Search results

This paper aims to explore the extent to which the control quality impacts non performing loans (NPLs) of Tunisian listed banks by integrating the guidelines of Circular No. 2011-06 issued on 20 May 2011 by Tunisian Central Bank.

Regressions using panel data are applied on a sample of 11 listed banks during the period from 2010 to 2015.

The results show that the presence of foreign directors on the Tunisian bank board affects credit risk. These administrators, with knowledge, independence and technology transfer, exercise more control than institutional administrators or state representatives. The risk committee is more effective than the other committees (audit committee and credit committee) in reducing non-performing loans. The role played by this body is the most important.

Testing empirically the impact of control quality on NPL by integrating the guidelines of the Central Bank leads to a better evaluation of reforms’ application and effective measures to strengthen the banking governance practices.

By exploring the application of the Central Bank’s guidelines for strengthening post-revolutionary banking governance practices, it becomes easy to assess the extent of the Circular No. 2011-06 by accounting practitioners, auditors and authority bodies to give the necessary recommendations for further reforms.

Wealth Management Products (WMPs) are the largest and most crucial component of China's Shadow banking, which are off the balance sheet and considered as a substitute for deposits. Commercial banks in China are involved in the issuance of WMPs mainly to; evade the regulatory restrictions, move non-performing loans away from the balance sheet, chase the profits and take advantage of yield spread (the difference between WMPs yield and deposit rate).

In this study, the authors investigate what bank related characteristics and needs; influenced and prompted the issuance of WMPs. By using a quarterly panel data from 2010 to 2019, this study performed the fixed effects approach favored by the Hausman specification test, and a feasible generalized least square (FGLS) estimation method is employed to deal with any issues of heteroscedasticity and auto-correlation.

This study found that there is a positive and significant association between the non-performing loan ratio and the issuance of WMPs. Moreover, profitability and spread were found to play an essential role in the issuance of WMPs. The findings of this study suggest that WMPs are issued for multi-purpose, and off the balance sheet status of these products makes them very lucrative for regulated Chinese commercial banks.

Non-guaranteed WMPs are considered as an item of shadow banking in China, as banks do not consolidate this type of WMPs into their balance sheet; due to that reason, there is no individual bank data available for the amount of WMPs. The authors use the number of WMPs issued by banks as a proxy for the bank's exposure to the WMPs business.

From a regulatory perspective, this study helps regulators to understand the risk associated with the issuance of WMPs; by providing empirical evidence that Chinese banks issue WMPs to hide the actual risk of non-performing loans, and this practice could mislead the regulators to evaluate the bank credit risk and loan quality. This study also identifies that Chinese banks issue WMPs for multi-purpose; this can help potential investors to understand the dynamics of WMPs issuance.

This research is innovative in its orientation because it is designed to investigate the less explored wealth management products (WMPs) issued by Chinese banks. This study's content includes not only innovation but also contributes to the existing literature on the shadow banking sector in terms of regulatory arbitrage. Moreover, the inclusion of FGLS estimation models, ten years of quarterly data, and the top 30 Chinese banks (covers 70% of the total Chinese commercial banking system's assets) make this research more comprehensive and significant.

The German banking sector has recently been facing high real estate loan default rates resulting in the accumulation of a high volume of distressed real estate debt in the banks' balance sheets. As a consequence, German banks are confronted with the workout of their non‐ and sub‐performing real estate loans to proactively solve the problem. When doing so, banks have to decide whether they want to conduct the loan workout in their own workout departments (integrative approach) or whether they prefer to outsource the workout to a third party servicer or even sell their bad loan exposure to an external investor (disintegrative approach). This paper aims to investigate this issue.

A bank's decision to employ an integrative or a disintegrative approach can be transferred into a make‐or buy‐decision as described by the transaction cost economics. The transaction between the bank and the workout manager is analysed by the transaction characteristics of the transaction cost economics. The specificity of the human capital required for the loan workout of real estate loans is a key consideration for answering the question of integration or disintegration. Assuming highly specific investments for both, the workout manager and the bank, a formal model compares the aggregated pay offs for the bank and the workout manager to determine the optimal control structure for the specific assets.

Following the assumptions of the transaction cost economics, the specificity of the investment of the workout manager (and also the bank) is crucial for the decision of integrating or disintegrating the workout of real estate loans. The degree of specificity required to perform the workout tasks depends on the status of underlying credit engagement and the characteristics of the collateral (the real estate). The formal analysis shows that the bank and the workout manager both under‐invest in integration and disintegration scenarios. However, if the degree of specificity of the investments is equal, nonintegration is superior to integration. Forward integration is superior to nonintegration, if the bank's investment is more specific than the workout manager's investment.

