信用评级模型构建的统计学解读

不断累积的征信信息为判断借款人信用表现提供了数据支持,计算机技术的飞速发展为批量处理贷款申请提供了技术保障。金融机构利用统计方法建立信用评级模型,能够尽可能准确地挖掘违约借款人的信用特征,对借款人信用表现进行精准预判。从信用评级模型的概念入手,揭示信用评级模型的统计学本质,通过对比信用评级建模的输入端和输出端,即征信数据和信用评分卡,从统计学的视角解读建模过程中需要解决的数据离散化、特征选择、数据缺失、拒绝推断和数据不平衡五类技术难题。     

The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher

The purpose of this study is to demonstrate potential problems associated with the use of bankruptcy prediction models in current research. The tests in this study demonstrate the problems that may arise when bankruptcy prediction models are inappropriately applied. This analysis evaluated the Zmijewski (1984) and Ohlson (1980) models using time periods, industries, and financial distress situations other than those used to originally develop the models. The findings indicated that both models were sensitive to time periods. That is, the accuracy of the models declined when applied to time periods different from those used to develop the models. The findings also suggest that the accuracy of each model continues to decline moving from the 1988–1991 to the 1992–1999 sample period. Additionally, Ohlson's (Zmijewski's) model was (was not) sensitive to industry classifications. The findings of this study also suggest that the Ohlson and Zmijewski models are not sensitive to financial distress situations other than those used to develop the models. Thus, the models appear to be more generally useful for predicting financial distress, not just bankruptcy.In sum, the results of this study suggest that researchers should use bankruptcy prediction models cautiously. Applying the models to time periods and industries other than those used to develop the models may result in a significant decline in the models' accuracies. Additionally, some bankruptcy prediction models may be more appropriate for evaluating various forms of financial distress as opposed to just bankruptcy. To avoid erroneous applications of bankruptcy prediction models in the future, it is necessary for researchers not only to understand the uses of prediction models, but also to understand the limitations of the models.     

A PSYCHOLOGICAL APPROACH TO MICROFINANCE CREDIT SCORING VIA A CLASSIFICATION AND REGRESSION TREE

Microfinance institutions' (MFIs') peculiar lending methodology is characterized by an unchallenged decision‐making predominance from the part of loan officers. Indeed, the latter are in charge of providing a great deal of diagnostic information regarding the entrepreneur's psychological traits likely to help them run a business. This paper constitutes an initial attempt towards exploring the role of borrowers' psychological traits in predicting future default occurrences. It builds on a nonparametric credit scoring model, based on a decision tree, including borrowers' quantitative behavioural traits as input for the final scoring model. On applying data collected from a Tunisian microfinance bank, the major depicted result lies in the fact that borrowers' psychological traits constitute a major information source in predicting their creditworthiness. Actually, the variables deployed have helped reduce the proportion of bad loans classified as good loans by 3.125%, which leads to a decrease in MFIs' losses by 4.8%. In addition, the results indicate that the scoring model based on a classification and regression tree (CART) outperforms the classic techniques. Actually, implementing this CART model might well help MFIs reduce misclassification costs by 6.8% and 13.5% in comparison with the discriminant analysis and logistic regression models respectively. Our conceived model, we consider, would be of great practical implication for microfinance and may provide a means for securing competitive advantage over other MFIs that fail to implement such a methodology. Copyright © 2014 John Wiley & Sons, Ltd.     

大数据应用于信用评分模型的实践与启示

传统征信业务必因大数据而发生改变,大数据将为现有征信体系增加海量数据来源并推动普惠金融的发展。但是,由于存在个人隐私权保护、信贷风险控制及管理等限制因素,大数据技术最终如何实现与征信业务的完美结合以及究竟对传统征信业带来何种程度的影响,仍需要时间的检验。     

Strategic Bankruptcies and Price Reactions to Bankruptcy Filings

This study investigates whether the stock market differentiates between firms that file bankruptcy petitions for strategic reasons and firms that file bankruptcy petitions for financial reasons. We perform both univariate and regression tests on a sample of 245 firms that filed Chapter 11 bankruptcy petitions between 1981 and 1996. After controlling for bankruptcy outcome, probability of bankruptcy, firm financial condition, and firm size, we find that, in the period around bankruptcy filing, firms that file bankruptcy petitions for financial reasons have significantly larger stock price declines than firms that file bankruptcy petitions for strategic reasons.     

