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This study aims to examine the relationship between financial inclusion, CO₂ emissions and financial sustainability across 17 African countries.

Data were sourced from the World Development Indicators for the period 2004-2021. The study performs the principal component analysis, panel fixed effects model and quantile regression estimations to investigate the relationship between financial inclusion, CO₂ emissions and financial sustainability.

The study finds that an increase in automated teller machine (ATM) penetration rate, savings and credits increases CO₂ emissions. Findings also reveal that financial sustainability reduces financial inclusion, with significant negative effects on the conditional mean of CO₂ emissions and the conditional distribution of CO₂ emissions across quantiles.

This study is beneficial for policymakers, particularly in the age of digitalization and drive for low-carbon emissions, to develop green credits for energy players and investors to take up renewable and green energy projects characterized by high levels of carbon storage and carbon capture. Further, the banking sector’s credits and liquid assets should be used to finance alternative banking energy-related equipment and services, such as solar photovoltaic wireless ATMs, and fewer bank branches.

This paper aims to investigate the determinants that contribute to the financial stability and banking sector of Palestinian banks listed on the Palestine Stock Exchange (PEX) by using yearly data for the years 2012–2022.

Pooled ordinary least squares (OLS) and two-stage least squares (2SLS) were used to identify the variables and factors affecting the financial stability and banking sector of Palestinian banks. The study’s data were collected from the banks listed on PEX and from the yearly reports posted on the Palestine Monetary Authority’s (PMA) webpage over the years from 2012–2022. According to this research’s analysis, SMEs loans and capital sufficiency have a statistically significant positive impact on the stability of Palestinian banks. Unobserved heterogeneity, simultaneity and dynamic endogeneity are taken into account when using the 2SLS regression approach to adjust for the study endogeneity factor.

The study’s findings show that some factors and determinants might have both good and negative effects on financial stability and banking sector. Loans to small and medium-sized businesses (SMEs) and enough capital are two characteristics that statistically have a major favourable impact on the stability of Palestinian banks since they help the banks withstand deficits. A further potential discovery relates to the favourable effects of financial inclusion (FI) and digital financial services (DFS) on the stability of banks.

This research has faced some limitations, such as the lack of a defined index from the regulatory organizations, this research is based on information from bank annual accounts. It has mostly relied on self-developed or World Bank indexes. Furthermore, the research solely used information from the supply side (banks); demand-side data were not taken into consideration.

This paper has managerial implications for stability of banking sector. The Palestine Monetary Authority, as the central bank, must increase the percentage of bank loans directed to small and medium-sized companies and oblige bank management to adhere to adequate capital standards, which contributes to strengthening the Palestinian banking sector and increasing its profits. The study findings advise banks that are enjoying financial stability to speed up the pace of FI and DFSs because most of these reliable banks have relatively low FI ratios. PMA is responsible for preserving the stability of the financial system. PMA, decision makers and banks management must retain adequate liquidity in their institutions and raise client collateral expectations to raise credit conditions.

This paper adds some contributions to the literature. To adjust for discrepancies between various types of banks, the authors concentrate on conventional and Islamic banks, which enables us to use a homogenous data set as opposed to depending on dichotomous variables. The authors used Z-scores, which have recently been used in research, to measure stability and FI at the level of specific institutions. This research contributes in some key aspects that no prior research has addressed. Conventional banks are different from Islamic banks, and a number of issues might impact their stability. To evaluate the connection between FI and DFSs, it is important to consider the actions of bank regulators.

This paper makes a novel attempt to estimate the potential impact of credit risk on foreign direct investment (FDI hereafter), thereby focusing on a completely unexplored area in the existing empirical literature.

To provide a comprehensive understanding of the relationship between credit risk and FDI inflows, the study incorporates all the eight-member economies of the South Asian Association of Regional Cooperation (SAARC hereafter) and analyzes a panel data set, over the period 2011 to 2019, extracted from the World Development Indicators, using the suitable econometric techniques for the efficient estimations of the specified models.

The results indicate a negative and statistically significant relationship between the credit risk of the banking sectors and FDI inflows. Similarly, market size and inflation rate appear to be the two other main factors behind the increasing FDI inflows in the SAARC member economies. Interestingly, the size of the market became irrelevant in attracting FDI inflows when the Indian economy is excluded from the sample due to its higher economic weight. On the other hand, FDI inflows are not dependent on the level of trade openness, with most of the specifications showing either an insignificant or negative coefficient of the variable.

The obtained results are unique and robust to alternative methodologies, and hence, the SAARC economies could consider them as the critical inputs in formulating the appropriate policies on FDI inflows.

The findings are unique and original. The authors have established a relationship between credit risk and FDI for the first time in the SAARC context.

