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This study aims to propose a non-linear model to describe the effect of macroeconomic shocks on delinquency rates of three kinds of bank loans. Indeed, a wealth of literature has recognized significant evidence of the linkage between macro conditions and credit vulnerability, perceiving the importance of the high amount of bad loans for economic stagnation and financial vulnerability.

Generally, this linkage was represented by linear relationships, but the strong dependence of bank loan default on the economic cycle, subject to changes in regime, could suggest non-linear models as more appropriate. Indeed, macroeconomic variables affect the performance of bank’s portfolio loan, but such a relationship is subject to changes disturbing the stability of parameters along the time. This study is an attempt to model three different kinds of bank loan defaults and to forecast them in the case of the USA, detecting non-linear and asymmetric behaviors by the adoption of a Markov-switching (MS) approach.

Comparing it with the classical linear model, the authors identify evidence for the presence of regimes and asymmetries, changing in correspondence of the recession periods during the span of 1987–2017.

The data are at a quarterly frequency, and more observations and more extended research periods could ameliorate the MS technique.

The good forecasting performance of this model could be applied by authorities to fine-tune their policies and deal with different types of loans and to diversify strategies during the different economic trends. In addition, bank management can refer to the performance of macroeconomic conditions to predict the performance of their bad loans.

The authors show a clear outperformance of the MS model concerning the linear one.

The purpose of this study is to investigate the effect of internal and external variables on the profitability of conventional banks operating on developing and underdeveloped countries, the Organization of Islamic Cooperation (OIC) states.

In this paper, the author uses ordinary least squares fixed-effects model on an unbalanced panel data set of all conventional banks operating in OIC countries (52 countries included from 57) over the period 1989-2008, 686 banks.

The results suggest that equity, foreign ownership, off-balance sheet (OBS) activities, real gross domestic product growth, real interest rate and concentration foster banks’ profitability. In addition, the results showed that the banking sector development and loans will increase banks’ profitability in the long run in the countries of the studies. In contrast, the study reported that deposits lower profitability. The study also revealed that GDP per capita, market capitalization and banks size have no impact on profitability.

The findings of this study have considerable policy implications. First, policymakers need to regulate nontraditional activities to avoid any financial crisis because banks in OIC countries are heavily engaged in nontraditional activities to boost its profit. Second, policymakers are advised to improve the deposit insurance system to insure the stability of the financial system as well as improving banks’ profitability. Third, policymakers need to improve the efficiency of the stock market, maintain small banking system and encourage foreign investments in the banking system.

The paper adds to the literature on the commercial bank’s profitability determinants. In particular, such study has not been conducted on OIC countries, and the study included all mainstream banks and incorporated the effect of deposit insurance system so far. Also, pure sample of conventional banks used as many conventional banks in OIC countries have Islamic windows or offer Islamic products. In addition, this study investigated the effect of OBS activities on net interest margin (NIM) because the studies that explored this interrelationship are limited especially for developing and under developed countries. The results showed that OBS activities contributed significantly and positively to return on assets and NIM. Moreover, this paper used a pure sample of conventional banks to avoid any biasness; see data section. Moreover, this study gives an idea about the economic situation and financial conditions of OIC countries during the period of the study.

This study is designed and directed to analyze the effect of board characteristics and audit committee attributes on the firm performance of publicly listed commercial banks of Bangladesh.

Thirty publicly listed commercial banks of Dhaka Stock Exchange (DSE) have been taken as sample for this study. Data have been collected from annual reports between 2011 and 2017 of the assessed banks. Pooled OLS model has been used for running regression model of this study.

Board independence has a negative and significant relationship with ROA and Tobin's Q. However, Board Independence has a positive and significant relationship with Stock Return. On the other hand, Board Diversity has a negative and significant relationship with ROA and ROE, which implies inefficiency of diversified board members in the context of Bangladesh. Family duality has a positive and significant relationship with ROA and a negative and significant relationship with Stock return. Board Meeting has a positive and significant relationship with ROA. Audit Committee Size has a negative and significant relationship with Tobins' Q. Independence of audit committee chairman has a negative and significant relationship with Tobin's Q and Stock Returns. Presence of non-executive directors and number of audit meetings have no significant relationship with any of the predicted variables.

Among all variables of the board characteristics, role of independent directors and participation of female directors have conflicting results in this study. This has raised a question about the fair appointment independent directors and their objective view on the board. Female directors' role is not convincing in the context of Bangladesh as most of the commercial banks are family-owned. Policymakers can tighten and supervise the appointment of independent directors to ensure good governance in the banking sector. Moreover, role of audit committee and independence of audit committee chairman have generated conflicting results in terms of market-based performance measure.

