The Role of Financial Literacy in Reducing Credit Risk Due to Digital Financial Inclusion A Study on Generation Z

Abstract

This study aims to analyze the influence of digital financial inclusion and financial literacy on credit risk and examine the role of financial literacy in moderating the relationship between digital financial inclusion and credit risk in Generation Z. The study used an explanatory quantitative approach with primary data collected through a Likert-scale questionnaire. The sample consisted of 212 Generation Z respondents aged 18–25 years selected through purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. Significance testing was conducted through bootstrapping 10,000 subsamples at a 5 percent significance level. The evaluation results showed that the measurement model met the reliability and validity criteria, while the structural model explained 49.9 percent of the variation in the credit risk construct (R² = 0.499). In this study, the credit risk construct was reverse-coded so that a higher score indicates a lower actual credit risk. Digital financial inclusion has a positive and significant effect on the reverse credit risk score (β = 0.397; p < 0.001), which substantively indicates a negative relationship with actual credit risk. Financial literacy also has a positive and significant effect on the reverse score (β = 0.470; p < 0.001), thus negatively related to actual credit risk. The interaction effect of financial literacy and digital financial inclusion is negative and significant (β = −0.304; p < 0.001). The conditional effect of digital financial inclusion on the reverse score decreases from 0.701 at low literacy levels to 0.397 at the average level and 0.093 at high levels; the effect at high levels is not significant (p = 0.070). Thus, financial literacy is shown to moderate the relationship by weakening the positive effect of digital financial inclusion on the reverse credit risk score. This finding confirms that the direction of the results should be interpreted consistently with the coding of the credit risk construct.