With the growth of an economy, the banking industry expands and the competitiveness becomes intense with the increased number of banks in the economy. The objective of this research was to discover the influence of industry-specific and macroeconomic determinants of non-performing loans (NPLs) in the entire banking system of Bangladesh. We performed an analysis for the period from 1979 to 2018 by an autoregressive distributed lag (ARDL) model and checked the robustness of the results in the vector error correction (VEC) model. The outcomes of this research suggest that both industry-specific and macroeconomic factors influence NPLs significantly. Among the industry-specific determinants, bank loan growth, net operating profit, and deposit rates negatively impact NPLs with statistical significance while bank liquidity and lending rates have a significant positive affiliation with NPLs. Gross domestic product (GDP) growth and unemployment, among the macroeconomic variables, have a negative connection with NPLs. Whereas, domestic credit and exchange rates have a significant positive association with NPLs. The contribution of this research is that the outcomes found by means of econometric models can be used for predicting and measuring NPLs in upcoming years, not only for Bangladesh but also for developing and emerging economies. Individual banks, as well as the banking sector, by and large, can get a guideline from this research.

During the last few decades, the world financial crisis sheds on the bank risk, which creates a direct threat to the existence of banks. This paper investigates the relationship between bank risk and loan growth in the South Asian economies. The study has collected data from BankFocus of 118 commercial banks from 2011 to 2019. This study explores three hypotheses explaining the relation between (i) Bank Risk and Loan Growth; (ii) Loan growth and Bank Profitability; and (iii) Loan growth and bank solvency. Results show that loan growth can induce bank risk in the South Asian economic region. At the same time, Banks' solvency and profitability are correlated to bank risk with statistical significance. Primarily OLS has been applied, followed by GMM estimation. Non-Performing Loan (NPL) has been used as the proxy of bank risk. Further, to check the robustness of the investigation, we have used ZSCORE as a replacement to NPL. The results derived from regressions can put light on banks' poor performance in the South Asian counties and, simultaneously, may set guidance for policymakers of emerging economies.

This research aims to investigate the effect of banks' liquidity on its profitability; with the ordinary course of business and in the medium term (10 years). A quantitative analysis is performed on a statistical sample of forty (40) commercial banks in Bangladesh. Secondary data is used to evaluate the performance of the last ten years (2009-2018) of the annual report of the commercial banks in Bangladesh with 206 bank years of data gathered to consider all Bangladeshi commercial banks. Proposed variables are: LDR, DAR, CDR, LAR and CR as liquidity representation; on the other hand, ROE is the profitability representation. Five hypotheses have been established to assess the effect of liquidity on profitability. Following a correlation and regression analysis, it is observed that LDR, DAR and CDR had a substantial effect on the profitability measured as ROE, but LAR and CR proved insignificant. Therefore, it can be concluded that, in general, the impact of liquidity has a significant effect on the profitability in the commercial banking sector of Bangladesh. By relying on this report; Bangladeshi banks will be best positioned to keep equality between its liquidity and profitability. Keywords: Liquidity, Profitability, ROE, Commercial Banks

The objective of the study is to show the remedial effect of bank liquidity risk in the marketplace by disseminating financial information and practicing corporate governance mechanisms. The link between financial disclosure, corporate governance, and banks' liquidity risk management in Bangladesh is examined in this paper. The study used panel data on 32 commercial banks from the 2008 to 2018 with 346 observations collected from published annual reports. Based on the preliminary diagnosis, the study chose the two-stage least squares (2SLS) regression method to minimize the errors arising from heteroskedasticity, autocorrelation, and endogeneity issues. The study found that adequate financial disclosure and corporate governance practices minimize bank liquidity risk to maintain a stable image in the minds of investors and withstand immense regulatory pressure. To allow banks to detect issues early, they must implement changes quickly and be more robust to crises, thus risk management efficacy and excellent corporate governance implementation are required. Moreover, banks are mainly concerned about liquidity risk as it directly affects the market's performance and stability. Liquidity crises can be eradicated by proper monitoring and providing information pertaining to risks to prudent investors in a reliable and transparent corporate culture.

This paper examines the consequences of banks’ performance on bank risk. The paper forms a theoretical model and delivers empirical evidence to identify that banks suffer in performance as the loans become bad. Using panel data from a sample of five (05) South-Asian emerging economies from 2011 to 2019, we have found that the banks are highly influenced by the development of non-performing loans (NPLs). We have primarily used Return on Asset (ROA) followed by Return on Equity (ROE) as a substitution to the performance of the banks and NPL as the proxy of bank risk. Simultaneous regression applying 3sls finds that Non-Performing Loan (NPL) hinders banks' growth, negatively affecting their profitability.

The impact of disclosure quality (according to International Accounting Standard IAS 34) on the financial performance of listed commercial banks in Bangladesh has been discussed in this study. The number of firm-quarter observations varied between approximately 100 for the quarterly data set from 2021 through 2025. Data were collected from interim and annual reports, as well as the disclosures in these reports of the Dhaka Stock Exchange and the Bangladesh Securities and Exchange Commission (BSEC). Panel regression analysis was used, and return on assets (ROA) was used as an indicator of financial performance, and the IAS 34 disclosure compliance score (DCS) was the primary independent variable. The major control variables used were firm size, leverage, and liquidity. The Hausman test was used to justify fixed-effects estimation, and alternative measures of profitability and lagged disclosure variables were used to assess the robustness of the results. The results revealed that IAS 34’s disclosure quality was found to have a positive and significant correlation with financial performance. Size and liquidity have a positive impact on performance, while leverage has a negative effect. The results indicate that improving the transparency of reporting helps to reduce the information gap, increase accountability, and enhance stakeholder trust. This study adds to the current financial reporting literature in an emerging economy and provides practical implications for regulators, investors, auditors, bank management, etc.