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Averting the risk of falling short on the expected profitability of a bank requires the knowledge of the underlying determinants. Knowledge of long-run underlying determinants of profitability assists banks in comprehensive planning. In this backdrop, the paper seeks to identify the long-term fundamental risk factors and their impacts on their profitability. The FM-OLS regression method is employed using annual data on the components of profitability as well as internal and external determinants of profitability of Amalgamated Bank of South Africa (ABSA) bank from 1998 to 2014. The study is particularly importance since bank-specific studies aimed at identifying long-run fundamental factors of profitability has not been given much attention in literature. Evidence from the study indicates that profitability of ABSA is cointegrated with its determinants. It is further observed that, with the exception of inflation and GDP, all the determinants have significant long-term impact on profitability. However, although size has significant impact on net interest margins, its impact on return on equity is insignificant. The results further suggest that capital and stock market capitalization pose risk to aggregate profitability of ABSA. It is therefore recommended that in future, ABSA should resort to optimal equity financing to maximize its expected profitability.

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 provides rather scares evidence on the nexus between bank competition and economic growth in a unique developing economy; Sri Lanka for the period 1996-2018. The effect of competition in the Sri Lankan banking sector on economic growth, and the mechanisms through which competition affects growth are analyzed in the present paper. The VEC model used in this study was aimed at capturing independently the short and long-term effect of bank competition on economic growth. The competition is measured with Pazar-Ross H- Statistics. Contrary to the common wisdom, the study found evidence for negative effects of bank competition, on economic growth in the short run. However, in the long run, this effect is strong and positive. Further, the statistical results of this paper revealed that higher bank competition channels economic growth through interest rate and bank efficiency. These findings have important policy implications as it gives great insight into the complexity of competition related conduct in developing countries.

This paper provides interesting insights into the practices of banks and institutional setting in Sri Lanka. The sustainability and stability of banks that makes up an economy’s banking system should be sound at all time. This paper aimed at analyzing the determinants of banking sector stability in Sri Lanka. The study used a broad set of macro and bank level data covering 22 commercial banks for the period 1996-2016. The fixed effect GLS panel data model tested in this paper sets the relationship between bank stability measure; Z-score and business environment which includes bank characteristics and the elements of macro environment. The analysis of the study revealed lower level of Z-scores and thus lower level of bank stability, indicating a higher risk associated with the commercial banking sector in Sri Lanka.  From among the variables tested, strong evidence was found for a positive effect of bank efficiency on bank stability and a negative effect of credit growth on bank stability. At macro level, bank stability is promoted at a higher rate when the economy is more developed and stable. The results imply that efficiency of commercial banks needs to be further improved and regulatory and policy environment should be strengthened to manage the credit growth at the bank level. Further, it is suggestive to strengthening bank supervision and other financial infrastructure in order to ensure sustainability of the banking sector. Thus, the present paper contributes the current banking literature by unveiling the explicit and unforeseen economic implications associate with individual bank operations and macro imbalance which are particularly unique in underdeveloped countries.

This paper researches the impact that shadow banking in China has upon credit creation and the potential effectiveness of monetary policy. Using a credit creation model, we derive the effect that shadow banking has upon the money multiplier and the money supply. The model shows that shadow banking can change the money multiplier, potentially increasing it during an expansion and decreasing it during a contraction. Introducing shadow banking in a CC-LM model results in a shift of the CC and LM curves resulting in a higher equilibrium output. A vector autoregressive model is used to empirically estimate the impact of shadow banking deposits' growth rate on the growth rates of the broad money supply, GDP, and the CPI. The results show that shadow banking's credit creation function in China has a pro-cyclical characteristic, potentially reducing the money supply's controllability and increasing the difficulty in effectively regulating monetary policy. This paper introduces shadow banking into the currency creation process of traditional commercial banks, accounting for the reserve requirement ratio, the excess reserve ratio, the shadow bank leakage rate, and the reserved deduction rate. Future research can determine whether coordinating monetary policy and leverage ratio regulation mitigates the impact of shadow banking. Another area of research is how the shadow banking of non-financial companies affect monetary policy.

