【作者】 周鑫；

【导师】 夏洪胜；

【作者基本信息】 暨南大学 ， 管理科学与工程， 2013， 硕士

【摘要】 随着银行业竞争的加剧，为了扩展业务范围，增强市场竞争力，国内商业银行从全新的视角出发，开辟了基于供应链的中小企业融资业务模式——供应链金融。供应链金融是为中小融资企业服务的，其成功实施的关键是对中小企业的信用风险进行客观且公正的评价。但是，我国供应链金融的发展尚处于起步阶段，目前并没有非常完善的、成熟的中小企业信用风险评价体系。鉴于此，基于现有中小企业信用评价研究，本文站在银行的视角，从融资企业所处行业状况、融资企业自身状况、核心企业状况、供应链关系状况四个方面出发，建立了基于供应链金融的中小企业信用评价指标体系。在指标体系的基础上，本文用Logistic回归和BP神经网络分别对供应链金融指标体系下和传统指标体系下的中小企业信用风险进行了评价，并对基于两种方法和两种指标体系的评价结果进行了对比分析。研究结果表明：供应链金融使中小融资企业凭借其与供应链核心企业的稳定的合作关系而达到自身的信用增级，使原本单靠自身资信水平达不到银行授信标准的中小融资企业获得资金支持，从而解决了诸多中小企业融资难的困境。此外，本文的研究也证明，Logistic回归和BP神经网络都是对中小企业履约情况的判断有较高的准确率的可靠的信用评价方法。更多还原

【Abstract】 With the competition of banking industry more and more fierce, in order to expand the sphere ofbusiness and enhance the competitiveness, commercial banks in China, from a new perspective,opened up a new financing model named supply chain finance based on supply chain for smalland medium-sized enterprises(SMEs).Supply chain finance serves for small and medium-sizedfinancing enterprises, and the key to its successful implementation lies on objective and fairevaluation of credit risk of SMEs. However, the development of supply chain finance in China isstill in the initial stage, and currently there is no perfect and mature credit risk evaluation systemfor SMEs. Given this, based on the existing study on credit risk evaluation model for SMEs andsupply chain risk evaluation, this article stands on the bank’s viewpoint and establishes a creditevaluation index system based on supply chain finance for SMEs from four aspects: industrystatus, financing SMEs status, core enterprise status and supply chain operation status. Based onthis index system, this article uses Logistic regression and BP neural network to evaluate thecredit risk of SMEs respectively under credit evaluation index system based on supply chainfinance and under traditional credit evaluation index system, and makes a comparative analysison the results resulted from the two methods and two kinds of index system. The study showsthat small and medium-sized financing enterprises make its own credit level lift by means of itssteady partnership with core enterprise in the supply chain, which makes SMEs not up to thefinancing credit standard through its own credit level get a bank loan, and thereby at some degreesolves financing difficulties of a lot of SMEs. What’s more, this article indicates that bothLogistic regression and BP neural network are reliable credit evaluation methods which have ahigh accuracy on judgment on performance of small and medium financing enterprises.更多还原