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The purpose of this paper is to investigate the effect of bank specific factors on interest rate in banking financial institutions (BFIs) of Uganda.

To analyze the effect, an OLS random effects regression estimate on a data set of 24 banks from 2008 to 2016 from Bank of Uganda Depository Corporation survey was carried out. Studied bank specific factors including liquidity, operational efficiency, credit risk, capitalization and lending ratio are considered.

The results indicate that liquidity, operational efficiency, capitalization and lending out ratio affect the interest rate while credit risk does not.

The study has confirmed that bank specific factors influence interest rate and other factors such as industry-level and indirect macroeconomic indicators need to be explored. The differences in categories of banks on interest rate would be of importance. Finally, this study concentrated on banks in Uganda, future study would focus on the comparison of Ugandan banks with those of other countries in the East African Region.

Bank managers should invest in up-to-date technology to reduce operational costs and improve efficiency. Managers of bank should take interest on equity mobilization, because it constitutes a cheaper source of capital to finance asset used in operations and long-term needs of borrowers financing. Government should consider a legislation that provides incentives toward savings and reduction in tax for bank inputs.

This is the first study that investigates the effect of bank specific factors on interest rate in Uganda’s BFIs.

The purpose of this paper is to examine the factors that influence the variability of loan losses (termed as non-performing advances or NPA in India) of Indian banks in the public sector during the period of five years from 2001 to 2005.

The analysis is based on a panel approach, which considers both spatial and time dimensions of observations. Panel regression was used to explore the impact of different bank-specific factors on NPAs of 27 public sector banks (PSBs). Standard tests were used to find out suitability of different models of panel data analysis. Eight bank-specific factors were identified for analysis on the basis of review of extant literature.

Certain bank-specific factors, in particular, net interest margin and capital adequacy ratio exhibit negative and significant impact on gross non-performing advances (GNPA) ratio of Indian PSBs. The results also suggest that relative quantum of sensitive sector (SEN) (comprised of commercial real estate, commodity and capital market) advances has a positive relationship with NPA ratio, and such a relationship is statistically significant.

The sample is restricted to India and may not be reflective of other countries. The study considers bank-level factors, and there are some macro factors (e.g. gross domestic product, interest rate and inflation rate) which could have explained the variability of GNPA ratio.

Provisioning against loan losses is a major issue for stability of the banking system. Identification of appropriate causes of variability of such loan losses is important for managing credit portfolio of a bank. A positive and significant relationship between SEN advances and NPA calls for a more cautionary approach toward lending to those sectors.

This paper is believed to be the first attempt to empirically examine the role of bank-specific factors. This study attempts to enrich empirical research in the field and provides an insight into the role of various bank-specific factors on loan losses in the context of Indian PSBs. The study provides contrary evidence regarding the role of priority sector advances on a GNPA ratio.

Using bank-level data over the 1994–2015 period, the authors aim to investigate the role of bank-specific factors on credit risk in Italy by considering two different groups of banks, namely, cooperative and non-cooperative (commercial and popular), in different local markets.

Relying on highly territorially disaggregated data at labour market areas’ level, the authors estimate the impact of the role of bank-specific factors on credit risk in Italy from the estimation of a fixed-effect estimator. Non-performing loans to total loans has been used as a proxy of credit risk; the bank-specific factors are as follows: growth of loans, reflecting credit policy; log of total assets, controlling for banks’ size; loans to total assets, reflecting the volume of credit market; equity to total assets, capturing the solvency of banks and reflecting their capital strength; return on assets, reflecting the profitability of banks; deposits to loans, reflecting the intermediation cost; cost of total assets, reflecting the banks’ efficiency or volume of intermediation cost.

The empirical findings suggest that regulatory credit policy, capitalisation, volume of credit and volume of intermediation costs are the main bank-specific factors affecting non-performing loans. Nevertheless, the present analysis suggests that the behaviour of cooperative banks’ behaviour seems to be in line with that of commercial rather than popular banks, casting doubts about the feasibility of their credit policies. It turns out that recent reforms involving popular and cooperative banks represent the first step toward the enhancement of the stability and efficiency of the Italian banking system. While the present study’s benchmark results are not particularly affected by the degree of competition in the banking sector and by banks’ size, it shows that both cooperative and non-cooperative banks have undertaken more prudent credit policies after the advent of the financial crisis and the introduction of the Basel regulation.

The relationship between bank-specific factors and credit risk has been analysed using a rich sample of cooperative, commercial and popular banks in Italy over the 1994–2015 period. The authors rely on labour market areas being sub-regional geographical areas where the bulk of the labour force lives and works. The contribution is motivated by the financial distress experienced after the 2008 financial crisis, which has significantly hit the Italian banking system and cooperative banks in particular.

Every shock, starting from the banking sector reform in 1992 to the global crisis due to Covid-19 pandemic, affects the performance of banks. The shocks and transformations jeopardise the bank’s performance. This study cover period of 30 years starting from 1992. So, the reason behind taking only public sector banks is that after 1991–92 many banking sector reforms took place, and many new private sector banks and foreign sector banks entered into competition due to the liberalization, privatization, globalization (LPG) policy. So, it has been difficult for public sector bank to manage their performance in a competitive market. So, the purpose of this study is to find out influencing factors of bank performance especially public sector bank, because, it has been vital to identify factors influencing their performance.

