个人信用评分有力推进信贷风险管理转型

随着我国全面建设小康社会进程的加速,社会财富不断增加,个人客户对银行的个人业务提出了更多需求,进一步拉动了个人金融服务的增长.由于个人业务具有笔数多、单笔金额小,数据丰富的特点,所以要对其采用精细化、智能化、自动化的管理模式.然而长期以来,我国商业银行个人业务的经营管理方式一直比较粗放.中国人民银行最新研发的全国个人信用评分,可以对个人客户在未来一定时期内的违约概率进行评估和预测.它可以有效防范风险,为商业银行实现个人信贷风险管理转型提供先进的风险管理技术支持.     

个人通用信用评分系统：我国征信体系建设的新跨越

经过20余年的发展,我国信用经济已经进入快速发展时期,房贷、车贷、信用卡消费快速增长。如何更好地监管个人信用、更好地防范金融风险已经成为金融机构乃至商家关注的重点。现代市场经济是建立在法制基础上的信用经济,高度发达的社会信用体系在防范金融风险、提高市场资源配置效率等方面都发挥着积极作用,征信体系的建设则是整个社会信用体系建设的重要环节。     

A credit scoring model for Vietnam's retail banking market

As banking markets in developing countries are maturing, banks face competition not only from other domestic banks but also from sophisticated foreign banks. Given the substantial growth of consumer credit and increased regulatory attention to risk management, the development of a well-functioning credit assessment framework is essential. As part of such a framework, we propose a credit scoring model for Vietnamese retail loans. First, we show how to identify those borrower characteristics that should be part of a credit scoring model. Second, we illustrate how such a model can be calibrated to achieve the strategic objectives of the bank. Finally, we assess the use of credit scoring models in the context of transactional versus relationship lending.     

Correction to: Impact of anti-discrimination laws on credit scoring

Journal of Financial Services Marketing -     

The use of credit scoring in the mortgage industry

In times of increased focus on risk management, acquiring or growing comparatively low risk mortgage portfolios has become an attractive value proposition. Banks that pursue an aggressive growth strategy in this sector, do, however, require risk control mechanisms that enable them to make a clear judgment on how great a growth appetite they can afford to have in order to still grow profitably. Moreover, under Basel II, the proper quantification of mortgage portfolio risk tends to help the release of own capital, because the mortgage portfolio is one of those portfolios where the relative benefits of internal ratings-based approaches compared with the standardised approach are greatest. Credit scoring models in general, and credit scorecards in particular, are suitable methods for quantifying the risk of an individual mortgage applicant or mortgage customer. In addition to score card development, this paper reviews alternative scoring model types that could be used for mortgage scoring. It presents reasons why it is beneficial to build such models in-house, before focusing on the steps necessary for building a mortgage scorecard. Finally, it discusses the important topics of creating segments, deploying models and eventually monitoring models.     

我国小企业信用评分系统的开发策略

为了缓解借贷双方信息不对称问题,防范和化解借款人较高的逆向选择和道德风险,促进其盈利水平和核心竞争能力的提高,商业银行将信用评分技术引入小企业货款业务中,使用数据对小企业信用风险进行准确度量,准确快速地识别"好客户"和"坏客户".目前小企业信用评分模型已广泛应用干欧美等发达国家中小企业授信业务上,并在大量授信实践中丰富了信用评分的内容,使该项技术日趋成熟.     

A two-stage credit scoring model based on random forest: Evidence from Chinese small firms

Small firms are major contributors to most economies, often supported by government policies. However, the credit scoring of small firms is complicated and costly, making it a challenging field of research. Using loan data from 3045 small firms in China, we design a two-stage expert system for default prediction that quantifies the variables and thresholds that have a key impact. Firstly, we use SMOTE to deal with the imbalanced data and secondly, we employ random forest to build predictive credit features. Dominance analysis shows that, when making default assessments on Chinese small firms, it is important to consider not only financial factors, but also non-financial and macroeconomic factors. In particular, the net cash profit, the firm's legal disputes and the per capita disposable income of urban residents are key factors in credit scoring. Robustness tests show that our proposed methodology performs better than other machine learning models, and this result is robust with observations from other countries.     

The credit rating process and estimation of transition probabilities: A Bayesian approach

The Basel II Accord requires banks to establish rigorous statistical procedures for the estimation and validation of default and ratings transition probabilities. This raises great technical challenges when sufficient default data are not available, as is the case for low default portfolios. We develop a new model that describes the typical internal credit rating process used by banks. The model captures patterns of obligor heterogeneity and ratings migration dependence through unobserved systematic macroeconomic shocks. We describe a Bayesian hierarchical framework for model calibration from historical rating transition data, and show how the predictive performance of the model can be assessed, even with sparse event data. Finally, we analyze a rating transition data set from Standard and Poor's during 1981–2007. Our results have implications for the current Basel II policy debate on the magnitude of default probabilities assigned to low risk assets.     

中小企业呼唤实施差别性信贷政策

2011年中央经济工作会议和中国人民银行工作会议明确指出．加大对中小企业与“三农”的支持力度,把更多的信贷资金投向实体经济,但落实起来恐怕有难度。鉴于当前县域信贷政策对中小企业发展的不利影响,迫切需要央行出台差别性信贷等政策支持     

个人信用评分系统应用现状与展望

一、个人信用评分系统概述 1.个人信用评分的现实意义 (1)个人信用评分是世界上普遍采用的评估个人信用风险的方法.在欧美发达国家,信用评分专业公司根据银行的业务需要开发不同的信用评分模型.因为每一家银行的业务经营存在差异,从目标客户的选择到客户服务水平都可能有所不同,这使得各个银行开发模型所依赖的数据不同.实践证明,个人信用风险的管理有三个突破,每个突破都会给银行带来较大的利润增长.这三个突破是信用评分、自动化管理系统和决策优化.     

