Global Financial Crisis and Accounting Rules： The Implications of the New Exposure Draft （ED） Financial Instruments： Expected Credit Losses on the Evaluation of Banking Company Loans

During the financial crisis, the delayed recognition of credit losses on loans and other financial instruments was identified as a weakness in existing incurred loss model of impairment stated by International Accounting Standards （IAS） 39, because it is believed that this delay might generate pro-cyclical effects. In response to the recommendations of G20, Financial Crisis Advisory Group （FCAG）, and other international bodies, the International Accounting Standards Board （IASB） has undertaken, since 2009, as a part of the project to replace IAS 39, a project （partially shared with Financial Accounting Standards Board （FASB）） aimed at introducing an expected loss model of impairment. Within the scope of this subset project, the IASB has previously issued two exposure documents proposing models to account for expected credit losses： an exposure draft （ED） Financial Instrument： Amortized Cost and Impairment, published in November 2009, and a supplementary document （SD） Financial Instrument： Impairment, published jointly with the FASB in January 2011. However, neither of the two proposals received strong support from interested parties. Recently, the IASB, after the FASB＇s decision to withdraw from the joint project and to develop a separate expected credit loss model based on a single measurement approach consisting in the sole recognition of lifetime expected credit losses, published a third proposal--Ahe so-called expected credit losses model （ED/2013/3 Financial Instruments： Expected Credit Losses）.

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.

A Knowledge-based System for the Analysis of the Ability of Paying back Loans

This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system developed focuses on what is bank loans risks management, how to prevent risk by the analysis of the ability of paying back loans. The paper makes the structural analysis involved in the system's decision situation, the structured situation diagram or model, dependency diagram and the document needed by the KBS prototype system thus are developed. Through testing the samples from loan business, the quality for the analysis of the ability of paying back loans can be effectively evaluated by the KBS prototype system.

Intelligent Decision Support System for Bank Loans Risk Classification

Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

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.

Designing of Commercial Bank Loans Risk Early Warning System Based on BP Neural Networks

According to the index early warning method, a commercial bank loans risk early warning system based on BP neural networks is proposed. The warning signal is mainly involved with the financial situation signal of loaning corporation. Except the structure description of the system structure the demonstration of attemptive designing is also elaborated.

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.

Loans to Foreign-Funded Enterprises

With the implementation of the opening policy, the Bank of China(BOC) started lending to foreignfunded enterprises early in the 1980s. At the end of 1993, 50 percent of foreignfunded enterprise had opened accounts with the BOC. BOC has made US dollar loans worth $16.8 billion, and RMB ioans of ￥ 135.55 billion to

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.

Guidelines Procurement under IBRD Loans and IDA Credits

I. INTRODUCTIONPurpose1.1 The purpose of these Guidelines is to informthose carrying out a project that is financed in wholeor in part by a loan from the International Bank forReconstruction and Development (IBRD) or a creditfrom the International Development Association(IDA), of the arrangements to be made for procur-ing the goods and works (including relatedservices) required for the project. The Loan Agree-ment governs the legal relationships between the Bor-rower and the Bank, and the Guidelines are made ap-plicable to procurement of goods and works for theproject, as provided in the agreement. The rightsand obligations of the Borrower and the providers ofgoods and works for the project are governed by thebidding documents, and by the contracts signed bythe Borrower with the providers of goods and works,and not by these Guidelines or the Loan Agreements.No party other than the parties to the Loan Agree-ment shall derive any rights therefrom or have anyclaim to loan proceeds.

双重资金约束下考虑碳配额交易的供应链融资决策

构建由生产和减排双重资金约束的制造商和零售商组成的低碳供应链系统,针对银行借贷和提前支付两种融资模式,探究碳配额交易下制造商的融资决策问题,并分析了碳减排成本系数和碳交易价格对融资决策和供应链成员利润的影响.研究发现:当提前支付利率等于银行借贷利率时,无论是否考虑碳配额交易,提前支付融资总会给制造商带来较大利润,因此,提前支付是制造商的最优融资选择.当融资利率不等时,制造商融资方式会受到碳配额交易和碳减排成本系数的影响.碳减排成本系数增大时,融资规模、供应链成员利润均降低,而碳交易价格提高时,融资规模、制造商利润均增加.另外,碳配额交易会增加制造商利润,但会损害零售商利润.