The current study explores the determinant of the performance of public sector banks in India. Currently, in India, 12 banks are public sector banks, which capture 59.8% market share in the banking industry. After 1994 new licences were issued by Reserve Bank of India for many banks, and foreign sector banks entered the market as an effect of LPG policy, and market competition is one of the significant determinants of the performance of banks. Thus, the panel regression model is used to analyse the impact of various determinants on the performance of public sector banks (from 1992 to 2021). Return on equity and return on assets are used as indicators of performance, whereas influencing factors are divided into two parts, bank-specific factors, which include bank size, asset quality (AQ), liquidity, credit deposit ratio (CDR), capital adequacy, debt-equity ratio, employee’s productivity and macroeconomic factors which include inflation rate, tax rate and gross domestic product (GDP).

Results of the study show that bank size is not an essential factor for measuring bank performance because it is insignificant with both indicators of performance. AQ, liquidity ratio and CDR are significant in both models with negative impact. Macroeconomic factors like GDP are insignificant with both indicators with positive relations and tax rates are significant with a positive relationship. The inflation rate is significant but affects negatively to performance.

This study only focuses on public sector banks. So, the results for private and foreign sector banks might differ. Considering the larger market share compared to other sector banks, the authors are focusing on public sector banks only. Foreign banks and cooperative banks are not included current analysis because of huge numbers and different working environments.

Determining influencing factors of bank performance is crucial because it will help the bank take various policy implications and formulation. Since independence measuring bank performance are important area.

The purpose of this paper is to provide an understanding of the banking needs of urban informal poor consumers in South Africa. These consumers find it difficult to obtain access to banking products.

A survey of consumers was undertaken in a large informal settlement outside Johannesburg. A qualitative exploratory pilot study was undertaken first to gain a better understanding of these consumers and to develop a research instrument. Second, a quantitative analysis was undertaken among 200 households.

Banking products used by the sample are discussed as well as all their patronage motives. It was established that the majority of consumers did have a bank account and there was a significant association between having an account and various demographics such as income level, employment status and level of education.

Each informal settlement may have unique characteristics and therefore it may be difficult to generalize the findings.

Banks will have to address the patronage factors of these consumers as they have very different needs when compared to middle and upper income customers. Specify strategies are recommended to bank management.

No study has been done on the banking needs of this segment of the market and very little is known about the urban informal poor in general. This paper gives insight into how banks can play their part in uplifting the poor in societies where they make up large segments of the population.

Among all of the world's continents, Asia is the most important continent and contributes 60% of world growth but facing the serving issue of high nonperforming loans (NPLs). Therefore, the current study aims to capture the effect of credit risk management and bank-specific factors on South Asian commercial banks' financial performance (FP). The credit risk measures used in this study were NPLs and capital adequacy ratio (CAR), while cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR) were used as bank-specific factors. On the other hand, return on equity (ROE) and return on the asset (ROA) were taken as a measure of FP.

Secondary data were collected from 19 commercial banks (10 commercial banks from Pakistan and 9 commercial banks from India) in the country for a period of 10 years from 2009 to 2018. The generalized method of moment (GMM) is used for the coefficient estimation to overcome the effects of some endogenous variables.

The results indicated that NPLs, CER and LR have significantly negatively related to FP (ROA and ROE), while CAR and ALR have significantly positively related to the FP of the Asian commercial banks.

The current study result recommends that policymakers of Asian countries should create a strong financial environment by implementing that monetary policy that stimulates interest rates in this way that automatically helps to lower down the high ratio of NPLs (tied monitoring system). Liquidity position should be well maintained so that even in a high competition environment, the commercial is able to survive in that environment.

The present paper contributes to the prevailing literature that this is a comparison study between developed and developing countries of Asia that is a unique comparison because the study targets only one region and then on the basis of income, the results of this study are compared. Moreover, the contribution of the study is to include some accounting-based measures and market-based measures of the FP of commercial banks at a time.

The purpose of this paper is to investigate how bank-specific factors affect the riskiness of conventional and Islamic banks in response to shocks in major financial indices as market conditions change.

The authors use a multivariate quantile model using daily equity returns data to analyze financial risk spillovers in the values at risk that may occur between major financial indices and the equity prices of conventional and Islamic banks worldwide. Then, using both quantile and quantile-on-quantile models, the authors examine the effects of bank-specific variables such as leverage ratio, bank size, return on equity and capital adequacy ratio on the initial impact of shocks in major global financial indices on bank equity price returns at different quantiles of shocks and bank-specific variables.

The findings reveal that major financial indices can predict bank stock returns. Moreover, the authors find that the effect of bank-specific factors on the riskiness of banks is heterogeneous in that it depends on the bank type (Islamic vs conventional), the level of banking variable (high vs low) and, more importantly, market conditions.

