个人信用评分模型及其在信用额度评价中的应用

个人信用评分模型及其在信用额度评价中的应用硕士学位论文 THESIS OF MASTER DEGREE论文题目: 个人信用评分模型及其在信用额度评价 中的应用(英文): Personal Credit Scoring Models and their Application to Credit Limit Evaluation 作 者:左 玉 婷 指导教师: 张波 教授 2006 年 5 月 24 日 论文题目: (中文)个人信用评分模型及其在信用额度评价 中的应用(外文)Personal Credit Scoring Models and theirApplication to Credit Limit Evaluation所在院、系、所 :统计学院专专业、名、称 : 统计学 指专导专教专师姓专名、职专称 : 张波 教授论文主题词: 个人信用; 信用评分; Logistic 回归;信用额度评价 学专习专期专限 : 2004 年 9 月至 2006 年 7 月 论文提交时间:2006 年 5 月 24 日 独 创 性 声 明 本人郑重声明:所呈交的论文是我个人在导师指导下进 行的研究工作及取得的研究成果。尽我所知,除了文中特别 加以标注和致谢的地方外,论文中不包含其他人已经发表或 撰写的研究成果,也不包含为获得中国人民大学或其他教育 机构的学位或证书所使用过的材料。与我一同工作的同志对 本研究所做的任何贡献均已在论文中作了明确的说明并表 示了谢意。 签名: 左玉婷 日期: 2006 年 5 月 24 日 关于论文使用授权的说明 本人完全了解中国人民大学有关保留、使用学位论文的 规定,即:学校有权保留送交论文的复印件,允许论文被查 阅和借阅;学校可以公布论文的全部或部分内容,可以采用 影印、缩印或其他复制手段保存论文。签名: 左玉婷 导师签名: 张波 日期:2006 年 5 月 24 日个人信用评分模型及其在信用额度评价中的应用 摘 要 在现代市场经济中,信用作为一种隐含性契约提高了交易效率,降低了交 易成本。 “个人信用”即指社会根据某一公民现有的和历史的记录,由于其可以 预见的偿付能力和偿付意愿,而相应给予的信赖和评价。这种信赖和评价使该 公民在经济生活中能够便利地获得相应的资金、物资等经济支持。 个人信用评分的目的,就是通过综合考察影响个人信用状况的的各种因素 以及个人过去的信用表现,来预测其未来的信用行为。从本质上来看,个人信 用评分模型相当于模式识别中的一类分类问题,即从已知的数据中总结出分类 规则,建立数学模型,用于预测违约风险(或违约概率)。 将计量分析方法运用到个人信用评分技术中始于上世纪 30年代的美国,然 而国外的主要信用评分机构对其评分模型和开发方法都极为保密。在中国,则 是上世纪末随着信用卡在国内发行,才刚刚开始借鉴和应用国外有关个人信用 评分的做法。根据国内外相关领域的研究文献,个人信用评分技术研究中主要 应用的计量分析方法包括三大类:参数统计方法、非参数统计方法和运筹学方 法。参数统计方法主要是判别分析、线性回归、Logistic 回归、Probit 回归等; 非参数统计方法主要是神经网络、决策树(递归划分)、专家系统、昀近邻法、 基因算法等;运筹学方法主要是数学规划。本文对这些模型的优缺点及其适用 性进行了综述比较,在模型比较的基础上,论文在实证研究中所选择使用的模 型为 Logistic回归模型。 在信用风险控制过程中,个人信用评分模型不仅可应用于对被评估者进行 违约风险审核,还可进一步应用于对被评估者的信用额度进行评价。本文依据 两种分析思路,提出了两种评价个人信用额度的方法: “直接预测评价法”和“贝 叶斯预测评价法”。论文同时指出了这两种方法各自的模型特点和适用条件。 通过采用美国某征信局的个人信息数据样本,本文进行了数据实例建模分 析,建立了一个基于 Logistic 回归方法的个人信用评分模型,并对模型预测有 效性进行了检验。验证结果表明,该模型体现了优良的预测违约概率的性能, 能够显著提高信用评审的效率和准确性。 随着我国金融市场的逐步完善,信用经济时代已经到来,信贷决策十分需 要个人信用评分系统提供更为精确的计量分析依据。与此同时,个人信用还是 1个人信用评分模型及其在信用额度评价中的应用 一个人守信程度、社会信誉的反映,对于我国建立起“德治”社会也具有着举 足轻重的作用。本文对该领域研究工作的主要创新在于:在对个人信用评分模 型所主要应用的计量分析方法和模型的讨论基础上,进一步探索了对个人信用 额度评价的计量分析方法,从而使得个人信用额度的确定也具有了量化分析依 据。 本文研究中存在的重要不足是:对所提出的两种个人信用额度评价的计量 分析方法尚未进行实证研究,因此对两种预测评价方法的实际应用效果还无法 比较。关键词:个人信用;信用评分;Logistic回归;信用额度评价 2个人信用评分模型及其在信用额度评价中的应用 Abstract In modern market economy, credit as a cryptic contract can reduce the trade costThe concept of personal credit means the trust and evaluation that the society judges one person basing on his current and historical records, his solvency and his refund will. By this trust and evaluation, the person can obtain corresponding financial or material supplyThe aim of personal credit scoring is to forecast ones future credit behavior by reviewing synthetically the ones historical credit behave and all kinds of the factors that influence personal credit status. Essentially, personal credit scoring models are of some kind of classification problems in mode identifying. They summarize classifying rules from known data and establish mathematical models to forecast breach risk or breach probabilityApplication of quantitative analysis methods to personal credit scoring began in America in 30s of last century. However, most of the overseas credit scoring corporations have been keeping their models and methods as precious secrets. In China, it is just since the end of last century along with credit card being issued that the domestic organizations began to refer to the overseas personal credit scoring techniques. According to the domestic and overseas literatures on relevant