本文關(guān)鍵詞： 供應(yīng)鏈金融 信用風(fēng)險(xiǎn)評估 主成分分析法 最小二乘模糊支持向量機(jī)　出處：《華南理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：供應(yīng)鏈金融服務(wù)起源于20世紀(jì)90年代，最開始是由國內(nèi)外的先進(jìn)物流企業(yè)和商業(yè)銀行開展的。國內(nèi)外一些先進(jìn)的物流企業(yè)及銀行適時(shí)地推出了多樣化的供應(yīng)鏈金融服務(wù)，以幫助企業(yè)實(shí)現(xiàn)對資金流的管理。近年來供應(yīng)鏈金融己成為許多物流企業(yè)、金融機(jī)構(gòu)關(guān)注的焦點(diǎn)。在國內(nèi)，供應(yīng)鏈金融業(yè)務(wù)是針對供應(yīng)鏈的業(yè)務(wù)結(jié)構(gòu)、交易方式及運(yùn)作特點(diǎn)而設(shè)計(jì)的，以供應(yīng)鏈中最具有信用實(shí)力的大企業(yè)為核心，，圍繞與之在生產(chǎn)過程、銷售過程中開展業(yè)務(wù)的多家中小企業(yè)，將整個(gè)供應(yīng)鏈鏈條涉及到的上下游企業(yè)連起來，整體考察供應(yīng)鏈的信用狀況，更好地為中小企業(yè)提供金融服務(wù)，從而促進(jìn)整個(gè)供應(yīng)鏈價(jià)值的增長。 過去商業(yè)銀行對中小融資企業(yè)信用風(fēng)險(xiǎn)的評估主要是著力于單個(gè)中小融資企業(yè)本身，分析其財(cái)務(wù)數(shù)據(jù)，關(guān)注其抵押物質(zhì)等，而在供應(yīng)鏈金融融資模式中，對中小融資企業(yè)風(fēng)險(xiǎn)的認(rèn)識和評估則換了一個(gè)新的視角。把供應(yīng)鏈融資模式中的核心企業(yè)也作為考察的主體，以及整個(gè)供應(yīng)鏈鏈條的穩(wěn)定作為參考因素。 本文以供應(yīng)鏈金融為視角研究商業(yè)銀行對中小融資企業(yè)信用風(fēng)險(xiǎn)的評估，首先通過分析供應(yīng)鏈金融融資模式的特點(diǎn)，構(gòu)建基于供應(yīng)鏈金融的信用風(fēng)險(xiǎn)評價(jià)指標(biāo)體系；接著采用主成分分析法對指標(biāo)數(shù)據(jù)進(jìn)行降維處理，簡化數(shù)據(jù)結(jié)構(gòu)提高分類效率；對比分析現(xiàn)有信用風(fēng)險(xiǎn)評價(jià)方法的優(yōu)缺點(diǎn)，確定用支持向量機(jī)SVM方法進(jìn)行評估，具體選擇了帶模糊隸屬度的模糊支持向量機(jī)并引入可變罰因子對其算法進(jìn)行改進(jìn)，在此基礎(chǔ)上建立了供應(yīng)鏈金融信用風(fēng)險(xiǎn)評估模型。 模型的求解過程中，引入二次損失函數(shù)將復(fù)雜的二次規(guī)劃問題轉(zhuǎn)化為求解線性方程，求出最優(yōu)分類函數(shù)。最后通過實(shí)證研究，將基于主成分分分析與最小二乘模糊支持向量機(jī)（PCA-LSFSVM）的供應(yīng)鏈金融信用風(fēng)險(xiǎn)評估模型與基于二分類Logistic回歸的供應(yīng)鏈金融信用評估模型進(jìn)行對比分析，證實(shí)了基于PCA-LSFVM的供應(yīng)鏈金融信用風(fēng)險(xiǎn)評估模型性能優(yōu)越，能有效地解決供應(yīng)鏈金融的信用評估問題，從而為商業(yè)銀行供應(yīng)鏈金融信用風(fēng)險(xiǎn)評估提供科學(xué)合理的有效工具，有著重要的理論價(jià)值和現(xiàn)實(shí)意義。
[Abstract]:Supply chain financial services originated in 1990s. At the beginning, it was carried out by advanced logistics enterprises and commercial banks at home and abroad. Some advanced logistics enterprises and banks at home and abroad launched diversified supply chain financial services in good time. In recent years, supply chain finance has become the focus of many logistics enterprises and financial institutions. In China, supply chain financial business is aimed at the business structure of supply chain. The transaction mode and operation characteristics of the design, the supply chain with the most credit strength of the large enterprises as the core, around the production process, sales process business with a number of small and medium-sized enterprises. Connecting the upstream and downstream enterprises involved in the whole supply chain, the credit condition of the whole supply chain is investigated, and the financial service is provided to the small and medium-sized enterprises better, thus promoting the growth of the value of the whole supply chain. In the past, commercial banks mainly focused on the credit risk assessment of small and medium-sized financing enterprises, analyzed their financial data, paid attention to their mortgage materials, and so on, but in the financing mode of supply chain finance. The cognition and evaluation of the risk of the medium and small financing enterprises have changed a new angle of view. The core enterprises in the financing mode of supply chain are also taken as the main body of investigation, and the stability of the whole supply chain is taken as the reference factor. This paper studies the credit risk assessment of small and medium-sized financing enterprises by commercial banks from the perspective of supply chain finance. Firstly, it analyzes the characteristics of the supply chain financial financing model. Constructing credit risk evaluation index system based on supply chain finance; Then the principal component analysis (PCA) is used to reduce the dimension of the index data and simplify the data structure to improve the classification efficiency. Comparing and analyzing the advantages and disadvantages of the existing credit risk evaluation methods, the support vector machine (SVM) SVM method is used to evaluate. The fuzzy support vector machine with fuzzy membership is selected and the variable penalty factor is introduced to improve the algorithm. On this basis, the credit risk assessment model of supply chain finance is established. In the process of solving the model, the quadratic loss function is introduced to transform the complex quadratic programming problem into solving the linear equation, and the optimal classification function is obtained. Finally, the empirical study is carried out. PCA-LSFSVM based on principal component analysis (PCA) and least square fuzzy support vector machine (LSSVM) is proposed. The model of supply chain financial credit risk assessment is compared with the supply chain financial credit evaluation model based on two-classification Logistic regression. It is proved that the credit risk assessment model of supply chain finance based on PCA-LSFVM has superior performance and can effectively solve the credit evaluation problem of supply chain finance. Therefore, it is of great theoretical and practical significance to provide a scientific and effective tool for the credit risk assessment of the supply chain finance of commercial banks.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F832;F224

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