International Journal of Finance & Banking Studies

Increase in losses borne by banks as a result of inadequate operational risk management practices and the adverse impact on banks’ financial performance has been a major concern to bank management and regulators. This study analysed the impact of operational risk management practices on the financial performance of commercial banks in Nigeria. 10-years (2008 - 2017) secondary data extracted from audited financial statements of selected commercial banks in Nigeria was used for the study. The data was analysed using the Linear Multiple Regression Model. The results showed that there is a positive relationship between operational risk management and the financial performance of banks. The findings revealed that sound operational risk management practices impact positively on the financial performance of banks. We, therefore, recommend that banks’ management should deploy adequate resources towards understanding operational risk to ensure sound operational risk management and improved financial performance of banks.

Location selection problem in banking is an important issue for the commercial success in competitive environment. There is a strategic fit between the location selection decision and overall performance of a new branch. Providing physical service in requested location as well as alternative distribution channels to meet profitable client needs is the current problematic to achieve the competitive advantage over the rivalry in financial system. In this paper, an integrated model has been developed to support in the decision of branch location selection for a new bank branch. Analytic Hierarchy Process (AHP) technique has been conductedto prioritize of evaluation criteria, and multi-objective optimization on the basis of ratio analysis (MOORA) method has been applied to rank location alternatives of bank branch.

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.

This study aims to investigate the association between non-performing loans (NPLs) and the profitability of banks in Bangladesh. The data of twenty-five listed banks for the twelve years spanning from 2010 to 2021 have been analyzed to achieve the research objective. through the use of the ordinary least square (OLS) regression model, we found that the NPL has a negative significant impact on the profitability determined by the return on asset (ROA). In addition, the study revealed that the bank size, which is represented by banks’ total assets, is also inversely related to the profitability of the sample banks used in this research. The study concludes that the stakeholders, particularly the management of the banks, as well as the regulators, should be more cautious about NPLs and should try to lessen the level of NPLs because it can bring devastating results both on the microeconomic as well as on macroeconomic metrics of a developing country like Bangladesh.  

Bu çal??man?n amac?, Türkiye’de hayat d??? sigortac?l?k sektöründe aktif karl?l??? ile firmaya özgü faktörler aras?ndaki ili?kiyi tespit ederek aktif kârl?l???n?n etkinlikten mi yoksa yo?unla?madan m? kaynakland???n? belirlemektir. Bu amaçla, Türk sigorta sektöründe faaliyet gösteren 36 hayat d??? sigorta ?irketi aras?nda 2015 y?l? verilerine göre pazar?n toplam %83.38’ini olu?turan 15 sigorta ?irketinin 2010-2015 dönemine ait mali verileri ile performans ili?kisine yönelik Period SUR panel veri analizi yap?lm??t?r. Analiz sonuçlar?na göre, aktif büyüklü?ü, likidite ve pazar pay? de?i?kenleri ile aktif karl?l??? aras?nda pozitif ve istatistiki olarak anlaml? bir ili?ki tespit edilmi?ken kald?raç, hasar/prim oran? ve firma ya?? de?i?kenleri aras?nda ise negatif ve istatistiki olarak anlaml? bir ili?ki tespit edilmi?tir.  Analiz dönemi boyunca Herfindahl–Hirschman Endeksi de?erleri 1.500’ün alt?nda oldu?u için Türkiye’de hayat d??? sigortac?l?k sektörünün yo?un olmayan bir piyasa görünümünde oldu?u tespit edilmi?tir. Bu nedenle, hayat d??? sigortac?l?k sektöründe aktif kârl?l??? yo?unla?madan daha ziyade faaliyetlerdeki etkinlikten kaynaklanmaktad?r.

