Structural Equation Modeling Semiparametric in Modeling the Accuracy of Payment Time for Customers of Credit Bank in Indonesia

Abstract

Credit risk assessment is crucial for financial institutions to ensure loan repayment. To enhance the prediction accuracy of creditworthiness and timely repayment, this research employs semiparametric structural equation modeling (SEM) to analyze the factors influencing credit repayment timeliness. The research was conducted to apply semiparametric SEM modeling to the timeliness of paying credit. Semiparametric SEM is structural modeling in which two combined approaches of parametric and nonparametric approaches are used. The analysis method in this research is semiparametric SEM with a nonparametric approach using a truncated spline. Truncated splines are chosen for their flexibility, ability to model complex relationships, continuity, interpretability, and strong performance in nonparametric regression tasks. The data in the study were obtained through questionnaires distributed to Bank X mortgage debtors and are confidential. The quetionnairs in the Likert scale, with five options. The study used 3 variables consisting of one exogenous variable, one intervening endogenous variable, and one endogenous variable. The results showed that: (1) the effect of capacity and willingness to pay variables on timeliness of payment is significant; (2) modeling the capacity variable on willingness to pay also produces a significant estimate; (3) the effect of the capacity variable on the timeliness of payment variable is not influenced by the willingness to pay variable as an intervening variable; and (4) the R^2 value of 0.763 or 76.33% indicates that the model has good predictive relevance. To continue to develop punctuality of paying credit, banks need to pay attention to the financial stability of consumers. Besides the financial stability, banks should pay attention to the sense of responsibility that customers have.