AI technology, FinTech services and Technostress effects on consumer financial decision-making: a smart PLS and experimental evidence approach

Purpose This study examines the impact of AI-driven personalization and FinTech accessibility on consumer financial decision-making, while exploring how technostress factors, complexity, overload and insecurity affect decision quality and the overall user experience in digital banking. Design/methodology/approach This study uses a mixed-methods approach to integrate PLS-SEM, experimental design and PLSpredict to assess the effects of AI personalization, accessibility, affordability and technostress on decision-making outcomes and cognitive strain. Findings AI personalization and accessibility significantly enhance decision quality, while affordability also plays a positive role, though to a lesser extent. Technostress, particularly techno-complexity and techno-insecurity, negatively impacts decision-making, while techno-overload has a minimal effect. Practical implications Effective AI systems should prioritize user-friendly designs, offer personalized recommendations, ensure seamless access across devices and provide transparent pricing. Reducing cognitive complexity and enhancing data security measures are crucial to minimize technostress and improve consumer decision-making in AI-enabled financial services. Originality/value This study integrates Media Synchronicity Theory with technostress theory, providing a comprehensive model that predicts how AI-driven personalization and FinTech accessibility influence consumer decision-making, offering a deeper understanding of psychological factors in AI-powered financial services.