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Referring to the provisions of Law Number 7 of 1992 and its amendments to Law Number 10 of 1998 concerning Banking, it is explained that a Bank is a business entity that collects funds from the public in the form of deposits and distributes them to the public in the form of credit and or other forms of to improve the standard of living of the wider community so that the banking industry greatly affects the overall stability of the economy because banking institutions are intermediary institutions that bridge people who do not need their funds (surplus) to be deposited in banking institutions as deposits and distributed by these institutions to people who need them in a productive form of distribution. The role of banking institutions is systemic; in other words, banking is an important part of the economic system which will cause a multiplier effect if it is not healthy or in this case, it becomes a failed bank. The main function of banking in macroeconomic policy infrastructure is indeed directed in the context of how to make money effectively and efficiently to increase economic value, which requires the role of regulation in the economic sector as a rule for the essence and existence of banking institutions in carrying out their operations. This study is normative legal research that uses several approaches namely: the statute approach, the case approach, the historical approach, and the conceptual approach carried out with juridical concepts of banks, failed banks, bank restructuring, macroprudential and microprudential. The objective of this study is to comprehensively explain the model and system for rescuing failed banks that meet the benefits principles.

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.

The objective of this study is to examine the effect of bank lending on the growth of selected small and medium scale businesses in Nigeria. There are two basic research designs in social sciences, qualitative and quantitative orientation. However, the literature suggests a growing interest in a mixed approach (triangulation) following on from the argument that one is used to strengthen the other. Often, combining qualitative and quantitative methods, also known as the triangulation of methods, can capture a more holistic, complete, and contextual view of a phenomenon. The research is based on both qualitative and quantitative research designs.  Three research questions were addressed. Data were collected from a purposive sample of 200 respondents drawn from a population of 400 respondents. A research developed questionnaire was used for the data collection. Data were analyzed using simple percentages and tables. The result of the study revealed that Lending to SMEs encourages self-employment thereby reducing the rate of unemployment and crime in Nigeria. It also boosts industrialization as well as improving the economic situation in the Country. In conclusion, bank lending influence positively the level of economic activities and the growth of SMEs in the country. A number of recommendations were made based on the findings prominent among them is the need for Government, Commercial bank, and Central bank of Nigeria to increase lending to small and medium scale business with a view to create more jobs, reduce crime and unemployment as well as boost industrialization in Nigeria.

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 purpose of this study is to determine the effect of the level of banking health on the ratio of liquidity coverage in the corporate banking sub-sector included in the category of commercial banks based on business activities (BOOK) 3 during the 2017-2018 period with each period only taking 2 quarterly data. The sample in this study was a banking company listed on the IDX and included in a commercial bank based on business activities (BOOK) 3 consisting of 19 banks selected using the purposive sampling method, with a total of 76 data units. The analytical method used in this study is panel data regression analysis. The results of partial hypothesis testing indicate that the ratio of liquidity coverage is influenced by the level of health with the Altman Z-Score modification method and the Grover G-Score method.

This study examines the influence of credit risk on the shareholder market value of commercial banks listed in the Nairobi Securities Exchange. A mixed-method approach and concurrent design were used in this study. Logistic regression was performed to ascertain the influence of credit risk on shareholder market value of commercial banks listed in the Nairobi Securities Exchange as a quantitative method and processes tracing as a qualitative approach to trace the causal mechanism by which credit risk contributes to shareholder market value. This research demonstrated that (i)there is a relationship between credit risk and shareholder market value among the commercial banks listed in NSE; (ii) Wald (1) =41.475, p=.000, sig<.05, 2-tailed is below the permissible value of likelihood above which null hypothesis is accepted. The study concludes that there is a relationship between credit risks and Shareholders Market Value in commercial banks listed in NSE.