基于BP神经网络的商业银行供应链融资信用风险评价研究
发布时间：2018-11-17 12:06
【摘要】：占我国企业总数九成以上的中小型企业为我国经济的发展起着无可替代的作用,它们促进了企业之间的公平竞争,增加了就业机会,同时在维护社会稳定上也发挥了重要作用。但是,中小企业获得的信贷支持却与其对社会做出的贡献极不相称,资金的瓶颈已成为了阻碍中小企业发展的主要问题,而供应链融资业务正是为中小企业量身打造的新型筹资模式。 本文主要从供应链融资信用风险评价角度进行研究。首先提出此次研究的背景并概述当前国内外该领域研究的现状,然后对已有研究成果加以评析并指出其中的不足,在此基础上确立了该篇文章研究的重点。其次,本文论述了信用风险评价在供应链融资业务风险管理与控制中的重要性；商业银行供应链融资信用风险概念的界定；BP神经网络的理论基础以及供应链融资业务中信用风险评价指标体系的构建。在借鉴国内外供应链金融领域学者研究成果的基础上,本文经过筛选归纳出供应链融资业务中整个融资过程中的28个信用风险影响因子并进行了相关性分析及鉴别力检验,建立起具有很好稳定性与一致性的供应链融资信用风险指标体系。对供应链融资业务信用风险状况科学、准确地评价是本文所要研究的核心问题,文章在具体分析用BP神经网络评估供应链融资信用风险具有的优势的基础上,根据MATLAB软件平台上BP神经网络模块的构建要求,确定包括传递函数、训练算法等在内的网络初始参数,从而构建了供应链融资信用风险评价仿真模型。在此基础上,通过运用查询公开数据及调查问卷相结合的方法采集到十三组供应链融资信用风险样本并对其进行归一化处理。根据研究的需要,本文随机选取其中的十组样本数据作为训练样本,把剩余三组数据作为检验样本。最后通过训练样本与神经网络工具箱在MATLAB7.0平台上对供应链融资信用风险评价模型进行仿真,并通过检验样本来检验该模型的有效性。 本文在构建商业银行供应链融资信用风险评价指标体系的基础上,基于BP神经网络结合该体系建立起具有良好风险评估能力的供应链融资信用风险评价模型,且对所建立的模型进行比较充分的实证分析验证,相信该模型的不断完善及应用能为商业银行降低供应链融资业务信用风险提供借鉴,具有很强的现实意义。
[Abstract]:Small and medium-sized enterprises, which account for more than 90% of the total number of enterprises in China, play an irreplaceable role in the development of our economy. They promote fair competition among enterprises, increase employment opportunities, and also play an important role in maintaining social stability. However, the credit support received by SMEs is not commensurate with their contribution to society, and the bottleneck of capital has become the main problem that hinders the development of SMEs. And supply chain financing business is for small and medium-sized enterprises to create a new type of financing model. This article mainly carries on the research from the supply chain financing credit risk appraisal angle. Firstly, the background of this study is put forward and the present situation of the research in this field is summarized, then the existing research results are evaluated and the deficiencies are pointed out. On this basis, the emphasis of this article is established. Secondly, this paper discusses the importance of credit risk evaluation in the management and control of supply chain financing business risk, the definition of the concept of credit risk in supply chain financing of commercial banks. The theoretical basis of BP neural network and the construction of credit risk evaluation index system in supply chain financing business. Based on the research results of domestic and foreign supply chain finance scholars, this paper concludes 28 credit risk influencing factors in the whole financing process of supply chain financing, and carries out correlation analysis and discriminant test. Establish a supply chain financing credit risk index system with good stability and consistency. The key problem of this paper is to evaluate the credit risk of supply chain financing business scientifically and accurately. This paper analyzes the advantages of evaluating the credit risk of supply chain financing by BP neural network. According to the requirements of BP neural network module on MATLAB software platform, the initial network parameters, including transfer function and training algorithm, are determined, and the credit risk evaluation simulation model of supply chain financing is constructed. On this basis, thirteen groups of supply chain financing credit risk samples are collected and normalized by using the method of query public data and questionnaire. According to the needs of the research, ten groups of samples are randomly selected as training samples, and the remaining three groups of data are used as test samples. Finally, the credit risk evaluation model of supply chain financing is simulated on MATLAB7.0 platform by training sample and neural network toolbox, and the validity of the model is verified by testing samples. On the basis of constructing the credit risk evaluation index system of supply chain financing of commercial banks, based on BP neural network and this system, a credit risk evaluation model of supply chain financing with good risk assessment ability is established. It is believed that the continuous improvement and application of the model can provide a reference for commercial banks to reduce the credit risk of supply chain financing business, which has a strong practical significance.
【学位授予单位】：浙江工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F832.2;F224
本文编号：2337728
[Abstract]:Small and medium-sized enterprises, which account for more than 90% of the total number of enterprises in China, play an irreplaceable role in the development of our economy. They promote fair competition among enterprises, increase employment opportunities, and also play an important role in maintaining social stability. However, the credit support received by SMEs is not commensurate with their contribution to society, and the bottleneck of capital has become the main problem that hinders the development of SMEs. And supply chain financing business is for small and medium-sized enterprises to create a new type of financing model. This article mainly carries on the research from the supply chain financing credit risk appraisal angle. Firstly, the background of this study is put forward and the present situation of the research in this field is summarized, then the existing research results are evaluated and the deficiencies are pointed out. On this basis, the emphasis of this article is established. Secondly, this paper discusses the importance of credit risk evaluation in the management and control of supply chain financing business risk, the definition of the concept of credit risk in supply chain financing of commercial banks. The theoretical basis of BP neural network and the construction of credit risk evaluation index system in supply chain financing business. Based on the research results of domestic and foreign supply chain finance scholars, this paper concludes 28 credit risk influencing factors in the whole financing process of supply chain financing, and carries out correlation analysis and discriminant test. Establish a supply chain financing credit risk index system with good stability and consistency. The key problem of this paper is to evaluate the credit risk of supply chain financing business scientifically and accurately. This paper analyzes the advantages of evaluating the credit risk of supply chain financing by BP neural network. According to the requirements of BP neural network module on MATLAB software platform, the initial network parameters, including transfer function and training algorithm, are determined, and the credit risk evaluation simulation model of supply chain financing is constructed. On this basis, thirteen groups of supply chain financing credit risk samples are collected and normalized by using the method of query public data and questionnaire. According to the needs of the research, ten groups of samples are randomly selected as training samples, and the remaining three groups of data are used as test samples. Finally, the credit risk evaluation model of supply chain financing is simulated on MATLAB7.0 platform by training sample and neural network toolbox, and the validity of the model is verified by testing samples. On the basis of constructing the credit risk evaluation index system of supply chain financing of commercial banks, based on BP neural network and this system, a credit risk evaluation model of supply chain financing with good risk assessment ability is established. It is believed that the continuous improvement and application of the model can provide a reference for commercial banks to reduce the credit risk of supply chain financing business, which has a strong practical significance.
【学位授予单位】：浙江工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F832.2;F224
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