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Research On Credit Evaluation For Smes Based On Supply Chain Finance

Posted on:2014-08-27Degree:MasterType:Thesis
Country:ChinaCandidate:X ZhouFull Text:PDF
GTID:2269330392963941Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
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.
Keywords/Search Tags:supply chain finance, credit risk evaluation, SMEs, Logistic regression, BP neural network
PDF Full Text Request
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