This research paper approaches the problematic from an academic stand point, integrating both the banking and the real estate perspective and aims to provide a recommendation for banks on the integration or disintegration of the workout unit for a certain real estate secured loan portfolio.

The purpose of this paper is to evaluate Chinese commercial banks efficiency based on different non-performing loans in the process. Moreover, we identified the difference among different types of banks (state-owned commercial banks, joint-stock commercial banks and city commercial banks) and different operation stages (deposit producing sub-stage, profit earning sub-stage and overall stage).

Assurance region (AR) restrictions are combined with a two-stage data envelopment analysis (DEA) model. The efficiency scores of 26 Chinese commercial banks (listed banks) are analyzed by a two-stage AR-DEA model in the study period of 2013–2017.

The results show that state-owned commercial banks had better performance than joint-stock commercial banks and city commercial banks over the five-year study period. The development of Internet finance has positive impact on deposit producing sub-stage and insignificant non-homogeneity existed among the different groups in the circumstances of considering different non-performing loans.

The research findings provide practical insights that help bank managers find the defects in operation process, which need to be improved.

Previous studies viewed non-performing loans as an integrated whole variable. The paper divides non-performing loans into three categories based on the risk and investigates the effect of different types of loans on bank efficiency scores.

The purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.

Data was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.

The findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.

The focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.

Policymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.

This paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

The COVID-19 pandemic deteriorated the economic situation and raised the issue of the quality of banks’ assets and, in particular, the growth of non-performing loans (NPLs). The study approaches a topical subject that is of interest to banks and society at large, as credit availability is likely to be reduced. Over the last 10 years, the Baltic countries’ banking sector has significantly improved its risk management policies and practices, increased capital ratios on its balance sheets, and created risk reserves. The current chapter examines the factors affecting NPLs in the Baltic States based on advanced econometric modelling applied to data extracted from the International Monetary Fund (IMF) and Eurostat. The study results show that credit risk management in the Baltic States has significantly improved compared to the period before the global financial crisis (GFC), the capitalisation of credit institutions is one of the highest in the European Union (EU), and banks are liquid and profitable. Lending recovered from the downturn in the first phase of the pandemic, and credit institutions have taken advantage of the European Central Bank’s (ECB) long-term funding programme ITRMO III to improve the liquidity outlook. Although the credit quality of commercial banks has not deteriorated, as the exposures of credit institutions in the most affected sectors are insignificant and governments have provided fiscal support to businesses and households, some challenges remain. The increase in credit risk is expected due to rising production prices as well as the rebuilding of disrupted supply chains. The findings allow conclusions to be drawn on the necessary actions to mitigate the credit risk of the banking sector.

This study aims to analyze bank lending behavior before and during the most recent financial crisis. Banks are more willing to grant loans during economic expansion. However, this behavior can result in reduced portfolio asset quality. The analysis tries to facilitate understanding of whether this relationship is always true. A second aim of the study is to highlight whether the impact of credit risk on bank lending behavior during a financial crisis is greater for banks that grew faster during the pre-crisis period than for other banks.

The analysis is based on a sample of banks in Italy, an example of a country undergoing a credit crunch without a lending bubble burst. The methodology is based on a panel regression and author uses different models to test his hypothesis: an ordinary least squares, a fixed effect, a least absolute regression and a Generalized Method of Momentum (GMM). This allows to mitigate some of the endogeneity problems.

The essay shows that effectively, most of the banks that grew faster during a pre-crisis period show a higher growth of non-performing loans and a greater reduction in lending activity during a financial crisis. However, 34 per cent of banks that grew faster during a pre-crisis period have a low growth of non-performing loans in the subsequent years. Finally, the results suggest that credit risk negatively affects bank lending behavior, but a higher impact relative to fast banks with respect to other banks cannot be emphasized.

Findings have some policy implications. First, given the adverse effect of the increase of non-performing loans (NPLs) on the bank’s lending activity and on the broad economy in general, there is merit to strengthen supervision to prevent a further increase and accumulation of NPLs in the bank’s credit portfolio. In addition, the supervisors could require that banks take always high credit standard when extend credit, both during positive economic cycle and during period of contraction. The using of higher credit standard could be helpful in the reduction of the pro-cyclicality of bank’s lending behavior and credit risk. Furthermore, the fact that high level of NPLs continues to impact on the bank’s lending activity and that this activity is very important for the economic recovery underlines that banks should clean-up their credit portfolios as soon as possible.

This paper contributes to the literature in various ways. The study analyzes the cyclical effect of credit growth, i.e. banks increase their bank lending behavior during good times, which leads to an increase in bad loans and a high credit risk in their portfolio. These cyclical effects are not knowingly studied together, but the literature usually analyzes the single steps of the cycle. Second, studying listed and unlisted banks allows to have a more representative sample and to analyze better the real bank lending activity considering both commercial than cooperative banks.

