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Behavioural finance in an era of artificial intelligence: Longitudinal case study of robo-advisors in investment decisions

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  • Shanmuganathan, Manchuna

Abstract

This study focuses on the actual and potential implications of artificial intelligence (AI) based applications and technical issues that are related to behavioural finance. However, there have being an enormous growth in the field of AI-based application within the financial services industry, especially in behavioural finance. This paper addresses the recent developments in AI applications related to algorithms in financial advisory services. Its performance through a theoretical framework based learning model in the financial context, which are effective in producing reliable portfolios based on investors’ behaviour and known as robo-advising. In recent years, the traditional financial services have been replaced by robo-advisors in wealth management industry due to new generation of clients who have the technical know-how of the digital technologies, prefer to have active and ongoing control over their investments while relying on the information from multiple (mainly on-line) sources. Currently, robo-advisors are recognized as most disruptive trend in asset and wealth management. Thus, a robo-advisor can be defined in an automated investment platform which utilizes​ quantitative algorithms to manage investors’ portfolios along with easily accessible to customers through on-line. This paper provides a longitudinal case study based on robo-advisors and behavioural financial decision-making process by investors, because the notion that those behavioural financial decisions are important for successful execution of a customer’s financial portfolios.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:beexfi:v:27:y:2020:i:c:s221463501930214x
    DOI: 10.1016/j.jbef.2020.100297
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