Financial institutions and banks are required to follow mechanisms to monitor the positions and create stimulas for sensible risk-taking by divisions a well as individuals. Risk measurement comprises of the quantification of risk exposures, whereas risk management demonstrates to the overall procedures by which managers fulfill these needs to identify the risks and recognise the category of the risks it faces. This research targerts on the economic instability faced by banks in financial arena in terms of the crises affairs in regard of economic distress. Here, the methodology followed is based on the CAMELS framework variables. CAMELS is a short form stands for: capital adequacy (C), asset (A), management (M), earnings (E), liquidity (L) and sensitivity to market risk (S). Based on these nomenclature, a couple of variables should be selected, such as capital asset ratio, cost income ratio, non-performing loan, non-interest income as component series and return on asset (ROA) as the reference series to identify turning points of economic volatility in banking sector of Bangladesh. Thus, by forecasting the directional deviations it could make financial policymakers aware of the changes at early stage in financial markets and banking industry and privilege them to undertake precautionary steps for preventive purposes. The constructed MPI should have a incredible lead time of about 5 to 7 months on an average in case of prediction against leading for the reference series. By renovating financial efficacy of venture banks, Bangladesh also should recover their subsequent banking system to execute these suggestions.

In perspective of the economic vulnerability faced by banks in financial sector, this study mirrors the methodology used by Shumway (2001) – the dynamic hazard model that is able to forecast systemic risk in financial market arena. Here, the terminology followed is based on the CAMELS framework variables: capital adequacy, asset, management, earnings, liquidity and sensitivity to market risk. The objective of this study is to construct a macroprudential indicator (MPI) for the case of Bangladeshi financial market. The result will then be tested for robustness with macro-stress test. Lagged independent variables will be used in the simple hazard model to allow early prediction of MPI in the year in which the crisis happens. The empirical findings can be used as a guideline for the Bangladesh Government and policy makers in accessing, examining and forecasting the health of the Bangladeshi financial system and formulate suitable financial system policies for control. MPI generates information about systemic risk allowing the detection of potential economic crises functioning as an early warning indicator. Government and policy makers will be able to make early preparation in cushioning any potential crises by means of the MPI. Thus the impact of the crises could be minimized and eventually reduce its impact on the Bangladesh economy. The specific objectives are to assemble a novel MPI that is able to recommend early signals of financial market vulnerability, to identify the MPI turning points and establish a comprehensive reference chronology for Bangladeshi financial market and to evaluate the predictive performance of newly constructed MPI on characterizing Bangladeshi financial sector.

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.

It has always been believed that government ownership would lead to bad financial performance and overstaffing in any organization. This study aims to examine the effect of government ownership on staffing level and the financial performance of Kuwaiti bank over the period 2010-2018. Using the financial data of ten banks listed at Kuwait stock exchange (KSE), results shows that there was s statistically significant direct relation between government ownership and overstaffing and statistically significant inverse relation between government ownership and the financial performance of banks measured by return on assets (ROA). On the other hand results show that there was no relation between overstaffing and the financial performance of Kuwaiti banks.

This research examined bankers’ perceptions of environmental sources of financial risks and its impact on commercial banks in Ghana. Primary data was collected from a purposive sample of ninety-six (96) middle–level bank managers using structured questionnaires. Time series secondary data on banking performance (denoted as ROA and ROE) and stability (denoted as CAR and NPLR) and growth of five major industrial businesses (including agriculture, mining, construction, manufacturing, and trade) as the environmental sources of financial risks, for a period of 13 years (2006-2018) was further obtained for analysis. Data was analyzed using the sample t-test and the multivariate dynamic panel regression model. The results show that, in bank lending, mining was perceived to be the topmost source of indirect environmental risk (credit and reputational risks), while agriculture was perceived to be the leading source of direct environmental risk (business risk). We found that perceptions of environmental sources of financial risk by mangers of locally owned banks differed from that of foreign owned banks. Growth of mining, trade and manufacturing positively influenced banking performance while the growth of construction and agriculture negatively influence banking stability. The study thus provides supportive evidence that commercial banks require set standards that guide clients’ business towards environmental sustainability

This study examined the mediating role of net interest margin (NIM) on the nexus between market structure and banks’ performance. Two ordinary least-squares models with a path analysis model were applied to analyze the data. The first regression model measured the indirect effects of market structure, total assets, geographic expansion, and specialization on ROA through NIM and revealed that the higher market share of loans positively effects on bank’s performance and statistically insignificant. Similarly, the geographic expansion was observed to hurt the bank’s ROA, but statistically insignificant. On the other hand, the indirect effect of total asset size and specialization was negative, but the first one was statistically significant, and the second was statistically insignificant. The result of the second regression model measured the direct effect of antecedent variables on the ROA and revealed that the market structure, geographic expansion, and specialization were negatively related to performance measure ROA. However, the direct effect of total assets size was positively related to ROA and statistically significant. The results of the two regression models based on total effects revealed that a higher bank size appeared favorable to Nepalese CBs and was found to have positive effects on ROA but the geographic expansion was a negative effect on ROA, and statistically significant. The results of the study might be helpful to Nepalese bankers, regularity authorities, and other concerned stakeholders to take an effective decision about the direct, indirect, and total effects of chosen antecedent variables on consequent variables through the mediating role of NIM.

