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.

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.

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.

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.

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.

P2P网络借贷中存在地域歧视吗？--来自“人人贷”的经验数据

随着P2P网络借贷在我国的快速发展,借贷关系中的歧视现象开始受到国内外学者的关注。笔者运用"人人贷"平台的借贷数据,从借贷双方的角度出发,实证检验P2P网络借贷中是否存在由地区间收入水平不均衡引发的地域歧视现象。结果表明,P2P网络借贷中存在明显的地域歧视,表现为两个方面:首先,贷款人倾向于向高收入地区的借款人提供资金,而不愿贷款给低收入地区的借款人;其次,低收入地区的借款人倾向于设定较高的利率以获得贷款,高收入地区的借款人则会设定较低的利率。进一步研究发现,地域歧视现象存在异质性,具体来说,低学历、低信用、低认证数量、高借款金额借款人受到的地域歧视较为明显,而对高学历、高信用、高认证数量、低借款金额的借款人的地域歧视不甚明显。

美国国家助学贷款拖欠处理策略及其启示

助学贷款对于缓解学生的就学压力,保证优秀学子完成学业至关重要。助学贷款拖欠,特别是严重拖欠会使贷金周转困难,从根本上制约着贷款制度的正常运行和持续健康发展。毕业后流动性大所带来的管理难度大、找工作难度提升所带来的择业不稳定、信用意识不强是致使我国助学贷款拖欠问题越来越严重的主要原因。美国政府加大贷款回收的力度、制定灵活多样的还贷方案、加大惩罚力度、强化咨询指导等做法对我国处置学生助学贷款拖欠问题具有启示和借鉴意义。

论森林资源资产抵押贷款资产评估价值类型选择

首先介绍了国内外相关评估准则对抵押目的的资产评估价值类型选择的相关规定、国内外实务界和学术界对抵押目的的资产评估价值类型选择的主流观点,然后从经济行为和评估目的、抵押资产自身特征、价值类型应用基础角度对森林资源资产抵押价值评估中价值类型选择进行了分析,最后提出计算抵押价值时评估参数选择应遵循的3个原则:考虑资产未来持续经营能力的原则、考虑资产未来变现能力的原则、保守和谨慎的原则。

意大利银行业不良贷款处置的救助基金模式研究

近年来,意大利银行业在不良资产处置上取得了积极进展,系统性风险有所缓释,而目前我国正面临不良贷款上行压力,研究分析意大利不良资产处置机制,对我国控制并降低不良贷款水平具有重要的借鉴意义。意大利银行业对不良贷款的处置,是以强化资产负债表缩表、改革法律程序与会计准则、引入政府担保并发起建立银行救助基金等多措并举的方式进行的。亚特兰特银行救助基金是意大利银行业风险处置的创新之举。该机制以市场化方式将意大利政府担保嵌入不良资产处置流程之中,采用银行股本投资及不良贷款支持证券投资"双支柱"的投资战略,通过资本补充和不良资产处置,"双管齐下"地缓释银行资产负债表压力。鉴此,我国银行业不良贷款处置应发挥政府参与不良资产处置的引导作用,重点是将政府信用嵌入不良资产处置流程之中;多用市场手段而慎用直接救助,重在完善不良资产处置机制的建立,尤其是不良资产处置机制和二级市场建设,探索设立不良资产处置的基金模式。

中国金融业不良资产处置方法创新研究

资产处置方式直接影响金融不良资产价值回收程度。政策性资产处置任务完成之后,四大资产管理公司开始商业化经营,对资产处置方式创新产生了内在的要求;同时,市场环境的改善及相关法律法规的健全,为资产处置方式创新提供了良好的外部条件。本文在总结和借鉴国内资产管理公司传统处置方式及国外不良资产处置方法的基础上,对不良资产创新处置进行了探索。

资产证券化与不良资产处置——中国的实践与反思

不良资产证券化作为我国高效处置不良资产的预设方式,直接套用信贷资产证券化制度进行试点。尽管项目由市场主导顺利发行,但大量试点额度剩余反映出如下问题:一是对证券化处置不良资产制度功能的认识误差;二是不良资产证券化有别于信贷资产证券化,需要更多配套制度和市场环境配合,现实存在操作误差;三是不良资产的形成深受宏观政策调控影响,证券化发挥高效处置不良资产功能需要国家信用大力支持的政策误差。应理性认识证券化处置不良资产功能的有限性,通过推出契合不良资产属性的配套规则和注入必要的国家信用,才能发挥其积极作用,形成市场优选的不良资产处置制度。

“克强指数”2.0版本的构造及实证检验

2015年国务院提请十二届全国人大三次会议审议的政府工作报告中提出使用研究与试验发展经费支出占GDP比重、能耗强度、中长期贷款量三个指标用于描绘经济发展水平。基于此,本文研究首先通过Pearson相关性检验,证明这三个指标与GDP高度相关,的确可以用于评价经济发展状况。然后根据主成分分析的方法,参照花旗银行编制"克强指数"1.0版本的思想,利用这三个指标创造"克强指数"2.0版本。最后利用能让人们切实感受到经济发展水平的"城镇家庭人均可支配收入"作为参照标准,使用1995—2013年的实际经济数据进行评价,证明该指数具有较高的可靠度和准确性。

新疆法人银行不良贷款处置问题分析和对策研究

近年来,受经济下行影响,新疆法人银行机构不良贷款呈现反弹态势,大量的不良贷款沉积且持续增长,机构虽先后采取了一些处置措施,但由于处置手段单一、估值定价手段缺乏、抵债资产变现难、内控机制缺失、相关法律体系不完善等问题,处置措施收效甚微,对其稳健经营产生了较大影响。本文对新疆不良贷款处置过程中存在的问题进行了深入分析,在此基础上从完善不良贷款处置立法、处置方式、政策扶持、评估体系、管理制度五个方面提出政策建议。

商业银行不良贷款处置存在的问题及策略探析

随着我国产业结构的调整以及市场化进程的不断深化,现行经济下行压力日趋凸显,商业银行面临不良贷款总额与不良贷款比例上升的双重压力,如何优化不良贷款处置策略成为商业银行面临的重要问题。当前商业银行只有不断提升不良贷款的管理理念,优化内部控制机制,致力于不良贷款处置的金融创新,才能走出一条处置不良贷款的可持续发展之路。

关于抵押贷款安全性问题的思考

抵押贷款是商业银行普遍推行的一项信贷业务。在充分肯定抵押贷款的积极意义的同时 ,要看到这一新生事物在发展中存在着不容忽视的安全性问题。本文通过对抵押贷款安全性状况的分析 ,提出相应的对策建议及措施。

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.