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The Credit Risk Evaluation Model And Empirical Research Of Small And Medium-Sized Technological Enterprise

Posted on:2020-05-18Degree:MasterType:Thesis
Country:ChinaCandidate:F F XueFull Text:PDF
GTID:2439330602466755Subject:Statistics
Abstract/Summary:PDF Full Text Request
Since the reform and opening up,the national economy has developed rapidly.Technology-based small and medium-sized enterprises,with their unique high innovation and growth,are gradually beeoming an important support for social and economic progress and national strength enhancement.The CPC Central Committee and the State Council attach great importance to the development of small and medium-sized enterprises.In order to promote the healthy development of small and medium-sized enterprises,a series of policies and measures have been put forward in finance,taxation,business environment and public services.On April 7,the General Office of the Central Office of the Communist Party of China issued the Guiding Opinions on Promoting the Healthy Development of Small and Medium-sized Enterprises(SMEs),which pointed out that the central government should strengthen its support for SMEs,innovation.However,the current situation of small and medium-sized science and technology enterprises in China is not consistent with their important position in the national economic system.Because of the large investment in R&D and the large demand for funds,and because of its small scale,weak credit awareness,high operational risk and less collaterable property,the small and medium-sized technology-based SMEs in China have been facing the problem of financing.In recent years,the government has formulated many supportive policies,but the problem of financing is still prominent in China's small and medium-sized science and technology enterprises.In the Guiding Opinions on Deepening the Construction of SMEs,Loan and Credit Guarantee System issued by the Development and Reform Commission in December 2018,it is pointed out that promoting the construction of SMEs' credit system is an effective measure to solve the problems of asymmetric financing information,high default rate,lower financing cost and improve financing efficiency of SMEs.Therefore,the establishment of credit risk evaluation index system in line with the characteristics of small and medium-sized science and technology enterprises in China has become the focus of this paper.Based on this background,this paper studies the credit risk evaluation of small and medium-sized technology-based enterprises.Firstly,this paper studies the mainstream credit risk evaluation index system at home and abroad,and then comprehensively analyses the factors affecting the credit risk of small and medium-sized technology-based enterprises based on the characteristics of small and medium-sized technology-based enterprises in China.After that,it fully considers the basic conditions,operating capacity,solvency and profitability of small and medium-sized technology-based enterprises.To develop the ability,and innovatively consider the quality of enterprise managers,innovation ability and macroeconomic environment,and establish a set of perfect evaluation index system.Then the credit risk evaluation model of small and medium-sized technological enterprises is optimized.The weight of each index is set by using the combination of entropy method,coefficient of variation method and analytic hierarchy process,and the grey correlation analysis method is used to improve the fuzzy comprehensive evaluation model.The model is used to evaluate the credit risk of science and technology SMEs in Dalian.After the evaluation work is completed,the association rule algorithm is used to correlate the credit evaluation results with the enterprise performance data.It is found that the evaluation results obtained in this paper are consistent with the actual situation of Dalian science and technology SMEs,it also analyzes the financial characteristics of the better credit status and the worse enterprises.Finally,according to the conclusions drawn by the research institute,some suggestions are put forward to further improve the credit risk evaluation system of science and technology SMEs in China in the future.By establishing a credit risk evaluation system for small and medium-sized technology-based enterprises,this paper hopes to provide some reference for banks and other financial institutions to grant loans;improve the theory of credit construction in China,provide ideas and theoretical support for the formulation of relevant laws and policies;and alleviate the financing difficulties of small and medium-sized technology-based enterprises.The innovation of this paper mainly includes the following aspects:first,in the research object and data selection.In this paper,the relevant data of small and medium-sized technology-based enterprises collected by the torch center of the Ministry of science and technology of Dalian city are taken as the research samples for the corresponding empirical analysis,which is relatively general.Second,the evaluation index system.This paper fully considers the characteristics of small and medium-sized technology-based enterprises,focuses on their innovation ability,growth ability,and the quality of enterprise managers and the external economic environment.In addition,the correlation of financial indicators is tested to make the established indicator system more comprehensive and scientific.The third is in the evaluation model.In order to avoid the one sidedness of single weighting method,this paper uses entropy method,coefficient of variation method and AHP subjective and objective combination weighting method to weight the index,and uses the grey correlation analysis method to determine the evaluation matrix,which makes the model more scientific in data processing.Fourthly,after the evaluation work is completed,the association rule algorithm is used to combine the credit risk evaluation results with the enterprise performance data for association analysis,which verifies the validity and scientificity of the evaluation results.
Keywords/Search Tags:Small and Medium-sized Technological Enterprises, Credit risks, Combination weighting, Grey relational analysis, The Apriori algorithm
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