Impact of AI-Powered Personal Finance Applications on Financial Decision-Making and Investment Behaviour Among Young Investors
TL;DR
It is indicated that AI-powered personal finance applications are consistently associated with improved financial confidence and more frequent, though not necessarily more diversified, investment activity among young users, with effects moderated by financial literacy, trust in automation, and platform design quality.
Abstract
Abstract The rapid proliferation of artificial intelligence (AI)-powered personal finance applications, spanning robo-advisors, automated budgeting tools, AI-driven expense trackers, and algorithmic investment platforms, has reshaped how young investors access financial information, form judgments, and act on investment opportunities. This paper presents a structured literature review and conceptual analysis of how AI-powered personal finance applications influence two closely related outcomes: financial decision-making quality and investment behaviour among young investors, broadly defined as individuals between eighteen and thirty-five years of age. Drawing on peer-reviewed research spanning behavioural finance, fintech adoption, robo-advisory literature, and digital financial literacy, the paper synthesizes evidence on the mechanisms through which AI personalization and automation affect cognitive biases, risk perception, financial confidence, and portfolio choices. A conceptual framework is proposed linking AI application features to decision-making and investment outcomes through mediating constructs such as perceived trust, financial self-efficacy, and perceived ease of use. The paper outlines a proposed mixed-methods research design for empirically testing the framework, discusses ethical and regulatory considerations including algorithmic transparency and data privacy, and identifies gaps in the current literature. The review indicates that AI-powered personal finance applications are consistently associated with improved financial confidence and more frequent, though not necessarily more diversified, investment activity among young users, with effects moderated by financial literacy, trust in automation, and platform design quality. The paper concludes with implications for fintech providers, regulators, and financial educators, and recommends directions for future longitudinal research. Keywords: Artificial intelligence; personal finance applications; robo-advisory; financial decision-making; investment behaviour; young investors; fintech; financial literacy