金融服务业的快速发展，传统依靠人工审批贷款的模式呈现出明显的局限性。近
年来，大数据技术对传统的信用评估方式产生了深刻的影响，而信用评分模型正是利
用数据挖掘技术，综合考虑客户各方面的基本信息、历史记录，对其违约风险和信用
资质进行量化评估。信用评分是指根据银行客户的历史信用资料，利用一定的信用评
分模型，评估出不同等级的信用分数。根据借款用户过去的信用表现来预测其未来的
信用行为。根据客户的信用分数，通过分析客户按时还款的可能性，据此决定是否给
予授信、授信的额度和利率，以及贷后的额度调整、定价及催收等相应的风险措施
本文在介绍信用评分模型的基本概念和开发过程的基础上，分析信用评分模型在
商业银行的应用及其价值点，以 S 银行积累的客户数据为研究对象，采用 logistic
回归数据挖掘技术，利用先进的统计软件和商业银行智能软件 SAS 进行分析，建立个
人经营性贷款的信用评估模型。 同时结合 S 银行的现状，发现当前 S 银行存在信用
评估问题，并对该问题产生原因进行分析。提出了适合 S 银行的相应对策与建议，为
同类商业银行的个人信用风险评估提供相关的理论支持。并总结目前该模型在实际应
用中的局限性和发展前景，希望能对银行信用评估方法有一些启示
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关键词：大数据，数据挖掘，信用评分模型，个人经营性贷款，逻辑回归
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作者：刘国斌
指导老师：孙耀英文摘要 S 银行基于大数据的个人信用研究
II
Research of S bank’s personal credit based on big data
---- for example personal business loan
Abstract
With the development of the socialist market economy and the deepening of reform,
the relevant policies of the state have gradually formed a healthy environment conducive to
the development of the private economy. The demand for individual and private economic
financing has become increasingly important. As a source of profit for commercial banks’s
personal business loans business gets more and more attention. The credit risk
management ， It is very necessary to established an risk managementmechanismof
commercial banks and improve itcontinually, As it is an integral part of the comprehensive
risk management of commercial banks.
With the rapid development of the financial services industry, There are obvious
limitations as the traditional model of approval of the loan which rely on manual.In recent
years, large data technology has a profound impact on the traditional credit assessment
methods, Using data mining technology, credit score model takes into account various
aspects of customer information, historical records, making the evaluation of the default
risk and credit qualification. Credit score is based on the bank customer&39;s historical credit
information, using a certain credit score model to assess the different grades of credit
scores. According to the borrower&39;s past credit performance to predict its future credit
behavior. and the customer&39;s credit score, by analyzing the possibility of repayment on time
of customers, to grant credit, credit lines and interest rates, as well as the amount of credit
after the adjustment, pricing and collection of appropriate risk measures.
On the basis of introducing the basic concept and development process of the credit
score model, this paper analyzes the application and value of the credit score model in the
commercial bank, and takes the customer data accumulated by the S bank as the research
object, using the logistic regression data mining technology, and analysis with the
statistical and commercial banking intelligent software SAS, establish a personal business
loans credit assessment model. At the same time combined with the situation of S Bank,
find out the S bank’s currentproblem of credit assessment, and the causes of the problem.S 银行基于大数据的个人信用研究 英文摘要
III
And puts forward the corresponding countermeasures and suggestions for the bank of S,
and provides relevant theoretical support for the personal credit risk assessment of similar
commercial banks. And summarizes the limitations and prospects of the current model in
practical application, hoping this will bring some enlightenment on the method of bank
credit assessment.
Key words: big data, data mining, credit scoring model, personal business loan,
logistic regression
Written by: LiuGuobin
Supervised by: SunYao
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目 录
第 1 章 绪 论 ··1
1.1 论文选题背景与研究意义·1
1.1.1 论文选题背景··1
1.1.2 论文选题目的与意义··2
1.2 国内外研究综述及简要评析·3
1.2.1 国外研究现状··3
1.2.2 国内研究现状··5
1.3 研究方法、研究思路及框架·7
第 2 章 本研究的相关理论与方法概述 ··9
2.1 个人信用的相关概念·9
2.1.1 信用 ·9
2.1.2 个人信用 ·9
2.1.3 信用风险 ·· 10
2.1.4 个人信用评分 10
2.1.5 个人经营性贷款 12
2.2 个人信用评估模型建立过程及方法 ·· 12
2.2.1 评估模型的建立过程 12
2.2.2 评估模型样本数据准备 16
2.2.3 评分模型的验证方法 17
第 3 章 S 银行个人经营性贷款信用评估现状分析·19
3.1 银行业务情况概述·· 19
3.1.1 业务发展现状 19
3.1.2 个人经营性贷款的现状 19
3.2 个人经营性贷款的信用评估问题分析 ·· 21
3.2.1 信用评估风险高 21
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3.2.2 贷款审批效率低 21
3.2.3 信用情况难跟踪 21
3.2.4 贷款质量难保证 22
3.3 个人经营性贷款的信用评估现状分析 ·· 22
3.3.1 信用评估方法落后不统一 22
3.3.2 贷款审批流程方式落后 22
3.3.3 信用风险预测手段欠缺 23
3.3.4 贷款过程检查不合规 23
第 4 章 S 银行个人经营性贷款的信用评估模型的构建·24
4.1 信用评估模型概述·
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