Abstract For risk and capital measurement, banks and other financial institutions need to meet forthcoming regulatory requirements. However, it is a serious issue to think that meeting regulatory requirements is the sole or even the most important reason for establishing a scientific, sound risk management system. To direct capital to activities with the best risk/reward ratios, managers need reliable risk measures. To stay within the limits imposed by readily available liquidity, by creditors, customers, and regulators, they need estimates of the size of potential losses. They need mechanisms to monitor positions and create incentives for prudent risk-taking by divisions and individuals. Risk measurement deals with the quantification of risk exposures, whereas risk management refers to the overall process by which managers satisfy these needs and follows to define a business strategy, to detect the risks to which are visible, quantifying those risks, and to control and understand the nature of the risks it faces. This research focuses on the economic vulnerability faced by banks in the financial sector in terms of the crises issues perspective of economic distress. Here, the methodology followed is based on the CAMELS framework variables. CAMELS is an abbreviation for: capital adequacy (C), asset (A), management (M), earnings (E), liquidity (L) and sensitivity to market risk (S). Based on these terminologies, a couple of variables should be selected, such as capital asset ratio, non-performing loan, cost income ratio, industry production index, non-interest income, reserve of gold, inflation, stock turnover ratio, real interest rate as component series and return on equity (RoE) as reference series to identify the turning points of economic vulnerability in the banking sector in Bangladesh. Thus, by forecasting the directional changes it could make policymakers aware of changes in the financial markets and banking economy and allow them to undertake preventive steps for remedial purposes. The constructed MPI should have a remarkable lead time of about not less than 6 months on average in case of prediction against the leading for reference Series.By mending the financial efficacy of investment banks. Bangladesh also should improve their corresponding banking system to implement these suggestions.  

This research examined the impact of Basel III capital regulation (BCR) on credit risk (CR) using a sample of 25 commercial banks in Lebanon over the period 2012–2017. BCR is measured using the capital adequacy ratio (CAR) and the common equity tier one ratio (CET1 ratio), CR is measured using net provision for credit losses /total assets. To analyze the data, we constructed a hybrid model based on 3 statistical approaches. First, we modelled the dual impact of BCR and CR using probabilistic inference in the framework of Bayesian Belief Network formalism (BBN). Second, to highlight more about the correlation between BCR and CR, we used Spearman correlation test as a nonparametric approach. Third to study the simultaneous effect of CAR and CET1 ratio on CR we applied multivariate regression analysis. By analyzing the probabilistic inference for the first approach we concluded that there is an effect of BCR on CR especially for the high level of CET1 ratio, but when we investigated more if this effect is significant using the Spearman correlation test and the multivariate regression analysis, we concluded that there is no effect statistically significant of Basel III capital regulation (BCR) on credit risk (CR).

The main aim of this study was to empirically assess the main microeconomic factors that affect a bank's performance. The objectives were to ascertain if there is a relationship between the performance variables with the microeconomic variables, determine those that are significant and their impact on the performance of banks in Zimbabwe. An econometric model was built from balanced panel data and the Arellano-Bond estimation procedure was employed. The empirical analysis was carried out on a sample of 17 banks that were operational in the years 2010 to 2017 in Zimbabwe. Return on Assets (ROA), Return on Equity (ROE) and Net Interest Margin (NIM) were used as the performance indicators in the analysis. The results indicate the main microeconomic factors to be those attributed to growth, credit risk, capitalisation, managerial efficiency, liquidity and diversification in the Zimbabwean financial institutions. Performance in these institutions is generally good as measured by positive persistent profits, that is, ROA, ROE and NIM. These returns reflect the extent to which these institutions are resilient to the economic crisis.