research, quantitative analysis methods applied to personal credit scoring techniques include three kinds: parametric statistical methods, nonparametric statistical methods and operational methods. Parametric statistical methods mainly include discriminant analysis, linear regression, Logistic regression and Probit regression. Nonparametric statistical methods mainly include neural networks, decision tree recursive portioning, expert system, nearest neighbour methods and gene arithmeticOperational methods mainly include mathematical programming methods. This paper compared the advantages, disadvantages and applicability of different personal credit scoring models. Basing on the comparison, this paper chose Logistic regression models in doing the practical data modelingWhen applied to credit risk control process, personal credit scoring models can3个人信用评分模型及其在信用额度评价中的应用 be applied to not only the applicant breach risk estimation, but also the applicant credit limit evaluation. From two analyzing ideas, this paper presented two methods: Direct forecast evaluation method and Bayes forecast evaluation method. At the same time, this paper pointed out the respective properties and conditional applicability of each method Adopting the personal information sample data from an American credit agency, this paper established a personal credit scoring model based on Logistic regression and verified the validity of the model forecast. The verifying result indicates that the model takes on good performance of forecasting breach probability, and can improve markedly the efficiency and veracity of credit scoring With the development of financial market in China, the credit economic times is coming. Credit decision-making needs personal credit scoring systems to provide more accurate quantitative analysis basis. Moreover, as the reflection of how one keeps his words and his social credit standing, personal credit is also vital for building a moral society in our country. In the work of this paper, the main innovative point is that basing on the discuss about different personal credit scoring models, I further probed into the quantitative analyzing methods of personal credit limit evaluation and presented two methods?Direct forecast evaluation method and Bayes forecast evaluation method, thus the methods can offer quantitative analyzing bases to the decision about personal credit limitThe concernful shortage of this paper is that I havent take on practical demonstration study for the two personal credit limit evaluation methods, so cannot compare the practical applying effect of the two methods yet Key words: Personal Credit; Credit Scoring; Logistic Regression; Credit Limit Evaluation 4个人信用评分模型及其在信用额度评价中的应用 目 录第 1章 引言. H1 0 32 1H1.1 问题背景和研究意义33H1 2H1.2 论文结构和主要工作34H5 H第 2章 个人信用评分主要模型及其比较. H7 3 35 4H2.1 主要模型. 36H7 5H2.2 模型比较37H13 H2.3 模型改进H17 6 38 7H第 3章 在信用额度评价中的应用39H21 8H3.1 应用原理40H21 H3.2 直接预测评价法H22 9 41 10H3.3 贝叶斯预测评价法. 42H24 11H第 4章 数据建模实例分析43H29 H4.1 数据概况H29 12 44 13H4.2 建模步骤45H30 14H4.3 模型验证46H38 H第 5章 结语H42 15 47 16H5.1 总结. 48H42 17H5.2 展望. 49H44 H附 录H45 18 50 19H附录 1:诊断变量的SAS宏程序代码. 51H45 20H附录 2:数据清理剔除变量52H48 H附录 3:建模分类变量和连续变量H50 21 53 22H附录 4:分类变量的卡方检验(按卡方值排序前 40位) 54H62 23H附录 5:分类变量的Logistic单步回归检验(按卡方值排序前 40位) 55H63 H附录 6:连续变量的卡方检验(按卡方值排序前 80位) H64 24 56 25H附录 7:连续变量的Logistic单步回归检验(按卡方值排序前 80位) 57H66 26H附录 8:连续变量转换和筛选的SAS宏代码. 58H68个人信用评分模型及其在信用额度评价中