Digital Credit and Debt Traps: Behavioral and Socio-Cultural Drivers of FinTech Indebtedness in Emerging Economies

FinTech-based lending has rapidly expanded in emerging economies, offering convenience and inclusion but also raising concerns about over-indebtedness. In Indonesia, the surge of digital loans has been accompanied by growing signs of risky borrowing behavior, including late payments, high debt-to-income ratios, and poor credit discipline. This study investigates the determinants of individuals’ propensity to indebtedness in FinTech-based loans, focusing on the influence of financial behavior biases, emotions, culture, and materialism, as well as the moderating effects of financial literacy, job security, and religiosity. Data were collected from 400 Indonesian civil servants and private/self-employed workers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that all proposed determinants significantly increase indebtedness, with financial behavior biases having the strongest impact. Financial literacy and job security amplify these effects, while religiosity weakens the influence of emotions and materialism. These findings contribute to behavioral finance theory and underscore the importance of promoting financial literacy, strengthening job stability, and integrating responsible lending policies to mitigate debt risks in emerging economies.