The Impact of Bank-Specific and Macroeconomic Factors on Non-performing Loans in Sri Lankan Commercial Banks

The main purpose of this study is to ascertain the effect of bank-specific and macroeconomic factors on non-performing loans in systemically and non-systemically important commercial banks in Sri Lanka over 10 year’s period from 2004 to 2013.Also,the study examines the impact of civil war that prevailed in the country for 30 years on the ex-post credit risk of the banking sector.The study employed panel data methodology to investigate the effect of bank-specific and macroeconomic factors on non-performing loans.Panel unit root test has been undertaken in order to test the stationary of the variables.Hausman test and Wald coefficient restriction test were used to select the appropriate model out of pooled,random,and fixed effect.A dummy variable panel regression model adopted to study the war effect,considering 2009 as the structural year.Findings revealed that return on assets as a proxy for bank efficiency has a significant negative influence,while non-interest income as a proxy for income diversity is positively correlated with non-performing loans of systemically important banks.Both real gross domestic products and lending rates were highly significant in both bank types.On contrary with literature,growth in bank branches is negatively correlated.Public banks do not account for higher level of non-performing loans compared to their private counterpart.Finally,it was identified that civil war had an effect on the level of non-performing loans in commercial banks.The research would have benefited if the analysis is carried out among classified types of loans offered by commercial banks.Future researchers should involve in identifying the most significant contributing loan type to the non-performing loans and its determinants.This study is one of the few studies which have investigated the causes of non-performing loans in the commercial banking industry in Sri Lanka.The analysis of civil war and its impact on non-performing loans is the first study of that nature to be conducted in the context.

Non-performing Loans in Turkish Banking Sector and Balance Sheets Effects

In the 21st century, while the scope of banking activities has been expanding every day, collecting deposits and providing credit remain as their main and most important functions. They transfer the collected funds thanks to the market confidence they create back to the market in terms of the credits they give. For the organizations operating in the banking sector, crediting is the highest revenue earning source. However, uncollected loans may disrupt the activities of banks and may reduce their effectiveness. Therefore, the control of bank credits has a particular importance in the bank balance sheets. In this study, the relationship between bank balance sheets and non-performing loans （NPL） will be analyzed using Granger causality test and vector autoregressive （VAR） method. This study aims to discuss the impact of NPL on balance sheets and contribute to making correct credit decisions. It also intends to assist to reduce the NPL ratios of banks and minimize the level of negativity in their financial statements.

Research in the Securitization of the Non-performing Loans of China＇s State-owned Banks

In this paper, through analyzing the necessity of the securitization of the non-performing loans of China＇s state-owned banks, the author proposes some tentative ideas for the securitization of the non-performing loans and works out some problems that need to be solved in this process.

Analyzing China's Non-performing Financial Assets

The non-performing assets of China’s financial institutions totaled RMB l,800 billion. Has this threatened the safety of China’s financial industry? Where do this large amount of nonperforming assets come from?

Non-performing loans(NPLs),liquidity creation,and moral hazard:Case of Chinese banks

This study analyzes the impact of non-performing loans(NPLs)on bank liquidity creation to investigate the existence of moral hazard problem in Chinese banks.It uses data from 197 listed and unlisted Chinese banks,spanning the period 2005 to 2014.Total liquidity creation by Chinese banks is declining,and NPLs ratio has started to increase following a continuous decline between 2005 and 2012.Using one-step system GMM estimation,fixed and random effect model,and pool data analysis,we find that liquidity creation by Chinese banks does not depend on NPLs ratio,i.e.,we did not find the evidence of moral hazard problem in Chinese banks.We repeated the analysis for small and large banks and the results of these sub-samples reinforced our findings for the aggregate sample.

Do Macroeconomic Determinants of Non-Performing Loans Vary with the Income Levels of Countries?