This paper provides a quantitative assessment of the “asset ratio” rule defined in Turkey as part of measures taken to stimulate the economy amid the Covid-19 pandemic. The main objective of the new rule was to boost credit growth in the economy and provide lending for credit-constrained households and firms that are in need. A secondary aim was to shift the denomination structure of the deposits toward domestic currency. Hence, the paper focus particularly on how the policy affected the growth rate of loans and the share of domestic deposits relative to foreign ones among the commercial banks. The policy was also heavily criticized due to the possibility that it will subjugate the banking system to excessive risk. The paper explore this possible impact by measuring how much the policy affected the default risk allowances in the banking system.

The new policy required banks with deposits above a threshold level, i.e. large banks, to maintain a certain asset ratio. Banks with deposits below the threshold, i.e. small banks, were held exempt from it. The paper implement a difference-in difference methodology to assess the quantitative impacts of the asset ratio policy by taking large banks as the treatment group, and small banks as the control group.

Difference-in-difference estimation results suggest that the asset ratio policy resulted in a 9.6% rise in loans and an 8.4% rise in government securities. Deposits also increased, with no significant change in their composition. The policy initially generated a 7% increase in the credit risk allowances of banks in the treatment group, which vanished in the following periods. Based on all these, the paper argue that the policy was successful in providing liquidity to the economy without jeopardizing the financial stability.

The findings of this study show that asset ratio policy is effective in increasing credit growth in countries with limited policy space such as Turkey. While saying this, the importance of the robust and prudent structure of the banking system in the economy should be underlined. Otherwise, the policy may have an unintended consequence of raising systemic risk. The policy suggestions also apply to advanced countries where the monetary policy has reached a natural limit due to the zero lower bound (ZLB). The ZLB problem encouraged these countries to use quantitative easing schemes in the aftermath of the Covid-19 crisis, just like the global financial crisis. However, it may take a long time to undo the effects of this policy on the balance sheets of central banks. In such cases, asset ratio policy can also be considered as an alternative tool for advanced economies notwithstanding the fact that the banking system should be prudent, well-capitalized and the country should have enough fiscal space. The main objective of the asset ratio policy was to help SMEs that were in urgent need of liquidity at the beginning of the crisis. The bank balance sheet data used in this paper does not contain information about the borrowers of the loans extended during the implementation of the policy. Analysis of this dimension using matched bank-firm level data will better demonstrate the success of the policy in achieving this goal. The paper address this as the main limitation of the paper and leave that analysis for future research.

This paper provides an important contribution to the literature by assessing a new unique policy whose objective is to stimulate loans and mitigate the impact of the Covid-19 crisis on the economy. The policy in question is predicted to have effects on the asset and liability structure and risk exposure of the banking system in Turkey. The quantitative analysis in this study estimates these impacts and discusses the effectiveness of the new policy in providing a relief for firms and households in need. Whether or not the policy caused a disruption in the sound structure of the banking system in Turkey is another question addressed in the paper.

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

This research analyzes borrowers' credit utilization through prepayment behavior in peer-to-peer (P2P) lending. The authors investigate factors influencing the decision to prepay and assess the role of P2P lending as an alternative source of consumer credits.

The authors use individual loan-level data from the LendingClub, one of the largest P2P platforms in the USA. The authors use a Logit model and a sample selection model estimated by the two-stage Heckman method. The empirical analysis considers borrower-specific and loan-specific characteristics as well as macroeconomic factors.

The authors present a number of significant findings that can enhance understanding consumers' financing decisions. The authors offer evidence that borrowers are able to take advantage of cheaper loans offered by P2P lending to better manage credit card balance and consolidate debt. The authors find that borrowers tend to prepay P2P loans quickly when the aggregate cost of borrowing is low, suggesting that P2P lending offers an efficient alternative to obtain credit. This is particularly true for creditworthy borrowers that are able to take advantage of competing sources of finance. The authors' results provide evidence that P2P lending can improve consumers' optimal credit utilization.

P2P lending has grown exponentially and has become a significant credit supplier to consumers and small businesses. While the existing literature mostly focuses on default risks, prepayment has received much less attention. This research fills in the gap and investigates borrowers' prepayment behavior in P2P loans and the role of P2P lending as an alternative source of consumer credits.

Keeping in view the robust growth of Islamic banking around the globe, this study aims to comparatively analyze the association between liquidity creation and liquidity risk for Islamic banks (IBANs) and conventional banks (CBANs) in Pakistan and Malaysia over a period of 2004–2021. The moderating role of bank loan concentration on the aforementioned relationship is also studied.

Regression estimation methods such as fixed effect, random effect and generalized least square are deployed for obtaining results. Liquidity creation Burger Bouwman measure (cat fat and noncat fat) and Basel-III liquidity risk measure (liquidity coverage ratio) are also used.