银行科技贷款对创新质量的影响机制及效应研究

银行科技贷款作为科技金融的重要组成部分之一,对企业创新质量的提高具有至关重要的作用。本文基于高科技产业面板数据,构建了银行科技贷款对创新质量的影响机制,并采用面板回归模型、面板门槛模型对其中的线性关系、非线性关系进行了实证研究。研究发现,银行科技贷款总体上对创新质量产生正向影响。银行科技贷款水平较低时,其对创新质量的促进作用较大;企业创新质量水平较低时,银行科技贷款对创新质量的促进作用不足。随着企业研发经费投入水平由低到高,银行科技贷款对创新质量的贡献呈“U”型。因此,为实现企业创新质量的提高,应优化研发经费来源配置。

数据要素跨部门共享能缓解中小企业融资约束吗?——基于“银税互动”的准自然实验

打破“政府数据孤岛”是新时代建设全国统一大市场的必然要求,数据要素如何服务微观企业成长构成经济社会高质量发展的关键环节。依托“银税互动”平台,数据要素可通过跨部门共享释放金融动能继而影响中小企业的融资约束。借助我国各地市陆续实施“银税互动”的准自然实验,以2009—2022年中小企业板和创业板上市公司为样本,研究政府数据跨部门共享对中小企业融资约束的影响及作用机理,并进行不同产权性质和金融资源发达程度的异质性分析。结果表明:相较于所在地未实施“银税互动”的中小企业,所在地实施“银税互动”的中小企业的融资约束问题得到显著缓解,且该结论在经过一系列稳健性检验和内生性分析后依然成立。机制检验结果表明,“银税互动”通过降低中小企业与银行之间的信息不对称程度、改善中小企业与银行之间的委托代理问题和提振其他利益相关者对中小企业未来发展信心的机制实现缓解效果,且该缓解效果在非国有中小企业和所在地金融资源匮乏的中小企业中更为明显。研究成果表明,以“银税互动”为典型的数据要素跨部门共享实践有助于中小企业高质量发展,不仅对“银税互动”和企业融资约束的学术研究作出了重要拓展,同时为党和国家不断健全数据要素市场化配置体制机制提供了政策参考。

商业银行数字化能否改善企业投融资期限错配?

本文基于中国246家商业银行及A股上市公司2013—2022年数据,探究了商业银行数字化能否改善贷款企业投融资期限错配。研究发现,商业银行数字化通过调节错配企业短期贷款金额、提高公司治理水平,进而缓解企业投融资期限错配。该效应在资本市场融资能力较强企业、高融资约束企业、中小规模企业及制造业企业中更为明显。文章结论在经过内生性处理和稳健性检验后依旧成立。进一步分析表明,商业银行战略、管理及业务的数字化均可对企业投融资期限错配产生影响,但前两个维度的影响更为明显。探究商业银行数字化的微观错配纠偏功能,不仅有利于降低企业层面投融资期限错配引发的风险,也为进一步优化银企互动和挖掘商业银行数字化意义提供了新的证据。

考虑技术异质性的中国商业银行效率评估及动态演变

考虑银行经营的阶段性特点,将银行经营过程划分为资金筹集和资金运用两阶段,针对我国商业银行存在的技术异质性及不良贷款和结转资产的时滞效应,构建了包含四个系统的两阶段动态网络DEA模型,并测度了2012—2019年我国38家商业银行的整体效率及子阶段效率,探究异质银行在连续时期内运营效率的变化情况及其无效来源。结果显示:因技术异质性导致的银行效率的差异显著;分类别来看,城市商业银行的整体效率最高,国有银行次之,而股份制银行整体效率最低;分阶段来看,除农商行外,其他三种类型的银行资金筹集效率始终高于资金运用效率;依据两阶段内生权重可以得到提高资金运用阶段的效率是提高银行业整体效率的关键。研究结论为提升我国商业银行效率的政策制定提供一定的理论依据。

银行金融科技对贷款损失准备计提顺周期的影响:推波助澜还是解危济困

商业银行贷款损失准备计提的顺周期行为会加剧金融市场的震荡,因此,如何缓释其顺周期性始终是金融监管的一大焦点。本文基于我国233家商业银行2010—2021年间数据,探究了银行金融科技对其贷款损失准备计提顺周期的影响。实证研究发现,商业银行的金融科技应用能够显著缓解贷款损失准备计提的顺周期性。这一结论在一系列内生性以及稳健性检验后,依然保持稳健。机制分析发现,金融科技通过显著增强银行贷款损失准备计提的前瞻性,缓解了贷款损失准备计提的顺周期行为,凸显了金融科技对商业银行的赋能效果。从宏微观层面进行的异质性分析发现,在规模较小、外部监管水平较低的商业银行中,以及在宏观经济信心相对不足时期,顺周期问题更为严重;而金融科技对商业银行顺周期行为的缓解作用则在规模较小、外部监管水平较低和报表粉饰程度较弱的银行中更为显著。分解检验发现,金融科技中,“科技管理”对缓释银行贷款损失准备计提顺周期性的作用最大。