This paper explores the macroeconomic determinants of non-performing loans(NPL) in 19 Asian countries(low to high income economies) using the Generalized Method of Moments estimation approach based on the economic data for the period between 1998 and 2015. The categorization of the economies is based on the average gross national income per capita as set by the World Bank.Specifically, the paper aims to evaluate if the determinants of NPL vary with the income levels of the countries. The results indicate that the NPL is strongly influenced by the inflation rate. The effect is,however, negative in the high-income and the middle-income countries and positive in the low-income countries. The GDP per capita has a dynamic negative relationship with the NPL in the high-income and the low-income countries. The remittance has a significant positive association in the high-income and a significant negative association in the low-income countries. Similarly, the unemployment rate has a positive effect on NPL in the middle-income and the low-income countries. With the rise in the official exchange rate, the NPL level increases in the low-income countries. The overall estimation results suggest that the NPL in Asian banking system depend on some key macroeconomic variables,such as unemployment rate, inflation rate, official exchange rate, remittance received and gross domestic product per capita, and these associations vary with the income level of the countries. Therefore,economic level of a country should be carefully considered while formulating credit policy to minimize credit risks in the banking system.

The Analysis of the Auction Disposal and Pricing Decision of AMC＇s Non-performing Assets with Game Theoryd

Based on the analysis of the characteristics of AMC＇s non-performing asset auction, this paper puts forward a model of AMC＇s non-performing asset disposal with the Game Theory thinking, explored the Nash Equilibrium solution to the pricing model of AMC＇s non-performing asset auction, discussed the impact of the actual value of non-performing assets, auction disposal costs and other relevant elements on auction price, analyzed the pricing and decision-making mechanism of AMC＇s non-performing asset auction with Game Theory, and provided a theoretical guide for AMC to auction the non-performing assets in practice.

On the Pricing Method of the Non-performing Loan Securitization

This paper analyzed in depth the difference between the pricing of non- performing loan （NPL） securitization and that of ordinary asset securitization. It has explained the pricing thought and method of non-performing loan backed securities in connection with the particularity and complexity of non-performing loan and finally proposed some key problems which need to be emphasized during the pricing practice of non-performing loan backed securitization.

A dynamic credit risk assessment model with data mining techniques:evidence from Iranian banks

Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment.According to the Basel 2 guidelines,banks need to develop their own credit risk assessment systems.Some banks have such systems;nevertheless they have lost a large amount of money simply because the models they used failed to accurately predict customers’defaults.Traditionally,banks have used static models with demographic or static factors to model credit risk patterns.However,economic factors are not independent of political fluctuations,and as the political environment changes,the economic environment evolves with it.This has been especially evident in Iran after the 2008-2016 USA sanctions,as many previously reliable customers became unable to repay their debt(i.e.,became bad customers).Nevertheless,a dynamic model that can accommodate fluctuating politicoeconomic factors has never been developed.In this paper,we propose a model that can accommodate factors associated with politico-economic crises.Human judgement is removed from the customer evaluation process.We used a fuzzy inference system to create a rule base using a set of uncertainty predictors.First,we train an adaptive network-based fuzzy inference system(ANFIS)using monthly data from a customer profile dataset.Then,using the newly defined factors and their underlying rules,a second round of assessment begins in a fuzzy inference system.Thus,we present a model that is both more flexible to politico-economic factors and can yield results that are max compatible with real-life situations.Comparison between the prediction made by proposed model and a real non-performing loan indicates little difference between them.Credit risk specialists also approve the results.The major innovation of this research is producing a table of bad customers on a monthly basis and creating a dynamic model based on the table.The latest created model is used for assessing customers henceforth,so the whole process of customer assessment need not be repeated.We assert that this model is a good substitute for the static models currently in use as it can outperform traditional models,especially in the face of economic crisis.

