Digital financial literacy and household financial resilience: The mediating role of financial self-efficacy and the moderating role of AI literacy

Abstract

his study develops and empirically examines an integrated model linking digital financial literacy, artificial intelligence (AI) literacy, financial self-efficacy, and household financial resilience among Indonesian homemakers. Drawing on Social Cognitive Theory, the Technology Acceptance Model, and the Capability Approach, the study positions financial self-efficacy as a mediating mechanism and AI literacy as a moderating factor. A quantitative cross-sectional survey was conducted among 250 homemakers from Jakarta, Surabaya, Semarang, Palembang, and Makassar selected through purposive sampling. Data were analysed using Partial Least Squares Structural Equation Modelling with SmartPLS 4.0. The results demonstrate that digital financial literacy positively affects household financial resilience (β = 0.412, p < 0.001) and financial self-efficacy (β = 0.378, p < 0.001). Financial self-efficacy also positively influences household financial resilience (β = 0.287, p < 0.001) and partially mediates the relationship between digital financial literacy and financial resilience (β = 0.109, p < 0.001). Furthermore, AI literacy strengthens the relationship between digital financial literacy and financial self-efficacy (β = 0.198, p = 0.002). The model explains 67.3% of the variance in household financial resilience. These findings highlight that digital competencies must be accompanied by confidence and critical AI capabilities to strengthen household financial preparedness and adaptability. Practically, the findings support the design of inclusive financial education programs that combine digital financial skills, responsible AI use, privacy awareness, and confidence-building exercises. Such programs can help homemakers evaluate automated recommendations, manage household budgets more effectively, anticipate financial shocks, and make informed decisions without becoming overly dependent on technology.