产业结构调整的金融支持方式探讨——通辽市个案

经济发展不仅表现为总量增长,还表现为产业结构的合理化和高级化。产业结构调整的过程就是经济资源不断优化配置的过程,而优化资源配置正是金融市场的基本功能。本文分析了金融在产业结构调整中支持方式的有效性,阐述构建产业结构调整的金融支持方式应考虑的因素,同时提出金融支持产业结构调整的对策建议。     

教育信用卡的构建方法、盈利模式与流程设计

教育贷款的本质是借贷双方达成的一项教育金融合约.一项高效率的教育金融合约应当具备最大限度地促进资金供给与资金需求缺口的弥合、资金供求双方积极参与合约的制定、违约率低等特点.     

企业信用评级指标的选取

影响企业信用状况有哪些主要风险因素？信用评级指标的选取要坚持哪些原则？选取方法有哪些？请看中国信保专家如是说     

Competition in the credit rating Industry: Benefits for investors and issuers

We empirically investigate the benefits of multiple ratings not only at issuance of debt instruments but also during the subsequent monitoring phase. Using a record of monthly credit rating migration data on all U.S. residential mortgage-backed securities rated by Standard & Poor's, Moody's, and Fitch between 1985 and 2012 (154,600 tranches), our results provide empirical evidence that rating agencies put more effort in rating and outlook revisions when tranches have assigned multiple ratings. Furthermore, we see that in the case of multiple ratings, agencies do a better job in discriminating tranches with respect to default risk. On the downside, we observe a shift in collateral towards senior tranches and incentives for issuers to engage in rating shopping activities, but find no evidence that rating agencies exploit such behavior to attract more rating business. Our results contribute to the literature on information production of credit ratings and extend the perspective to the monitoring period after issuance.     

Hedging structured credit products during the credit crisis: A horse race of 10 models

Pricing and hedging structured credit products poses major challenges to financial institutions. This paper puts several valuation approaches through a crucial test: How did these models perform in one of the worst periods of economic history, September 2008, when Lehman Brothers went under? Did they produce reasonable hedging strategies? We study several bottom-up and top-down credit portfolio models and compute the resulting delta hedging strategies using either index contracts or a portfolio of single-name CDS contracts as hedging instruments. We compute the profit-and-loss profiles and assess the performances of these hedging strategies. Among all 10 pricing models that we consider the Student-t copula model performs best. The dynamical generalized-Poisson loss model is the best top-down model, but this model class has in general problems to hedge equity tranches. Our major finding is however that single-name and index CDS contracts are not appropriate instruments to hedge CDO tranches.     

Accounting for self interest in the credit crisis

Taking as its starting point Alan Greenspan’s ‘shocked disbelief’ in the failure of institutional self interest to prevent the credit crisis, this paper sets out to explore two related questions. How was self interest constructed in financial markets? And how might we account for its failure? Conceptually the paper draws upon Callon’s (1998) analysis of ‘agent–networks’, the importance this gives to the agency of non-humans, and his complementary notions of ‘framing’/‘disentanglement’ and ‘overflowing’ as these allow and subvert the calculation of self interest. Empirically, the paper then presents a sketch of these processes in the rise and then fall of the market for collateralised debt obligations (CDOs) that was central to the credit crisis. The final substantive section of the paper reflects on the role and ‘hyperreal’ interaction of accounting and models as ‘mediators’ in these processes.     

How changes in market conditions affect screening activity,credit risk,and the lending behaviour of banks

The global financial crisis dramatically transformed the market conditions in the banking industry. We construct a theoretical model of spatial competition that considers the differential information between lenders and loan applicants to explore how changes in the market structure affect the lending behaviour of banks and their incentives to invest in screening and how this, in turn, affects the level of credit risk in the economy. Our findings reveal that enhanced competition reduces lending cost thus encouraging the entry of new customers in credit markets. Also, that the transportation cost that loan applicants are required to pay to reach the bank of their interest shrinks with respect to the degree of competition. We further lend support to the view that stiffer competition has an increasing impact on the level of credit risk. Notably, we find that competition strengthens the incentives of banks to engage in screening activity and that screening serves as a protection mechanism that can provide banks with a shield against bad loans. Overall, when market conditions are substantially distorted, this has a dilutive impact on the incentives mechanism of banks to screen their applicants. We provide empirical evidence which is consistent with the conceptual underpinnings of our theoretical model and the obtained findings.     

Price discovery of subordinated credit spreads for Japanese mega-banks: Evidence from bond and credit default swap markets

This paper investigates the determinants and dynamics of subordinated credit spreads for Japanese mega-banks using the bond and credit default swap (CDS) spreads. The main findings are as follows. Subordinated bond and CDS spreads are cointegrated in most cases, and the CDS spread plays a more dominant role in price discovery than the bond spread. In addition, there are significant volatility spillovers from the CDS to bond spread. This information leadership for the CDS spread can largely be explained by stronger reactions of the CDS spread to some financial market variables and bank-specific accounting variables than the bond spread.