Loan growth and bank solvency:evidence from the Pakistani banking sector

Background:The dramatic loan growth and changes in the Pakistani banking system in mid-2000s have led to significant research attention on borrowers and lenders.This expansion and diversification in financial sector was driven by structural reforms,political stability and significant economic growth.Against this background,this study investigates the loan growth and risk-taking behavior of the banks during the expansionary periods of lending.Method:This study used dynamic two-step system generalized method of moment’s estimation technique,based on data taken from 32 banks in Pakistan over 2006-2014.Result:Loan growth has a significant effect on bank-specific and macroeconomicspecific variables.Loan growth in the previous year raises non-performing loans and decreases the solvency of banks with a time lag of many years.The driving force behind this phenomenon is weak prudential regulation among competitors,the asymmetric information of the borrowers,and,most importantly,that banks underestimate the risk of lending during credit booms.Conclusion:More regulatory measures are required to ensure a strong financial system when the volume of non-performing loan grows significantly.An increase in the capital requirement policy for rapidly growing banks is also needed because the problem of abnormal loan growth cannot be detected at the current time.At the same time,strong supervision is necessary to avoid the adverse consequences of borrower selection.

Financial Supports to the Rejuvenation of the Old Industrial Base of Northeast China

Supporting the reconstruction and reform of the old industrial base in Northeast China is a significant strategy made by the Central Government. With the strategy going into effect, it will be a great opportunity for the economy and finance development in Northeast. Based on the financial facts in Northeast China and the analyses on the key issues concerning finance and the rejuvenation of the old industrial base, countermeasures in five aspects are put forwarded in this paper.

Does abnormal lending behavior increase bank riskiness?Evidence from Turkey

Purpose:This study empirically analyzes whether the rapid growth of loans and risktaking behavior during the expansion of loans affected non-performing loans(NPLs)and the solvency of financial institutions in the Turkish banking system.Design/methodology/approach:Using the GMM Generalized Method of Moments,this study used data on Turkish banks from 2011 to 2017 to test two hypotheses on the effects of loan growth on NPLs and solvency.Findings:This study finds significant results for the effect of loan growth on NPLs and solvency.NPLs rose from the previous year’s loan growth,which tended to reduce solvency.Research limitations/implications:Due to selected research methods,the results may lack generality.Therefore,future studies should test the propositions herein further.Practical implications:The results indicate that careful allocation behavior is required when lending.Additionally,these findings may be helpful to financial managers and decision makers.Originality/value:This study confirms the need to determine how to allocate loans during the loan boom periods.

Office Channeling and Its Impact on the Growth of Indonesian Islamic Banking Industry

The purpose of this paper is to analyze that the office channeling policy that based on Bank Indonesia＇s rule No. 8/3/PBI/2006 had an impact on the growth of Islamic banking industry in Indonesia. This research used ordinary least square regression to analyze the impact of office channeling policy on the growth of Indonesian Islamic banking industry. The variable used in this paper is office channeling which is used as a dummy variable, and margin deposit and non-performing financing （NPF） are also used as control variables. The indicators of the growth of Indonesian Islamic banking industry are asset and third-party funds. The result shows that office channeling does not have an impact on the growth of Islamic banking industry which is measured by asset growth and third-party funds growth. According to this result, Bank Indonesia should have an innovative policy to stimulate the Islamic banking industry growth in Indonesia.

Loan Loss Provisioning Practices

The purpose of this paper is to come up with factors in loan loss provisioning practices on commercial banks that reflect on collectability of defaulted loans. The need for this research is due to failures in the loan loss provisioning practices which resulted in loan loss provisions （LLP） not reflecting on collectability of the defaulted loans. As a consequence, the banks do not capture their loss expectations and do not continuously reassess their loss expectations as the conditions affecting their borrowers may change. Henceforth, in their financial reporting, the banks do not represent relevantly and faithfully their true underlying credit risks conditions. When the banks do not represent relevantly and faithfully their true underlying risk conditions, they contradict the objectives of useful financial reporting. The results showed that among explanatory variables, bad debt recoveries as a factor in loan loss provisioning practices that reflect on collectability of defaulted loans was rejected. Bad debt recoveries was a biased variable and inconsistent estimator. In context of perceived credit risks as the basis to make credit judgments, an estimate of bad debt recoveries had not fulfilled the criteria. On the other hand, non-performing loans （NPL） as a factor in loan loss provisioning practices was not rejected.

