Does AI Build Financial Confidence? A Structural Equation Model of AI Usage, Financial Self-Efficacy, and Financial Behaviour among Generation Z

Abstract

Generation Z has come of age alongside a rapid expansion of artificial-intelligence (AI)-enabled financial technologies, including robo-advisors, chatbot-based budgeting assistants, and algorithmic investment platforms. While digital financial literacy and social-media exposure are established predictors of young adults' financial self-efficacy and saving behaviour, the specific contribution of AI-tool usage remains comparatively under-examined. This study proposes and tests a structural model in which AI usage/reliance (AIU) predicts financial behaviour (FB) both directly and indirectly through financial self-efficacy (FSE), controlling for financial literacy (FL). Data are collected from a stratified random sample of 350+ Gen Z respondents (ages 18–27), stratified by gender, region, and income band. Measurement and structural parameters are estimated via structural equation modelling (SEM; WLSMV estimator for ordinal indicators), following confirmatory factor analysis of four latent constructs. This manuscript presents the full analytical framework variable definitions, sampling design, descriptive and inferential statistics, SEM specification, model-fit criteria, and visualization plan together with a reproducible R/Python pipeline.