Determinants of Credit Risk in Vietnamese Commercial Banks: A Bayesian Analysis

Abstract

The article uses Bayesian analysis to analyze specific factors influencing commercial banks' credit risk in Vietnam. The research period spans from Vietnam's post-Great Recession economic recovery until 2020, coinciding with the global spread of the Covid-19 epidemic. Employing the Hybrid Metropolis-Hastings algorithm within a Bayesian framework, the study yielded the following outcomes: credit risk provision ratio from the previous year, credit growth rate, previous year's credit growth rate, non-performed debt ratio, marginal net interest income, bank size and the impact of Covid-19: all positively affect credit risk; Conversely, income as a percentage of total to assets, outstanding debt to mobilized asset ratio, real economic growth, and inflation rate have negative effects on credit risk of commercial banks. This research provides crucial insights into the factors that influence credit risk management within commercial banks. These insights can assist regulatory agencies and bank administrators in evaluating the impact of these factors and formulating effective credit risk management policies.