Financial inclusion, especially the adoption of fintech, has emerged as a crucial avenue for removing the financial access divides in developing countries, including Bangladesh. Following the comprehensive analysis, this article intends to outline Bangladesh's recent experiences with fintech-based financial inclusion, identify the short-comings and hence make policy suggestions. Being a descriptive research, cross-sectional and observational research approaches are applied for the explanatory analysis of secondary data. Results suggest an urban-rural gap in the implementation of digital financial services, with urban areas consistently having higher rates of fully online branches and a greater number of financial machines. Despite this, the sharp rise in the issuance of active cards is a positive sign suggesting an expansion of consumer base and an adoption of electronic modes of payment. Moreover, inter-bank electronic fund transfers and online banking have experienced increasing uptake, revealing a progressing trend towards digital transactions within the banking industry. Additionally, the study identifies a speedy growth in the number of mobile financial services accounts in both urban and rural areas. This study adds to the exchange of ideas regarding financial inclusion by carrying out a detailed study of Bangladesh's digital financial transformation, exemplifying the accomplishments, obstacles, and future research directions. It highlights the need for targeted policies and ongoing research efforts to build inclusive financial systems to serve the entire society’s interest. Nevertheless, the observations will have both theoretical and practical significance, contributing towards building capability in harnessing technology for sustainability, community uplifting, and shaping a brighter future.  

This paper aims to examine the financial performance of Bangladeshi listed commercial banks. The study analyzed the financial performances of banks categorized into three generations—first, second, and third—based on their year of commencement of operations in the country. The data of a total of 24 banks, 8 from each generation, listed in the Dhaka Stock Exchange (DSE), has been collected from audited financial statements for the time period of 13 years, from 2010 to 2022. Data has been analyzed using different ratios of profitability, liquidity, capital adequacy, operational efficiency, and credit risk. The ANOVA test also has been used to make a comparison of profitability—the return on assets (ROA), and return on equity (ROE) of the banks of different generations. According to the results, the average profitability ratios in terms of ROA, and ROE of the second-generation banks showed their credibility than banks of other generations; while first generation banks kept higher liquidity, and capital adequacy with higher credit risk than the banks of other generations. The first-generation banks also showed a lower cost-expense ratio, and a higher efficiency in terms of operation, than the banks in the second and third generations. The research also discovered that the profitability of banks of different generations significantly varies from one another.  

In the past decade, Southeast Asia has seen the development of financial inclusion, as evidenced by the growth of the penetration, availability, and usage dimensions of financial inclusion. This study analyses the impact financial inclusion has on economic growth, represented by GDP per capita growth, and unemployment using data from Indonesia, Malaysia, Thailand, the Philippines, and Cambodia. The authors employed panel data regression with fixed effect and random effect models to analyse the data. The results show that the number of commercial bank branches and outstanding loans statistically significantly affect GDP per capita growth, while the number of saving/deposit accounts does not. All three variables are shown to have a statistically significant impact on unemployment.

This study aims to enhance credit risk identification, improve loan borrower review efficiency, and increase default prediction accuracy rate using data mining and machine learning techniques. The study also employs deep learning to develop a consumer loan default prediction model that minimizes credit risks and ensures consistent development. The researchers collected data from a survey of 1000 participants, stratified into local and foreign banks, and selected the top 11 banks based on turnover and customer volume. To construct the machine learning model, Keras, a neural network library that runs on TensorFlow, was utilized. The model predicts loan applicant default likelihood. The study's practical implications demonstrate a noteworthy success rate of customer default prediction, which can significantly benefit banks. The model was evaluated on a test set of 250 records and achieved a test set accuracy of 95.2%, correctly predicting the default state of 238 out of 250 respondents.

This study aims to investigate the association between non-performing loans (NPLs) and the profitability of banks in Bangladesh. The data of twenty-five listed banks for the twelve years spanning from 2010 to 2021 have been analyzed to achieve the research objective. through the use of the ordinary least square (OLS) regression model, we found that the NPL has a negative significant impact on the profitability determined by the return on asset (ROA). In addition, the study revealed that the bank size, which is represented by banks’ total assets, is also inversely related to the profitability of the sample banks used in this research. The study concludes that the stakeholders, particularly the management of the banks, as well as the regulators, should be more cautious about NPLs and should try to lessen the level of NPLs because it can bring devastating results both on the microeconomic as well as on macroeconomic metrics of a developing country like Bangladesh.