International Journal of Finance & Banking Studies

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.  

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.

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.

E-commerce is gaining popularity due to its importance for both merchants and consumers, particularly in light of the COVID-19 pandemic, which restricts mass movement and gathering, as well as the high costs associated with traveling to different markets. Despite mounting evidence demonstrating the importance of internet in retails business, little is known about the potential mechanisms that increase consumer purchasing intentions when using online shopping platforms. In today's high customer sensitivity to service quality, successful entrepreneurs have recently thrived under competitive pressures. Online transactions are more difficult because buyers and sellers do not know each other, yet they must provide financial information to intermediaries. Thus, it is now clear that increasing customer trust is a viable strategy for driving e-business success today. Considering this, a new model demonstrating a potential mechanism that increases customers' trust in intermediaries and thus leads to their online purchasing intentions was developed. This innovative model connects website quality to the online purchasing intentions of the customers, using trust in intermediaries as a mediator and moderating the effect of perceived usefulness. To prove or disprove the assumptions highlighted in this study, a cross-sectional research design was used with data from 568 clients of nine domestic e-commerce platforms operating in Rwanda. To investigate the relationship between the variables hypothesized in this study, a variety of methods and tools were used. To assess the potential effect of each variable in this model, we used CFA in SEM-Amos, mean and standard deviation in SPSS, and Hayes macro process. The overall results obtained using the various techniques specified supported the current hypothesized model. We believe that the current study provided an innovative and useful mechanism as one of the potential solutions for today's merging online businesses.

The banking system’s role as an intermediary between depositors and borrowers makes its stability a crucial element of the economy. Individual bank stability impacts the stability of the financial sector and, consequently, the real sector and economic growth. This study is a detailed investigation of bank stability scores for the Turkish banking sector. Turkey experienced a major banking crisis from 2000 to 2001. However, with an improved regulatory environment and structural reforms, its resilience to shocks increased significantly in subsequent years. The present study contributes to the literature in three areas. First, it applies eight variations of the Z-score to the Turkish banking sector to test the importance of time and risk variation. Second, it investigates the impact on stability scores of several factors–the implementation of new capital regulations and Basel III liquidity rules, the Turkish lira crisis and the effects of COVID-19). Finally, it measures the contribution to systemic risk of each Turkish bank using the leave-one-out (LOO) Z-score method; this is the first study to use this method to analyse the contribution of different bank types to the overall stability of the sector.

This exploration aims to test and dissect factors that impact bank fiscal performance and their impact on shareholder tips. The variables used are E-Banking, credit handed as an independent variable, and ROE as a dependent variable. This exploration also looks at the influence of ROE on shareholder tips proxied by the DPR. This exploration was conducted in all BPDs in Sumatra, there are 8 BPDs registered with the OJK during the 2019 – 2022 period. The exploration system used was descriptive exploration with a quantitative exploration approach. Data recycling analysis uses multiple and simple retrogression analyses. The exploration results show that E-Banking and the credit handed have a significant influence on ROE, both concertedly and collectively. Meanwhile, fiscal performance (ROE) also influences shareholder tips (DPR).

The Covid-19 pandemic has hit the world since the end of 2019 and has damaged the world economy, including Indonesia. Banking as a financial institution that provides funding to companies is also affected. Because the pandemic has reduced the company's performance, and this decline in performance has had an impact on banking. The aim of this research is to test whether the Covid-19 pandemic has an impact on the relationship between risk factors and bank performance. Bank performance is measured by profitability which consists of return on assets (ROA) and return on equity (ROE), while bank risk in this study consists of credit risk, liquidity risk, capital, operational risk and the Covid-19 pandemic. The population in this research is the Regional Development Banks (BPD) in Indonesia totaling 34 banks with a sample of 30 banks. The observation period was 4 years with quarterly data so that 320 observation data were collected. Hypothesis testing uses panel data regression, and to select the best regression model, the model will be tested using the Chow-test, Hausman-test, and Lagrange Multiplier test. After the model test was carried out, the fixed effect model was selected as the best model. The research results show that credit risk and operational risk have a significant and negative influence on all profitability, both ROA and ROE. Meanwhile, liquidity risk (LDR) has no effect on both types of profitability, while capital has an effect on ROE but has no effect on ROA. Another interesting result is that the Covid-19 pandemic has no impact on the influence of risk on bank performance.

This research aims to see to how far extent the user interface and user experience an impact on consumer have purchasing decisions through E-Impulse Buying. The correspondents of this study were IKIP PGRI Samarinda students who were active in online purchases through the Shopee application with a usage time of 0-6 years and between 18-24 years of age. The total sample is 131 respondents using purposive sampling method. Research data comes from questionnaires distributed using Google Forms or Manually. The data analysis technique uses path analysis through the SPSS 22 program. The results found show that the user interface and user experience have an impact on purchasing decisions directly, the user interface has an impact on purchasing decisions through E-Impulse Buying, and User Experience has no Impact on decisions purchase through E-Impulse Buying.  

The aim of this paper is to evaluate barrier options by considering volatility as stochastic following the CIR process used in Heston (1993). To solve this problem, we used Monte Carlo simulation. We studied the effects of stochastic volatility on the value of the barrier option by considering different values of the determinants of the option. We illustrated these effects in twelve graphs. We found that in general, regardless of the parameter under study, the stochastic volatility model significantly overvalues the in-the-money (ITM) barrier options, and slightly the deep-in-the money (DIP) options, while slightly undervaluing the near-out-the money (NTM) options.

In the modern world banks are unique. Formally, they are commercial enterprises, but in fact they have a government role, controlling all of the financial activity of the population and organizations. This article examines the roles of banks in the surveillance and pressuring of people that are not usually publicized. There is no political subtext in this article, as the situation described is typical for all countries. The fact that the majority of the examples given are from Russia and the USA simply reflects the experience of the authors. The other important thing to note is that the article describes the ongoing war of “banks against the people,” and the cascade of events is accelerating with nearly every month. And the winner in these intermittent skirmishes is always the same.