G商业银行中小企业信用评级模型的分析与改进研究
发布时间：2021-02-16 04:30
中小企业是推动国民经济发展,构造市场经济主体,促进社会稳定的基础力量。特别是当前,我国经济受国内外复杂多变的政治环境影响,不确定因素较多,而中小企业在缓解社会就业压力、实现科教兴国、优化经济结构等方面,发挥着越来越重要的作用。为此,国家也正围绕中小企业的发展问题,推动着各地方机构出台新政策、新措施,以扶持中小企业发展。而商业银行,作为我国金融业中历史最悠久,也是最成熟的金融机构,首当其冲应成为扶持中小企业发展的主要力量。但在近年来,受互联网金融等新经济体的冲击,商业银行目前在开展中小企业业务方面,尤其是信贷业务,正面临着诸多困难与挑战。本文以G商业银行中小企业信用评级模型为实际案例进行研究,通过分析G型商业银行中小企业信用评级模型存在的问题,剖析问题形成的原因,提出了针对原模型的缺陷项进行改进,构建G商业银行新的中小企业信用评级模型。并运用G商业银行的中小企业客户作为样本,对新模型进行了效果检验,从而判断新模型对比旧模型是否有改进效果。本文最后提出了对G商业银行的信用评级制度及工作流程的改进建议,拟提高该银行的信用评级模型的实际应用效果。本文的主要结论是,G商业银行中小企业信用评级的原...
【文章来源】：广东外语外贸大学广东省
【文章页数】：82 页
【学位级别】：硕士
【文章目录】：
ACKNOWLEDGEMENTS
ABSTRACT
摘要
LIST OF ABBREVIATIONS
Chapter I Introduction
1.1 Research Background
1.2 Research Significance
1.2.1 Theoretical significance
1.2.2 Practical significance
1.3 Research Method and Idea
1.3.1 Research Method
1.3.2 Research Outline
1.4 Basic Content of the Research
ChapterⅡ Literature Review
2.1 Literature on Classical Index Model
2.2 Literature on Modern Index Model
2.3 Literature Comments
ChapterⅢ Case Description
3.1 Profile of G Commercial Bank
3.2 Credit Rating System of SMEs in G Commercial Bank
3.2.1 Accessing Industry of the SMEs Customer in G Commercial Bank
3.2.2 Credit rating model of SMEs in G commercial bank
3.2.3 Definition of the customers’ indicators of the credit rating model
3.3 Process of the credit rating of SMEs in G commercial bank
ChapterⅣ Case Analysis
4.1 Problems existing in the credit rating model of SMEs in G commercial bank
4.1.1 Lack of objective quantitative analysis for the integrity of the rating objects
4.1.2 The rating process is subjectively influenced by the raters and lacks dynamicverification
4.2 Analysis of the Reasons for the Credit Rating Model of SMEs in G CommercialBank
4.2.1 Comprehensiveness of Rating Data
4.2.2 The composition of rating index system needs further study
4.2.3 Credit rating system is not perfect and lacks perfect system support
4.2.4 Lack of Credit Rating Professionals
ChapterⅤSolution and Test
5.1 Theory Basis for Credit Rating Model Optimization
5.2 Improvement for the credit rating model of SMEs in G commercial bank
5.2.1 Add indicator 1: Negative information concerning liability for breach of contract
5.2.2 Add indicator 2: Negative information on private lending
5.2.3 Add indicator 3: Negative information concerning labor disputes
5.2.4 Add indicator 4: Negative information on trade disputes
5.2.5 The Index Optimizing Item of Credit Rating Model for SMEs of G CommercialBank
5.3 Test on the Improvement Effect of Credit Rating Model for SMEs in GCommercial Bank
5.3.1 Test steps
5.3.2 Sampling test
5.4 Optimized credit rating system of SMEs in G commercial bank
ChapterⅥ Conclusions and Suggestions
6.1 Conclusions
6.1.1 The evaluation effect of the original SME rating model of G Commercial Bankis not good enough to evaluate the credibility of rating objects
6.1.2 New Credit Assessment Model for SMEs in G Commercial Banks has a moreaccurate screening effect for default customers
6.1.3 Research results have certain industry reference significance
6.2 Suggestions
6.2.1 Strengthen docking with external data sources to speed up the construction ofenterprise wind control database in banks
6.2.2 Reduce the Dependence on Mortgage
6.2.3 Strengthen the management of post-loan rating process
6.2.4 Reduce the Credit Reviewers' Right to Adjust Rating
6.3 Prospects
REFERENCES
【参考文献】：
期刊论文
[1]模糊层次分析法在小额贷款信用评级中的应用[J]. 郭驰,杨扬,王超,杨瑞. 河北工程大学学报(自然科学版). 2013(02)
[2]国际供应链金融三种典型模式分析[J]. 谢世清,何彬. 经济理论与经济管理. 2013(04)
[3]中国信用评级业的供需矛盾及解决途径探讨[J]. 彭宇松. 上海金融. 2010(12)
[4]模糊影响图评价算法在供应链金融信用风险评估中的应用[J]. 孔媛媛,王恒山,朱珂,李晟. 数学的实践与认识. 2010(21)
[5]面向供应链融资企业信用风险评估指标体系设计[J]. 白少布. 经济经纬. 2009(06)
