Impact of Factors on Non-performing Loan at Vietnam Commercial Bank

Abstract

This study delves into an analysis of data obtained from 27 commercial banks operating in Vietnam from 2012 to 2021. Its primary objective is to scrutinize the influence of various factors on the non-performing loan (NPL) ratio and its subsequent impact on the credit risk of Vietnamese commercial banks. To achieve this, the study adopts a widely used regression analysis method, which involves processing tabulated data and employing three distinct models: the pooled regression model (pooled OLS), the fixed effects model (FEM), and the random effects model (REM). These models are instrumental in uncovering relationships between variables and providing a comprehensive understanding of the dynamics at play. Furthermore, the researchers apply the method of feasible generalized least squares (FGLS) to enhance the accuracy of the estimation process. This method is particularly advantageous in mitigating issues related to variance and self-correlation phenomena within the data, contributing to more robust and reliable findings.Upon careful analysis, the study successfully identifies six crucial factors that significantly influence both the non-performing loan (NPL) ratio and the credit risk faced by Vietnamese commercial banks. These findings represent valuable insights into the complex interplay of variables impacting the financial stability and performance of these institutions. In conclusion, this study makes a notable contribution to the understanding of NPLs and credit risk in the context of Vietnamese commercial banks. Its insights and recommendations have the potential to inform effective policy decisions and best practices within the banking sector, ultimately promoting financial stability and growth in the country.