The present study investigates the impact of financial soundness variables on bank performance in emerging countries.

This study uses macro-level panel data from 17 countries from 2011 to 2020. The analysis adopts six models. While four models include bank profitability, the dependent variable of the other models is Bank Z Scores. Regulatory Capital to Risk-Weighted Assets, Liquid Assets to Total Assets, Non-Performing Loans to Total Gross Loans and Non-Interest Expenses to Gross Income are proxies of financial soundness variables.

The authors estimate fixed and random effects models with the Arellano, Froot and Rogers methods. Empirical results show that Non-Performing Loans to Total Gross Loans harm ROA and ROE. Regulatory Capital to Risk-Weighted Assets negatively affects ROE. Non-Interest Expenses to Gross Income on Bank Z Scores have a significant and negative effect. Moreover, Inflation, Foreign Direct Investment and GDP are macroeconomic variables that increase bank profitability.

This study contributes to the literature in different aspects. The first is the model of the study. The authors contribute to the literature regarding the variables used to measure financial soundness. Secondly, emerging countries are samples in the study. A significant part of the studies on financial soundness has focused on developed countries. Finally, the authors analyze the macro-level data. Bank soundness studies mainly investigate country-level variables. Macro-level analysis may provide an advantage in combating global financial crises.

Intellectual capital (IC) is beneficial to the improved performance of businesses, irrespective of their industry. The present study proposes to check if the use of IC can also help in improving the asset quality of banks. Thus, this study aims to examine the impact of IC and its components on non-performing assets (NPAs).

The study has been conducted with a sample of 30 Indian commercial banks and analysed over a time frame of 15 years (2004–2005 to 2018–2019). The modified value-added intellectual coefficient model has been used to measure the independent variables, IC, and its components. The dependent variable, NPA, has been represented by the net NPA ratio. Two-step system generalized methods of moments (SGMMs) have been applied for the regression analysis. Along with the short-term estimates provided by the SGMM approach, the long-term impact of explanatory variables on the dependent variables has also been seen.

The results of the study show that IC and its components are indeed helpful for the management of NPA, as they impact the problem loans negatively. Furthermore, the long-term benefits of IC in enhancing bank credit quality are more substantial.

The results from the present study can be used by bank management. The bank managers can draw inferences that the efficient application of IC can help them reduce their loan losses. Developing skills and knowledge of employees, maintaining close relations with stakeholders, significantly the customers, and putting more sophisticated processes and infrastructure to use can help banks to control their loan losses.

A major proportion of studies examining the role of intangible assets in various aspects of the banking sector focuses on the association between IC and the financial performance of banking entities. However, for banking institutions, apart from financial performance, improving credit quality is also imperative for staying afloat. Thus, to the best of the authors’ knowledge, the present study is one of the first to examine the relationship between knowledge-based assets (i.e. IC) and bank credit quality.

The purpose of this paper is to investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of non-performing loans (NPLs) and, more importantly, whether higher NPLs ratios could make the monitoring activity ineffective.

The empirical design is composed of two steps: in the first step, the authors introduce a monitoring performance indicator (MPI) of the credit process by combining the non-parametric technique Data Envelopment Analysis with some financial ratios adopted as input and output variables. As second step, the authors apply a threshold panel regression model to a sample of 298 Italian banks, over the time period 2006–2014, and the authors investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of NPLs.

This paper finds that, first, when the NPLs ratio remains below the threshold value estimated endogenously, an increase in the quality of monitoring has a positive impact on the NPLs ratio. Second, if the NPLs ratio exceeds the estimated threshold, the relationship between the NPLs ratio and quality of monitoring assumes a positive value and is statistically significant.

Due to the lack of data, the investigation of NPLs in the Italian industry across loan types combined with the monitoring effort by banks management was not possible. The authors plan to investigate this topic in future studies.

The identification of the threshold has a double operational valence. The first regards the Supervisory Authority, the threshold approach could be used as an early warning in order to introduce active control strategies based on the additional information requested or by on-site inspections. The second implication is highlighted in relation to the individual banks, the monitoring of credit control quality, if objective and comparable, could facilitate the emergence of best practices among banks.

A high NPLs ratio requires greater loan provisions, which reduces capital resources available for lending, and dents bank profitability. Moreover, structural weaknesses on banks’ balance sheets still persist particularly in relation to the inadequate internal governance structures. This means that bank management must able to recognise in advance early warning signals by providing prudent measurement together with an in-depth valuation of loans portfolio.

The originality of the paper is twofold: the authors introduce a new proxy of credit monitoring, called MPI; the authors provide an empirical proof of the Diamond’s (1991) economic intuition: for riskier borrowers, the monitoring activity is an inappropriate instrument depending on the bad reputational quality of borrowers.