To the best of the authors’ knowledge, this is the first study that compares the dual banking system with stock market performance while considering bank-specific variables as market conditions change. The results of this study reveal that the effect of bank-specific variables on bank performance varies according to different quantiles of shocks and bank-specific variables. Islamic banks may echo or differ from conventional banks depending on the specific factor under investigation.

The purpose of this paper is to investigate the determinants of interest rate in emerging markets, focusing on banking financial institutions in Uganda.

Using the net interest margin model, interest rate was estimated by applying a panel random effects regression method on 24 banks, while controlling for bank-specific factors, industry and macroeconomic indicators. Data were drawn from annual reports provided by Bank of Uganda Depository Corporation survey from 2008 to 2016.

The results indicate that liquidity, equity capital, market power and reserve requirement have a positive effect on interest rate. The study further finds that operational efficiency, lending out ratio, concentration, public sector borrowing and private sector credit have a negative effect on interest rate. However, credit risk does not influence interest rate.

Studied banks are grouped in one panel data set; future studies would focus on the differences in banks and establish how these differences affect interest rate. Future study would also focus on how the determinants of interest rate in Uganda are compared with those of other banks in other emerging market countries.

Bank managers need to take interest in equity mobilization because it is a reliable and cheaper source of funding bank operations. Banks should emphasize efficient operations to reduce on the cost of doing business. Government should utilize funds borrowed from banks in efficient ways to improve economic growth. The central bank should minimize the use of reserve requirement as a means of controlling money in circulation.

This is the first paper that uses annual report data from several banks and periods to investigate the determinants of interest rate in an emerging country.

The purpose of this paper is to examine and compare the impact of oil and gas prices shocks on the non-performing loans (NPLs) of banks at the aggregate as well as at the level of commercial and Islamic banks in Qatar over the period 2000-2016.

Using the West Texas Intermediate Database, BankScope Database, World Bank’s World Development Indicators Database, and International Monetary Fund Database, the authors use a one-step system generalized method of moments dynamic model to examine and compare the association between oil and gas prices shocks with NPLs in Qatari banks. The authors also test the hypotheses of direct and indirect impacts of oil price shocks and gas price shocks on bank NPLs.

The results indicate that oil price shocks and gas price shocks do not have directly affect NPLs of Qatari banks at the aggregate level, while they have indirect effects that are channeled through the country-specific macroeconomic and institutional factors. The authors find that oil and gas prices shocks affect NPLs of Qatari Islamic banks directly through extended oil and gas-related cash flows, while their impact on the NPLs of Qatari commercial banks is indirect. In other words, Islamic banks in Qatar greatly benefits from increased cash flow caused by the rise in the oil and gas prices, which make their NPLs, much lower than that in commercial banks. Better capital cushion, better managerial efficiency, better risk management, and liquidity management systems should be used by the Islamic banks in Qatar to expand their customer base. The authors also find that positive fiscal stance of the government reduces the NPLs in both commercial and Islamic banks.

The results of this study necessitate policy measures that can counter the effects of changes in oil and gas prices on the growth of bank NPLs.

It is widely recognized that oil and gas prices and the level of production are of great importance to the economic development of oil and gas-exporting countries. So far, however, no econometric study has been reported in the literature which analyses and compares the impact of oil and gas prices shocks on the NPLs of commercial and Islamic banks and also at the aggregate level in any of the oil economies. Thus, this study provides the first empirical evidence on distinct direct and indirect channels through which oil and gas prices shocks may affect bank NPLs.

Bank branching plays a significant role in a wide range of economic activities. Existing studies on determinants of bank branching activities largely focus on developed countries; studies devoted to developing countries are scant. The purpose of this paper is to examine the determinants of bank branching activities in one of the largest developing country India.

The authors employ a unique longitudinal data to study the determinants of bank branch location in India. These data are collected at the state level covering 25 Indian states for the period 2006–2017. The authors employ Poisson regression that are better suited for modeling counted dependent variable.

First, region and bank specific factors such as size of population and bank deposits influence location of bank branches. Second, the relationship between these factors and branch locations is heterogeneous across different types of banks and across states with different business environments.

First, from the view of banks, considering the factors of branch location are crucial in order to set out branching strategy. Irrespective of policy measures aimed at promoting financial inclusion in India, the authors show that banks consider economic activities in the region in locating their branches. Second, from the view of policy makers and regulators, such branching strategy could potentially contribute to financial exclusion. As a result, population in the less developed regions may be excluded from accessing financial services. Hence, policy makers and regulators should take into this account when formulating policies aimed at promoting financial inclusion.

First, while existing studies largely focus on developed countries, studies devoted to developing countries are scant. To the best of our knowledge, the authors have not come across any study that investigates the determinants of bank branch location in India, so the authors reasonably believe that this study is a first-of-its-kind. Second, the study provides a new perspective concerning how regional and bank specific factors influence banks of different ownership in locating branches. Third, while traditional regression used to be a method of choice among early studies, the authors employ Poisson regression that is better suited for modeling counted dependent variable.