavendish International Asia Pte Ltd.

Kuzniak, S., Rabbani, A., Heo, W., Ruiz-Menjivar, J. & Grable, J.E. 2015. The Grable and
Lytton risk-tolerance scale: A 15-year retrospective. Financial Services Review, 24(2):177-192.

Lane, D. 2013. Sample Size. Date of access: 6 Nov. 2020.

Lyons, A.C., Palmer, L., Jayaratne, K.S. & Scherpf, E. 2006. Are we making the grade? A national overview of financial education and program evaluation. Journal of Consumer Affairs, 40(2):208-235.

MacCrimmon, K. R. & Wehrung, D. A. 1986. Risk management. New York: The Free Press.

Mandela, N., 2014. Education is the most powerful weapon which you can use to change the world. Computer, 8, 45.

McLeod, S. 2019. What is Kurtosis? Date of access: 6 Nov. 2020.

Nelito. 2017. AI and its impact on the finance industry. Date of access: 13 Mar. 2020.

Okun, M. A. & DiVesta, F. J. 1976. Cautiousness in adulthood as a function of age and instructions. Journal of Gerontology, 31(1):571-576.

Pallant, J. 2016. SPSS survival manual: a step by step guide to data analysis using SPSS. 6th ed. England: McGraw Hill.

Riley, F.K., Brown, K.C. & Leeds, S.J. 2018. Investment analysis & portfolio management. 11th ed. MA: Cengage.

Riley, J. 2019. Technological Impact on the Future of Investing. Date of access: 30 Feb. 2020.

Rogers, E.M. 2010. Diffusion of innovations. 4th ed. Simon and Schuster.

Rouse, M. 2019. Statistical mean, median, mode and range. Date of access: 6 Nov. 2020.

Rubin, P.H. & II, C.W.P. 1979. An evolutionary model of taste for risk. Economic Inquiry, 17(4):585-596.

Sarpong, P., 2020. Robo-Advisors: Exploring and Leveraging the Competition. Centre for Financial Planning Studies.

Shapshak, T. 2018. South Africa's Newest Bank, App-Driven Bank Zero, Begins Trials. Date of access: 9 May. 2020.

Standard Bank Group. 2011. It’s been 30 years of ATMs in South Africa. Date of access: 19 Apr. 2020.

Statista. 2020. Robo-Advisors. Date of access: 15 Feb. 2020.

Statistic Solutions, 2020. Conduct and Interpret a Multinomial Logistic Regression. Date of access: 26 May. 2020.

Sulaiman, E.K. 2012. An empirical analysis of financial risk tolerance and demographic features of individual investors. Procedia Economics and Finance, 2:109-115.

Sunden, A.E. & Surette, B.J. 1998. Gender differences in the allocation of assets in retirement savings plans. The American Economic Review, 88(2):207-211.

Sung, J. & Hanna, S.D. 1996. Factors Related to Risk Tolerance. Financial Counseling and Planning, 7:11-19.

Taylor, B. 2019. Ten Lessons for the Twenty-first Century Investor. Date of access: 15 Feb. 2020.

Taylor, C. 2018. What Are the Maximum and Minimum?,in%20our%20set%20of%20data.&text=There%20cannot%20be%20two%20minima,be%20less%20than%20the%20other. Date of access: 6 Nov. 2020.

Tongco, M.D.C. 2007. Purposive sampling as a tool for informant selection. Ethnobotany Research and applications, 5:147-158.

Van de Venter, G., Michayluk, D. & Davey, G. 2012. A longitudinal study of financial risk tolerance. Journal of Economic Psychology, 33(4):794-800.

Van den Bergh, A. 2020. The influence of endogenous and exogenous factors on investor risk-tolerance behaviour. (Thesis-Phd). NWU: Vanderbijlpark.

Vroom, V. H., & Pahl, B. 1971. Relationship between age and risk taking among managers. Journal of Applied Psychology, 55(5):399–405.

Wang, A. 2009. Interplay of investors' financial knowledge and risk taking. The Journal of Behavioral Finance, 10(4):204-213.

Wang, H., & Hanna, S. 1997. Does risk tolerance decrease with age? Financial Counselling and Planning, 8(2):27-32.

Wheeler, D.W. 2020. Co-opting Artificial Intelligence as an Opportunity for Financial Service Professionals. Journal of Financial Service Professionals, 74(1):66-72.

Yao, R. & Hanna, S.D. 2005. The effect of gender and marital status on financial risk tolerance. Gender and Behaviour, 16(1):10851 – 10862.

Yao, R., Gutter, M.S. & Hanna, S.D. 2005. The financial risk tolerance of Blacks, Hispanics and Whites. Journal of Financial Counselling and Planning, 16(1):51-62.

Yao, R., Hanna, SD & Lindamood, S. 2004. Changes in Financial Risk Tolerance, 2001:249-266.

Young, D. 2015. Why technology is important for banking. Global Finance and Banking, 10 Jan. Date of access: 20 Nov. 2020.






Economic Development, Technological Change, and Growth