Behavioural Biases in AI-Assisted Investment Decisions: Evidence from Young Retail Investors

Abstract

Artificial Intelligence (AI) has revolutionized the financial sector, changing how retail traders are interacting with information, assessing investment opportunities, and making trading choices. This has been made more accessible and much more accessible for the younger retail investor who is more likely to be open to digital investment technology, through the use of AI and investment platforms, robo-advisors, predictive analytics and algorithmic recommendation systems. Though these numbers crunching tools are intended to assist investors in making rational decisions, behavioural biases still creep into any investor's judgment, and can even impinge on AI-driven suggestions in unforeseen ways. This study examines the influence on the investment decision making process of young retail investors (YRIs) when they are advised to invest by AI and looks at the impact of overconfidence, herd behaviour, confirmation bias, anchoring, loss aversion and familiarity bias. The method of study used in this study is a quantitative research method, and the data obtained in this study was made in the form of a questionnaire. The research adopts a quantitative approach based on the structured survey data of young investors actively utilizing the AI investment application and digital trading platform. To analyze the correlation between the behavioural bias and the investment decision quality when the environment is aided by AI, descriptive analysis, correlation and multiple regression are used. The results suggest that while AI tools can improve access to timely information and analytical assistance, behavioural biases are still important factors to influence investment behaviour. Some of the objective decisions made when they are more confident and do not think about objective decisions based on herd mentality, but when they have more trust in AI and financial education, the investment discipline will be enhanced. The study finds that AI tools are not decision-making tools, but they support decision-making and there is still a need for an awareness of behaviours and investor education. The study contributes to the ongoing research on behavioural finance and fintech, providing empirical evidence on the interactions between psychological characteristics and investment platforms powered by AI technology. The findings of these studies have real-world applications for financial institutions, fintech firms, policy makers and educators seeking to develop investment platforms that use AI to inform and empower the new generation of retail investors to make transparent and responsible investment decisions.