Credit Risk （Based on Analysis of Financial Statements） as the Decisive Factor Influencing the Risk of Investors

Banks as the key subjects in the financing of investment have a strong influence on the risk of investors. Hence, the solvency of the bank is of crucial importance for the risk management in the investment process. Given the fact of underdevelopment of financial markets and the lack of trading activities in securities, it is evident that the investments of banks in the developing countries mostly include lending investments. Looking at the key categories of risk that influence the overall risk of the banking business in such conditions, it can be concluded that credit risk presents the dominant and decisive factor. The aim of the paper is to select the bank determinant key factors of credit risk and to determine the extent to which non-performing loans （NPL） of bank credits affect the solvency of banks, and therefore also the risk of investors. This selection of the main determinants will be based on the analysis of financial statements. This is essential, especially taking into account the impact of the global financial crisis and the increasingly frequent falling into insolvency customers. Finally, liquidity of customers is that of the bank, and it is crucial for investors to timely identify possible risks associated with bank loans in order to proactively manage risk investment.

The Empirical Estimation of the Influence of Credit Risk Determinants in Baltic States＇ Banking Sector

There have been investigated empirically the influence of macroeconomic and real estate market variables on the level of non-performing loans in the Baltic States. A secondary goal was to analyze the effect of constant loan portfolio growth on the level of non-performing loans in mentioned countries and to define the type of influence of the variables （i.e., long-term or short-term）. The research indicates that all variables except the growth rate of the real estate market （RRE） have long-term influence on the level of non-performing loans. RRE has short-term influence and variables influence is associated with the development of another variables. The influence of RRE played an important role, but it was not as crucial as it has been previously assumed. If a respective credit risk management is applied, the influence of RRE is to be eliminated. The research results indicate that the most significant reason for the growth of non-performing loans for the Baltic States presented by rapid growth of aggregated loan portfolio and unemployment rate. The increasing influence of rapid loan portfolio growth proves the assumption that banks＇ credit risk management policies underestimated the changes in the macroeconomic variables during the analyzed period. The changes in the real GDP had initial influence on the economic situation deterioration for Baltic States.

Research on China’s Commercial Banks Rating and Ranking Based on DEA

China’s commercial banks are confronted with fierce competition from advanced big commercial banks abroad, which have much better performance in non-performing loans (NPLs) than China’s commercial banks. In this case, efficiency rating and ranking of China’s commercial banks are of great importance. We treat the rate of non-performing loans (NPLs) as an undesirable output from the operating process of commercial bank and utilize cross efficiency of DEA (Data Envelopment Analysis) to evaluate and rank China’s commercial banks between 2006 and 2008 horizontally and vertically. In the end we will propose our conclusion.

China＇s Achilles Heel： The Banking System

China＇s robust economy is bringing unprecedented growth and prosperity to the country. However, there is ample evidence to suggest that weaknesses in the banking system and the slow progress in reforming those weaknesses may cause disruption to continued economic growth. Bad loan portfolios as well as inadequate capital ratios point to the lack of proper governance and credit cultures at many banks. Unless these issues are quickly and properly addressed, the economic engine that drives the country will be at risk.

Sharing China’s Bank Restructuring Bill

This paper addresses the questions related to the cost of China＇s bank restructuring and how it has been financed. We first propose a framework for recognizing losses. Then, we examine the recent major moves by the Chinese Government to repair the country. ＇s bank balance sheets. Finally, we explore the implications of the Chinese Government＇s methods offunding bank restructuring. We find that the Chinese Government has been decisive in confronting the costly task of bank restructuring. So far, Chinese taxpayers have paid most of the bill for bank restructuring.