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.

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.

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.

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.

银行不良贷款违约损失率结构特征研究

本文对中国银行业面临的信用风险违约损失率(LGD)展开研究,以温州某商业银行不良贷款数据为样本,通过描述性统计,对LGD的结构特征:信用风险暴露规模特征、期限特征、地域特征以及担保特征等进行了详细分析。结果表明LGD与风险暴露规模呈负相关,LGD与贷款期限呈正相关,不同地域、不同担保方式的违约贷款其LGD差异性显著。以上这些结论可为商业银行信用风险管理、信贷投放导向以及信用风险监管提供现实帮助。

政府直接干预、金融抑制与银行不良贷款——基于省际动态GMM估计方法

利用2005—2015年我国各地区政府干预、金融抑制与银行业不良贷款率数据,运用动态GMM回归方法,对三者之间的关系进行了探讨,结果表明:金融抑制导致银行不良贷款率攀升,政府直接干预会促进银行不良贷款率的下降,而政府直接干预可以起到削弱金融抑制对银行不良贷款率负面影响的作用。此外,经济发展水平、非国有化程度及企业的资产负债率提高都能抑制我国银行业不良贷款率的上升。根据研究结论,提出如下政策建议:(1)在政府直接干预经济方面,政府要帮助创造良好宏观经济环境,加强服务意识,协调好直接经济干预和金融干预的平衡;(2)在降低金融抑制程度方面,应积极进行金融体制改革,充分发挥金融市场本身的资本配置作用;(3)从多方入手。

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。

关于银行贷款损失准备制度的调查报告——以我国五家上市银行为例的分析

本报告总结了我国贷款损失准备制度的历史沿革,分析了五家上市银行贷款损失准备计提情况,并对辖区相关机构进行了调研,发现:(1)五家上市银行贷款损失准备有明确的计提范围,但行际之间计提范围有差异;(2)贷款损失准备计提比例符合监管当局的原则性要求,但各行提取比例有差异;(3)计提损失准备时各行对抵押物金额扣除不同;(4)不良贷款拨备覆盖率呈逐年上升(除深发展)趋势,抗风险能力趋于增强;(5)部分机构逻辑上存在利用贷款损失准备操纵利润的可能;(6)仅仅从贷款损失准备比例看,大多未体现周期特征,在经济周期高点可能相对少计提;(7)调查中发现五级分类目前还存在问题,贷款损失准备计提的基础不牢靠。在此基础上,结合调研掌握的具体情况,本报告认为:(1)银行监管、财政、税务等部门应加强协调,进一步规范贷款损失准备计提制度;(2)进一步完善贷款五级分类制度,夯实损失准备计提的基础;(3)结合我国目前信用环境,需要研究五级分类、贷款损失准备计提这两个环节抵押品、有效担保的处理原则,避免重复考虑、高估价值,使贷款损失准备计提更加审慎;(4)五级分类、特种准备、一般准备、专项准备以及分红政策等方面要充分考虑经济周期或者行业周期波动的影响,以使贷款损失准备的计提更为前瞻、审慎,确保提足损失准备,及时弥补损失,增强资本基础,提高抗风险能力;(5)区别对待,分类监管;(6)重视贷款损失准备、资本充足率监管在货币政策传导方面的作用及其产生的宏观效应。

对当前我国不良信贷资产证券化的理性思考

该文就当前我国国有银行不良信贷资产证券化的问题做了较系统的分析。作者的基本观点是 :无论从中国国有银行不良资产的质量和形成背景看 ,还是从中国现实的金融市场、法制环境等分析 ,选择不良信贷资产作为中国资产证券化的切入点是不明智、不现实的。中国的资产证券化首先必须解决好若干认识定位问题 ,认真选择启动资产。同时 ,积极推进经济金融体制改革 ,加快现代企业制度建设 ,培育资本市场。否则 ,将欲速而不达。

产权制度下商业银行不良资产博弈

银行的改革进行了二十几年,虽然取得了阶段性的成果,但却没有从本质上解决银行的巨额不良资产问题。本文通过建立两阶段的动态博弈模型,分析了政府与国有银行之间的利益博弈行为,阐明国有银行不良资产之所以仍然不断涌现,是由于政府对银行产权份额的过多控制而导致的。在此基础上,提出了推进彻底的银行产权制度改革、完善银行的法人治理结构的建议,以便从根本上减少银行的不良资产。

商业银行不良资产价值管理:机理和策略

商业银行不良资产问题是关系到维护金融秩序,确保国民经济运行安全的重大课题,而银行的风险经营特点则更决定了不良资产的管理是银行面临的永久话题。本文提出不良资产价值管理基本内涵,从价值均衡角度分析价值管理机理,并从目标、技术、管理模式和制度等方面阐述了商业银行不良资产管理所应采取的策略。

个人住房贷款的风险管理

我国个人住房贷款的风险可能成为未来银行不良贷款增加的主要来源之一。个人住房贷款所面临的风险包括:银行的流动性风险、个人的信贷风险、贷款中的操作风险等。为了应对相关的风险,商业银行应当从多方面完善个人住房贷款的风险管理。商业银行应当改善个人信用风险的识别与评估环境,并且积极鼓励商业银行采取市场化的手段转移风险,从各方面推进房地产抵押贷款证券化,其作用可以有效地分散和转移风险。商业银行还应以预警机制预防风险,防患于未然。同时,金融管理机构在政策制定方面也应适应并引导个人住房贷款的健康发展。

资产管理公司不良债权资产价值分析

以不良债权资产价值的主要影响因素为基础,简要介绍三种基本的价值测评方法,并结合不良债权处置的有关实际情况,着重对清偿比例法进行详细讨论和分析。

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.

关于拨备覆盖率的思考

商业银行不良资产拨备覆盖率常常被作为衡量银行抵御信用风险能力的指标。本文认为,拨备覆盖率并非越高越好,由于其内在局限性,它反映银行抵御信用风险能力的准确程度受不良贷款结构和漏划不良贷款等因素的影响,并可能产生扭曲对银行抵御风险能力的评价、掩盖银行真实的财务状况、影响银行利润的合理使用以及降低银行监管的严肃性和权威性等负面影响。因此,为完善拨备考核指标,本文提出应以预期损失为基础考核银行冲销不良贷款损失的实际能力,设计新的贷款减值拨备率指标;并认为在确定减值准备指标时,考虑系统性风险既无实际意义,也缺乏可操作性。