宏观审慎政策能否抑制商业银行风险承担

选取2010—2020年中国225家商业银行年度数据,构建面板回归模型实证检验了宏观审慎政策对银行风险承担的影响及其作用机制。研究表明:(1)宏观审慎政策的实施有助于抑制银行风险承担。相对于国有银行与城农商行,宏观审慎政策对股份制银行风险承担的抑制效应更大。(2)同业负债、贷款集中度及杠杆率在宏观审慎政策与银行风险承担的关系中承担着多重中介作用,宏观审慎政策主要通过降低银行同业负债、贷款集中度及杠杆率渠道来降低银行风险承担,“宏观审慎政策—同业负债/贷款集中度/杠杆率—银行风险承担”的传导渠道均有效。(3)跨境资本流入对宏观审慎政策与银行风险承担关系具有负向调节作用,跨境资本流入规模增大会减弱宏观审慎政策对银行风险承担的抑制作用。(4)银行家信心对宏观审慎政策与银行风险承担关系具有负向调节作用,银行家信心提升会减弱宏观审慎政策对银行风险承担的抑制作用。该成果将为提升宏观审慎监管效率及防控中国银行业风险提供重要的理论指导与决策参考。

基于ITSA模型的浙江省世界银行贷款千岛湖项目成效分析

针对国家级战略规划《千岛湖及新安江上游流域水资源与生态环境保护综合规划》的出台,浙江省于2018年11月启动了世界银行贷款浙江千岛湖及新安江流域水资源与生态环境保护项目。为评估该项目对千岛湖水资源的阶段性保护成效,本文采用中断时间序列分析ITSA模型进行定量分析,研究千岛湖项目与千岛湖水基金协同执行2年之后的治理成效。研究结论显示,千岛湖部分水质指标的改善已进入瓶颈期,要获得水质的进一步提升,仍需继续加大科技投入,除提升上游来水水质外,还要从提升水环境治理的科技水平、治理广度与深度等方面着手,才能获得更大突破。

动态视角下房地产贷款对银行业系统性风险溢出研究

基于Credit Metrics模型动态度量房地产贷款信用风险,运用双重ΔCoVaR模型分析框架量化其对单家银行风险的影响,以及对银行业系统性风险的溢出,将总体溢出分解为直接溢出和间接溢出,考量房地产贷款信用风险对银行业系统性风险的传导途径。结果显示:一方面,房地产贷款信用风险近年来整体呈上升趋势,且对银行业风险溢出显著,尤其是大规模债务违约和新冠疫情的爆发加剧了溢出效应。另一方面,房地产贷款信用风险的间接溢出大于直接溢出,且高(低)系统重要性银行产生了更大的间接(直接)溢出,表明高系统重要性银行由于与其他银行的业务联系密切,其贷款信用风险更易引发银行业内的连锁反应从而间接刺激风险爆发;低系统重要性银行因为依赖少数大型客户贷款,面临信用丢失时缺乏强劲的风险缓冲能力,更可能直接对银行业的稳定造成显著破坏。

预期信用损失模型实施与银行信贷过度增长

如何通过制定有效的贷款损失准备计提规则来影响银行信贷行为,进而促进经济高质量发展,是政策当局亟需解决的难题。鉴于此,本文利用贷款损失准备会计准则改革——2018年预期信用损失模型实施——作为准自然实验,运用渐进双重差分法,实证检验了预期信用损失模型是否及如何影响我国商业银行信贷过度增长。研究发现,预期信用损失模型可显著降低银行信贷过度增长,且这一结论在经过稳健性检验后仍然成立。从机制分析看,预期信用损失模型主要通过充分性效应和及时性效应两条路径作用于银行信贷过度增长。进一步的分析则表明,预期信用损失模型对于以权重法进行资本计量的银行和资本充足率较低的银行而言,其抑制信贷过度增长的作用更为突出。本文丰富了预期信用损失模型经济后果的有关研究,为会计准则制定与金融监管政策调整提供了有益的政策启示。