Banking sector of Bangladesh experiences huge corruption in the form of excessive NPLs and poor management quality which results in low profit for the firm. This study has explored the problems of management quality and flaws of audit committee which is hampering overall growth of banking industry. Improvement of independent directors' appointment and audit committee formation and reporting will certainly help banking industry of Bangladesh to improve overall performance.

The level of non-performing assets (NPAs) best indicates the soundness of the banking sector of a country. The purpose of this study is an effort to look into the contribution of the different banks individually to the NPA in the industry by looking into its growth pattern during the period 2010-2017. Further, the study is made to look into the effect of different groups of banks, namely, State Bank of India (SBI) and its associates, nationalised banks and private sector banks on the banking industry in this regard.

The individual private sector banks, nationalised banks and SBI and its associates have been considered for the purpose of the study. The analysis is based on secondary data collected from the Reserve Bank of India website for the period 2010-2017. The geometric mean has been used as a statistical tool for arriving at the mean growth rate of gross NPAs. Further, refinement of the result is done by comparing the growth of gross NPAs of individual banks with that of the average growth rate.

The assessment of private sector banks reveals that the growth rate of NPAs is low as compared to the nationalised banks, as well as the SBI and its associates. The nationalised banks and the associate banks of SBI failed to handle the issue of poor loans effectively due to which the growth in such loans has been phenomenally high.

The research is interesting as the study period follows the financial crisis. There is no such previous study that has looked at the perspective of banking from this angle. The research is valuable from two angles. Firstly, it brings to light the situation of the different categories of banks with regard to NPAs. Secondly, the information can be useful for investors as the issue of poor loans is a relevant one for them because it has an impact on the profitability of banks and thereby the future prospects.

To enhance the loan repayment performance of microfinance institutions (MFIs) in Pakistan, this study aims to analyze the direct impact of social capital and loan credit terms on loan repayment performance and microenterprises’ business performance while considering the mediating role of microenterprises’ business performance on the relationship between social capital, loan credit terms and loan repayment performance.

The analysis was conducted based on the data gathered via a questionnaire distributed to 316 microenterprises owners. The respondents were selected using the stratified sampling technique by dividing the target population into three influential groups of manufacturing, trading and services microenterprises. The reliability and validity of the constructs were established using (1) factor loading, (2) Cronbach’s alpha, (3) composite reliability, (4) average variance extracted, (5) the variance inflation factor, (6) the Fornell–Larcker criterion and (7) the heterotrait–monotrait ratio. The structural equation modeling technique was then applied, and the hypotheses were tested based on the structure model generated through bootstrapping by using partial least squares structural equation modeling.

The results confirm the direct impact of social capital and loan credit terms on microenterprises’ business performance and loan repayment performance. It also supports the mediating role of microenterprises’ business performance toward the relationship between social capital, loan credit terms and loan repayment performance while considering the direct impact of microenterprises’ business performance on loan repayment performance.

To date, the direct impact of social capital and loan credit terms on microenterprises’ business performance and loan repayment performance has been hardly investigated in the context of Pakistan. This study also examines the mediating role of microenterprises’ business performance toward social capital, loan credit terms and loan repayment performance. The findings will enable both MFIs and microenterprises to improve their business performance and loan repayment performance through enhanced social ties and the development of more flexible credit products that protect the borrowers’ interests and the interest of lenders.

Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.

The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación

This study aims to capture the “persistence effect” of credit risk in Indian banking industry using the bank-level data spanning over the period of 19 years from 1998/1999 to 2016/17. Alongside, the study explored how the bank-specific, industry-specific, macroeconomic variables alongside regulatory reforms, ownership changes and financial crisis affect the bank's asset quality in India.

Using two-step system generalized method of moment (GMM) approach, the study derives key factors that affect the bank's asset quality in India.

The empirical results confirm the time persistence of credit risk among Indian banks during study period. This reflects that bank defaults are expected to increase in the current year, if it had increased past year due to time lag involved in the process of recovery of past dues. Further, higher profitability, better managerial efficiency, more diversified income from nontraditional activities, optimal size of banks, proper credit screening and monitoring and adherence regulatory norms would help in improving the credit quality of Indian banks.

The practical implication drawn from the study is that nonaccumulation of nonperforming loans (NPLs), higher profitability, better managerial efficiency, more diversified income from nontraditional activities, optimal size of banks, proper credit screening and monitoring and adherence regulatory norms would help in improving the credit quality of Indian banks.

This study is probably the first one that identifies in addition to the current year, whether lag of bank industry-macroeconomic affects the level of NPLs of Indian banks. So far, such an analysis has received less attention with respect to Indian banking industry, especially immediate aftermath of the global financial crisis.