Purpose: Using panel data approach in Pakistani banking sector for 7 year time period from 2010 to 2016, the aim behind this study was to examine the bank specific, industry specific and macroeconomic determinants of bank profitability Research Design: Quantitative research design has been employed with OLS, random effect model and fixed effect model, moreover regression and correlation analysis has been used in this study Findings: Rise in NPLs ratio, Loan loss provision, inflation and exchange rate reduces the profitability of banks while increase in market power, bank size, capital adequacy enhance the profitability Practical Implication: The deleterious impact of different indicators on profitability of banks shows that distressed banking sector can cause hindrance in not only growth of financial sector but can also cause the poor growth of economy. Outcomes of the study emphasis on the need of clear-out of NPLs to keep financial sector sound as NPLs cause high loan loss provision which effect the capitalization of banks that ultimately effect the economic growth of financial as well as other sectors of economy. Banking supervisory agencies should pay attention towards banking monitory policies and banks macroeconomic policies Originality/value: This study examine the impact of all three types of indicator (Bank specific, industry specific and macroeconomic) on banks profitability by employing latest data from 2010 to 2016 in which major reforms were held in banking industry of Pakistan because there exist rare studies with all three types of variables with latest figures

Banks are believed to  instrumental to economic growth because it provides the financial backbone needed to spur economic development through business creation and expansion. A healthy and resilient banking sector signals economic growth and development that is sustainable. The efficient transfer of funds from those that has surplus of them towards those that need them has been made possible due to the intermediation of banks. In the Philippines, banking formally started in 1851 with the establishment of the Bank of the Philippine Islands, which up to this day, stands to be one of the country’s biggest and most stable universal bank. This study analyzes how universal banks grew over the years, and determines whether a correlation exists between universal bank growth and economic growth, using the variable of GDP growth rate as proxy for economic growth. The study showed that at the most recent periods, universal banks’ ROE and ROA are negatively correlated with GDP growth rate.   Key words: Universal banks, History of banking, Economic growth of the Philippines, GDP growth rate

The aim of the empirical study is to investigate credit risk determinants in banking sectors across three kinds of South Asian economies. An accumulated sample of 105 unbalanced panel data of financial firms over the period of 2000-2015, by applying General Method of Moment (GMM) estimation techniques one-step at the difference in order to identify factors influencing credit risk. This study is inspired by two broad categories of explanatory variables which are bank-specific and macroeconomic. Bank-specific factors influencing unsystematic risk, while macroeconomic factors promoting systematic risk. The study uses a proxy of non-performing loans for credit risk in banking sectors of Pakistan, India, and Bangladesh. The empirical results have been found aligned with theoretical arguments and literature as expected. In comparison, NPLs in Pakistan is greater than India and Bangladesh, while India has the lowest ratio of non-performing loans. The study documents that bank-specific factors (inefficiency, profitability, capital ratio and leverage) have a significant contribution towards credit risk. Further, the study also finds a significant impact of macroeconomic variables on non-performing loans. While, the result in the case of Bangladesh predicts contradictions that have no significant effect on non-performing loans at various levels. The overall results indicate that credit risk is not influenced by only external factors but also affect by internal factors like bad management and skimping etc.

The banking sector in Kosovo continues to have a high level of sustainability and financial stability. Two substantial components for the stability of the banking system appear to be liquidity and liquidity risk. The purpose of this paper is to analyze liquidity management in Kosovo's commercial banks through liquidity risk indicators from 2008 to 2017. By comparing the methodology of the data presented, the study will assess the state of management of the liquidity risk of commercial banks. From 2008 until now, commercial banks in Kosovo have had liquidity reserves at a level higher than the level required by CBK, which means that exposure to liquidity risk was minimal.

Non-performing loans (NPLs) present one of the most controversial issues in both developed and developing countries. The main purpose of this paper is to analyze and compare the loan portfolio and NPLs in the Western Balkan countries: Albania, Bosnia and Herzegovina, Kosovo, Macedonia, Montenegro, and Serbia for the period 2008-2015. Besides, this research aims to make a comparative analysis of some other macroeconomic indicators and industry factors that affect them such as GDP, banking sector assets, loan portfolio, asset participation in GDP, credit participation in GDP, deposit credit ratio, the NPL report on total loans. The results show that the NPL have had a growing trend in the post-global financial crisis, with different variations. In this regard, the highest rate of NPL reflects Serbia, Albania, followed by Montenegro, B&H, and Macedonia, while the lowest rate is in Kosovo.

Banks between the financial services they provide play significant roles in the country's economy The importance of banks in Kosovo is one of the essential catalysts in economic growth. The banking industry based on efficiency and performance industryis the leading indicator of the country's financial stability The pace of economic growth and long-term stability in the country varies from the level of credit and for what economic activities the bank finances. Credit risk is the primary determinant of banking performance. The higher the risk that the higher the risk is the probability of bank loss and vice versa In this study banking activities will be discussed and events in general, as well as an analysis of the financial system especially at banks, with particular emphasis on the importance of credit risk management.