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This paper investigates the factors that form bank risks in Bangladeshi state-owned banks. As a representation of bank risk, non-performing loans have been considered the dependent variable for this study. The relevant data have been extracted from six state-owned banks in Bangladesh from 2013 to 2022. The final dataset consists of 60 firm-year observations. The ordinary least square (OLS) regression with robust standard errors model is utilized to find the relationship of bank risks with determinants like asset size, efficiency, liquidity, profitability, leverage ratio, capital adequacy ratio, and loan to asset ratio. The findings say that bank size and loan-to-asset ratio have a highly significant positive relationship with bank risk, whereas profitability, capital adequacy ratio, and bank efficiency have a significant negative association with bank risk. On the other hand, leverage and liquidity are negatively and positively correlated with no statistical significance. To check the study's robustness, another proxy of bank risk, loan loss provision has been used and the results are almost similar. State-owned banks operate in every economy with a different mindset than the general commercial banks. Hence, policymakers should take necessary initiatives based on this study to bring down the high bank risks in state-owned banks in Bangladesh.

The main objective of this study is to assess the impact of non-performing loans on bank lending behavior before and amid the COVID-19 pandemic. To do this research we have chosen fifteen private commercial banks in Bangladesh and data were taken from the year 2012 to the year 2021. Credit growth as a component of bank lending behavior was selected as the dependent variable and independent variables are non-performing loans to total loans, provision for loan losses to total loans, gross domestic product (GDP) rate, inflation rate, unemployment rate, total loans to total customer deposit, total equity to total asset, tier 1 ratio, growth of customer deposits, the dummy variables are used for incorporating the effect of covid-19. The paper suggests that NPL to total loan, provision for loan losses to total loan, total equity to total asset, and dummy variables (effect of covid-19 on NPL) are found statistically significant and inversely related to credit growth. Another three variables namely total loan to total deposit, deposit growth, and inflation variables are statistically significant and positively related to credit growth. All of the significant variables are consistent with general economic theory except the case for total equity to the total asset. To reduce non-performing loans, the banks may concentrate on improving corporate governance, maintaining strong loan review, thoroughly reviewing the KYC form, must ensure safety principles before approving a loan, collecting information from the CIB, accepting adequate collateral, examining the five C’s, name lending and connected party lending should be strictly prohibited which are quite related with behavioral and judgmental issues, would be a matter of further research.

Bank profitability plays a significant role in the growth and development of an emerging economy. The purpose of the study was to examine the impact of bank characteristics, industry concentration and macroeconomics variables on commercial bank profitability in Bangladesh from 2007-2017. Bank profitability is proxied by return on assets (ROA), return on equity (ROE) and net interest margin (NIM). The study is based on secondary data and Hausman test has been performed using STATA software in favor of fixed effect modeling. Panel regressions shows that cost efficiency has significant negative impact on ROA and NIM. The positive impact of loan to deposit ratio with ROA suggests that efficient fund management including investment and assessed expenditure should be emphasized. Bank size has significant negative impact on all the measures of profitability, which indicates that monopolistic competition will reduce banking profit. Credit risk has significant positive impacts on ROE. Industry concentration measured by CR3 is positively related with ROE and has significant negative relation with bank profitability (ROA). Among macroeconomic variables inflation has significant positive and bank spread has significant negative impact on ROE. The coefficients of all the macroeconomic variables have been found to be significantly related to bank profitability while measured by NIM. Our study recommends further research with other explanatory variables such as, corporate governance, corporate social responsibility (CSR) and deposit insurance to accelerate the model and construct the econometric model by using structural equation modeling, mediation effect modeling etc.

This paper attempts to reveal how several credit risk factors are affecting the profitability of commercial banks considering the econometric models estimated with Random effect, Fixed effect, Pooled OLS and Cross-sectional Generalized least square (GLS) method followed by dynamic panel data model estimated with one-step GMM (generalized methods of moments) approach to incorporate the issue of endogeneity, unobserved heterogeneity and profit persistence of data set collected from annual report of banks covering from year 2010 to 2019 in Bangladesh. We have also adopted several diagnostic checks such as Model specification test, test of heteroskedasticty, cross sectional dependence test followed by test of autocorrelation and unit root test to examine the validity of the models selected for this study. The first part of our empirical investigation of the estimated models considering all methods reveals that out of all the independent credit risk factors such as Total loans to total assets ratio, Total loans to equity ratio, NPL to total loans, NPL to Total equity ratio, Provision for loan losses to total equity, total equity to total assets ratio, Total loans to total deposits ratio and provision for loan losses to NPL ratio, only provision for loan losses to NPL ratio is significantly affecting the dependent variable measured with NIM (Net interest margin) ratio of banks under fixed effect method. The next part of our empirical results of estimated models considering same methods divulges that NPL to total loans ratio, NPL to Total equity ratio and Provision for loan losses to total equity are also significantly affecting the dependent variable measured with ROE (Return on equity) of banks. The third segment of our empirical findings of estimated models considering same approaches shows that only NPL to total loans ratio is statistically significant under all methods but the NPL to total equity ratio is significant under fixed effect and GLS method and Provision for loan losses to total equity is significant under GLS method only in explaining the changes in ROA (Return on equity) measuring profitability of banks. Further investigation reveals that the dynamic impact of the said credit risk factors on profitability measured with ROE of banks has been successfully adopted by one-step system GMM approach considering all conditions required for estimation.