Artificial Intelligence and Behavioural Finance: A Review of Investor Biases, Algorithmic Decision-Making, and Emerging Opportunities

ABSTRACT: Behavioural finance explains why investors do not always act as perfectly rational decision-makers. Emotions, mental shortcuts, social influence and the way information is presented can shape investment choices, sometimes leading to decisions that differ from an investor’s long-term interests. At the same time, artificial intelligence (AI)—including machine learning, natural language processing, recommendation systems and robo-advisory tools—is changing how financial information is collected, interpreted and presented. This review examines the intersection of AI and behavioural finance, with particular attention to investor biases, sentiment analysis, algorithmic advice, personalised financial services and the Indian investment setting. Drawing on foundational behavioural-finance theories and recent research on robo-advisors, AI-based investment management and technology-mediated investor behaviour, the paper organises the literature into five themes: detecting behavioural patterns, supporting disciplined decisions, personalisation and trust, the possibility of technology amplifying biases, and governance. The review suggests that AI can help identify patterns such as herding, overconfidence and loss aversion, but prediction should not be confused with understanding or eliminating bias. Data quality, opacity, privacy, unequal digital access and conflicts of interest remain important concerns. The paper proposes an integrated conceptual framework linking investor characteristics, AI system design, behavioural mechanisms and decision outcomes. It concludes with a research agenda for India, including studies of retail investors, digital trading platforms, financial literacy, language diversity and human–AI advice. The paper is a narrative integrative review and does not claim a new empirical dataset or a fully exhaustive systematic search. Keywords: Behavioural finance; artificial intelligence; investor behaviour; machine learning; robo-advisors; behavioural biases; sentiment analysis; India.