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Through the secondary data collected from 2005 to 2019, we used the BK approach in which, Pooled OLS, FEM, REM, and GMM methods and Sobel’s test are used to check the relationship between bank credit risk and bank stability of Vietnam commercial bank system. The results show that bank credit risk, profitability, and bank stability have a direct relationship and have a partial indirect relationship. The size and profitability of the previous period have a positively correlated with bank profitability, nonperforming loan, loan loss provision, non-interest income, efficiency, and bank credit growth have a negative impact on bank profitability, bank profitability has no impact on bank credit risk. Profitability and bank stability of the previous period have an impact on current bank stability. Nonperforming loans, non-interest income hurt bank stability, loan loss provision and bank stability of the previous period have a positively correlated with current bank stability. Finally, banks need to build and perfect the risk management system to comply with Basel II standards. Identifying and forecasting credit risks are one of the areas that need to be improved and carried out regularly and continuously.

ResumenEl objetivo de este trabajo es conocer las diferencias de género al valorar factores no financieros y financieros por los ejecutivos de crédito de instituciones financieras a la hora de autorizar un préstamo a la PYME mexicana. Mediante un análisis empírico se ha estudiado a los ejecutivos de crédito de 25 intermediarios financieros. Los resultados señalan que son las mujeres las que valoran como más importantes los factores no financieros de los prestatarios, frente a sus compañeros.AbstractThe aim of this study is to know the gender differences in assessing financial and non-financial factors by risk managers of financial institutions when approving a bank loan to Mexican SMEs. Through an empirical study the loan officers of 25 financial intermediaries have been analaised. The results show that it is women who value as more important the non-financial factors in borrowers than men.

Considering correlations between entries of credit portfolio is an important objective when estimating credit risk. This paper aims to construct a multivariate model of credit losses examining a portfolio composed of loans to a set of kinds of business. The paper also introduces the method of credit risk calculation via copulas, gamma distribution and kernel estimates. Empirical application of the introduced method is realized by using a historical loss data provided by one of the Moscow credit banks.