Have Financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy

Using a hazard model, we examine secular changes in the ability of financial statement data to predict bankruptcy from 1962 to 2002. We identify three trends in financial reporting that could influence predictive ability with respect to bankruptcy: FASB standards, the perceived increase in discretionary financial reporting behavior, and the increase in unrecognized assets and obligations. A parsimonious three-variable model provides significant explanatory power throughout the time period, with only a slight deterioration in predictive power from the first to the second time period. The striking feature of the results is the robustness of the predictive models over a forty-year period.JEL Classification: M41, G14, G33, C41     

金融信用发展演变研究

由信用风险引发的美国金融危机引起了我们对金融信用的反思。随着金融信用发展,金融信用的内涵和外延在不断变化。本文研究了金融信用的演进历程,根据不同发展时期的特征,将金融信用的发展划分为五个阶段:道德化、法制化、商业化、证券化及风险的市场化阶段。每一发展阶段,金融信用的作用和蕴含的风险是不同的,而目前的金融信用蕴含的信用风险,成为金融危机的重要诱因。     

国内个人信用评分机制的规范研究

信用评分日益成为金融机构贷款决策的重要依据。目前,公民个人的信用关联信息主要来自于以下途径:中国人民银行个人征信信息、信用服务机构的个人信用评分、地方的个人信用评分和电信运营商提供的个人信用评分。从规范我国个人信用评分机制考虑,应建立全国统一的个人信用评分机制,由中国人民银行征信中心统一管理个人信用分数,同时,对不确定性因素进行考察,并区别个人信用与个人声誉评价标准。为建立我国统一的个人信用评分机制,应完善全国征信系统中的个人信用记录,设定个人信用计分卡和计分权重,设置个人信用的风险分数,确立科学的个人信用评分模型,确保个人信用分数计算方法的科学性与合理性。通过规范个人信用评分机制,扩大信用分数在各个领域的应用,进一步促进我国信用体系的建立与完善。     

论重整企业信用修复的特征、机制与方式

重整企业信用修复日益受到重视,并且司法实践已经开启个案探索,亟待推进重整企业信用修复的制度建设.重整企业信用修复制度应当以企业拯救为目的,以准予修复为原则、不予修复为例外,以主动、高效为根本要求.重整企业信用修复应当构建以\"府院协调\"为基础,信用服务机构、银行等多元主体参与的机制,并且对信用修复方式进行革新,为重整企业...     

Credit Scoring and Mortgage Securitization: Implications for Mortgage Rates and Credit Availability

This article develops a model of the interactions between borrowers, originators, and a securitizer in primary and secondary mortgage markets. In the secondary market, the securitizer adds liquidity and plays a strategic game with mortgage originators. The securitizer sets the price at which it will purchase mortgages and the credit-score standard that qualifies a mortgage for purchase. We investigate two potential links between securitization and mortgage rates. First, we analyze whether a portion of the liquidity premium gets passed on to borrowers in the form of a lower mortgage rate. Somewhat surprisingly, we find very plausible conditions under which securitization fails to lower the mortgage rate. Second, and consistent with recent empirical results, we derive an inverse correlation between the volume of securitization and mortgage rates. However, the causation is reversed from the standard rendering. In our model, a decline in the mortgage rate causes increased securitization rather than the other way around.     

区块链:一种新的征信视角与技术架构

区块链是未来信息技术的一个重要方向,区块链技术和征信系统的结合是全球的研发热点.阐述征信的概念、信息技术在征信业发展过程中的作用以及征信市场的痛点,提出新技术背景下面临的挑战.为使区块链技术与征信更有效地结合,回顾区块链的产生、发展背景,对“初级版本”区块链和普通意义上的区块链进行详细解析,逐步发现区块链对构建一种新的...