[6]基于朴素贝叶斯的供应链金融信用风险预测分析[J]. 黄静,赵庆祯. 物流科技. 2009(08)
[7]国有商业银行RAROC贷款定价模型及应用[J]. 边俊杰,冯莲娜,刘立刚. 改革与战略. 2008(12)
[8]基于CreditMetrics模型评估银行信贷的信用风险[J]. 窦文章,刘西. 改革与战略. 2008(10)
[9]基于logistic模型的上市公司信用风险评价[J]. 傅强,李永涛. 华东经济管理. 2005(09)
本文编号：3036163
【文章来源】：广东外语外贸大学广东省
【文章页数】：82 页
【学位级别】：硕士
【文章目录】：
ACKNOWLEDGEMENTS
ABSTRACT
摘要
LIST OF ABBREVIATIONS
Chapter I Introduction
1.1 Research Background
1.2 Research Significance
1.2.1 Theoretical significance
1.2.2 Practical significance
1.3 Research Method and Idea
1.3.1 Research Method
1.3.2 Research Outline
1.4 Basic Content of the Research
ChapterⅡ Literature Review
2.1 Literature on Classical Index Model
2.2 Literature on Modern Index Model
2.3 Literature Comments
ChapterⅢ Case Description
3.1 Profile of G Commercial Bank
3.2 Credit Rating System of SMEs in G Commercial Bank
3.2.1 Accessing Industry of the SMEs Customer in G Commercial Bank
3.2.2 Credit rating model of SMEs in G commercial bank
3.2.3 Definition of the customers’ indicators of the credit rating model
3.3 Process of the credit rating of SMEs in G commercial bank
ChapterⅣ Case Analysis
4.1 Problems existing in the credit rating model of SMEs in G commercial bank
4.1.1 Lack of objective quantitative analysis for the integrity of the rating objects
4.1.2 The rating process is subjectively influenced by the raters and lacks dynamicverification
4.2 Analysis of the Reasons for the Credit Rating Model of SMEs in G CommercialBank
4.2.1 Comprehensiveness of Rating Data
4.2.2 The composition of rating index system needs further study
4.2.3 Credit rating system is not perfect and lacks perfect system support
4.2.4 Lack of Credit Rating Professionals
ChapterⅤSolution and Test
5.1 Theory Basis for Credit Rating Model Optimization
5.2 Improvement for the credit rating model of SMEs in G commercial bank
5.2.1 Add indicator 1: Negative information concerning liability for breach of contract
5.2.2 Add indicator 2: Negative information on private lending
5.2.3 Add indicator 3: Negative information concerning labor disputes
5.2.4 Add indicator 4: Negative information on trade disputes
5.2.5 The Index Optimizing Item of Credit Rating Model for SMEs of G CommercialBank
5.3 Test on the Improvement Effect of Credit Rating Model for SMEs in GCommercial Bank
5.3.1 Test steps
5.3.2 Sampling test
5.4 Optimized credit rating system of SMEs in G commercial bank
ChapterⅥ Conclusions and Suggestions
6.1 Conclusions
6.1.1 The evaluation effect of the original SME rating model of G Commercial Bankis not good enough to evaluate the credibility of rating objects
6.1.2 New Credit Assessment Model for SMEs in G Commercial Banks has a moreaccurate screening effect for default customers
6.1.3 Research results have certain industry reference significance
6.2 Suggestions
6.2.1 Strengthen docking with external data sources to speed up the construction ofenterprise wind control database in banks
6.2.2 Reduce the Dependence on Mortgage
6.2.3 Strengthen the management of post-loan rating process
6.2.4 Reduce the Credit Reviewers' Right to Adjust Rating
6.3 Prospects
REFERENCES
【参考文献】：
期刊论文
[1]模糊层次分析法在小额贷款信用评级中的应用[J]. 郭驰,杨扬,王超,杨瑞. 河北工程大学学报(自然科学版). 2013(02)
[2]国际供应链金融三种典型模式分析[J]. 谢世清,何彬. 经济理论与经济管理. 2013(04)
[3]中国信用评级业的供需矛盾及解决途径探讨[J]. 彭宇松. 上海金融. 2010(12)
[4]模糊影响图评价算法在供应链金融信用风险评估中的应用[J]. 孔媛媛,王恒山,朱珂,李晟. 数学的实践与认识. 2010(21)
[5]面向供应链融资企业信用风险评估指标体系设计[J]. 白少布. 经济经纬. 2009(06)
[6]基于朴素贝叶斯的供应链金融信用风险预测分析[J]. 黄静,赵庆祯. 物流科技. 2009(08)
[7]国有商业银行RAROC贷款定价模型及应用[J]. 边俊杰,冯莲娜,刘立刚. 改革与战略. 2008(12)
[8]基于CreditMetrics模型评估银行信贷的信用风险[J]. 窦文章,刘西. 改革与战略. 2008(10)
[9]基于logistic模型的上市公司信用风险评价[J]. 傅强,李永涛. 华东经济管理. 2005(09)
本文编号：3036163
本文链接：https://www.wllwen.com/jingjilunwen/huobiyinxinglunwen/3036163.html