The results give us insight that liquidity creation is positively and significantly related to liquidity risk in both IBANs and CBANs of Pakistan and Malaysia. This relationship has been moderated negatively (reversed) and significantly by credit concentration showing the importance of risk management and loan portfolio concentration.

It is analyzed that during the process of liquidity creation, IBANs in Pakistan faced more liquidity risk for both on and off-balance sheet transactions in the presence of moderation of loan concentration than IBANs in Malaysia necessitating strategic policy-making for important aspects of liquidity risk management and loan concentration while creating liquidity.

Such studies comparing IBANs and CBANs comparison keeping in view liquidity creation, liquidity risk and loan concentration are either limited or nonexistent.

This study aims to examine the role of financial inclusion and institutional factors such as corruption and the rule of law (RL) on the credit risk and stability of banks.

The study considers a sample of 61 developing countries and uses very robust estimation techniques that allow controlling for endogeneity, heteroskedasticity and serial correlation, such as instrumental variables method in two-stage least squares (IV-2SLS), instrumental variables generalized method of moments (IV-GMM), as well as system of generalized methods of moments in two stages (Sys-2GMM).

The results confirm that financial inclusion and strengthening the RL can significantly contribute to reducing credit risk and improving the financial stability of banks; in contrast, the authors find that weak control of corruption aggravates credit risk. In addition, they found that greater competitiveness in the banking sector increases credit risk.

This study supports the need to promote financial inclusion and strengthen institutional factors to improve the stability of the banking sector, as well as promote general well-being in the economy.

This study contributes to the scarce literature by simultaneously using institutional factors such as corruption and the RL and macroeconomic variables such as economic growth and inflation in the relationship between financial inclusion and the banking sector, as well as considering competitiveness as an explanatory factor for banks’ credit risk and stability.

Bank creditworthiness refers to the evaluation of a bank’s ability to meet its financial obligations. It is an assessment of the bank’s financial health, stability and capacity to manage risks. This paper aims to investigate the credit rating patterns that are crucial for assessing creditworthiness of the Islamic banks, thereby evaluating the stability of their industry.

Three distinct machine learning algorithms are exploited and evaluated for the desired objective. This research initially uses the decision tree machine learning algorithm as a base learner conducting an in-depth comparison with the ensemble decision tree and Random Forest. Subsequently, the Apriori algorithm is deployed to uncover the most significant attributes impacting a bank’s credit rating. To appraise the previously elucidated models, a ten-fold cross-validation method is applied. This method involves segmenting the data sets into ten folds, with nine used for training and one for testing alternatively ten times changeable. This approach aims to mitigate any potential biases that could arise during the learning and training phases. Following this process, the accuracy is assessed and depicted in a confusion matrix as outlined in the methodology section.

The findings of this investigation reveal that the Random Forest machine learning algorithm superperforms others, achieving an impressive 90.5% accuracy in predicting credit ratings. Notably, our research sheds light on the significance of the loan-to-deposit ratio as a primary attribute affecting credit rating predictions. Moreover, this study uncovers additional pivotal banking features that intensely impact the measurements under study. This paper’s findings provide evidence that the loan-to-deposit ratio looks to be the purest bank attribute that affects credit rating prediction. In addition, deposit-to-assets ratio and profit sharing investment account ratio criteria are found to be effective in credit rating prediction and the ownership structure criterion came to be viewed as one of the essential bank attributes in credit rating prediction.

These findings contribute significant evidence to the understanding of attributes that strongly influence credit rating predictions within the banking sector. This study uniquely contributes by uncovering patterns that have not been previously documented in the literature, broadening our understanding in this field.

The purpose of this paper is to focus on managing the risk of fraud in commercial letters of credit (LC) in Bangladesh involving three parties: the seller, the buyer and the bank. It addresses the severity of LC fraud, the banks’ actions when detected and the preventive measures the relevant parties can adopt.

This research uses doctrinal and qualitative methods to propose strategic actions that benefit buyers, sellers, banks, legal professionals and judges. The study aims to explore the modus operandi used by fraudsters through thematic analysis.

The study’s findings reveal that LC fraud has escalated to a concerning level, posing a significant threat to the economic stability of Bangladesh. Measures must be taken to mitigate this risk and safeguard the country’s financial integrity. To effectively combat the risk of LC fraud, the updated version of UCP must include specific and detailed guidelines on LC fraud. This study recommends preventative measures that all parties involved must take to reduce the likelihood of fraud significantly.

Due to a lack of LC experts, the participant sample for the study in Bangladesh was limited. Nevertheless, most banking participants were highly distinguished and held the Head of Trade Finance Department position in commercial banks. A few academics and legal practitioners with LC expertise also participated in the study.

It provides cutting-edge solutions to effectively handle LC fraud risk and provides proactive measures to prevent it.