【摘要】：占我國(guó)企業(yè)總數(shù)九成以上的中小型企業(yè)為我國(guó)經(jīng)濟(jì)的發(fā)展起著無(wú)可替代的作用,它們促進(jìn)了企業(yè)之間的公平競(jìng)爭(zhēng),增加了就業(yè)機(jī)會(huì),同時(shí)在維護(hù)社會(huì)穩(wěn)定上也發(fā)揮了重要作用。但是,中小企業(yè)獲得的信貸支持卻與其對(duì)社會(huì)做出的貢獻(xiàn)極不相稱,資金的瓶頸已成為了阻礙中小企業(yè)發(fā)展的主要問(wèn)題,而供應(yīng)鏈融資業(yè)務(wù)正是為中小企業(yè)量身打造的新型籌資模式。 本文主要從供應(yīng)鏈融資信用風(fēng)險(xiǎn)評(píng)價(jià)角度進(jìn)行研究。首先提出此次研究的背景并概述當(dāng)前國(guó)內(nèi)外該領(lǐng)域研究的現(xiàn)狀,然后對(duì)已有研究成果加以評(píng)析并指出其中的不足,在此基礎(chǔ)上確立了該篇文章研究的重點(diǎn)。其次,本文論述了信用風(fēng)險(xiǎn)評(píng)價(jià)在供應(yīng)鏈融資業(yè)務(wù)風(fēng)險(xiǎn)管理與控制中的重要性；商業(yè)銀行供應(yīng)鏈融資信用風(fēng)險(xiǎn)概念的界定；BP神經(jīng)網(wǎng)絡(luò)的理論基礎(chǔ)以及供應(yīng)鏈融資業(yè)務(wù)中信用風(fēng)險(xiǎn)評(píng)價(jià)指標(biāo)體系的構(gòu)建。在借鑒國(guó)內(nèi)外供應(yīng)鏈金融領(lǐng)域?qū)W者研究成果的基礎(chǔ)上,本文經(jīng)過(guò)篩選歸納出供應(yīng)鏈融資業(yè)務(wù)中整個(gè)融資過(guò)程中的28個(gè)信用風(fēng)險(xiǎn)影響因子并進(jìn)行了相關(guān)性分析及鑒別力檢驗(yàn),建立起具有很好穩(wěn)定性與一致性的供應(yīng)鏈融資信用風(fēng)險(xiǎn)指標(biāo)體系。對(duì)供應(yīng)鏈融資業(yè)務(wù)信用風(fēng)險(xiǎn)狀況科學(xué)、準(zhǔn)確地評(píng)價(jià)是本文所要研究的核心問(wèn)題,文章在具體分析用BP神經(jīng)網(wǎng)絡(luò)評(píng)估供應(yīng)鏈融資信用風(fēng)險(xiǎn)具有的優(yōu)勢(shì)的基礎(chǔ)上,根據(jù)MATLAB軟件平臺(tái)上BP神經(jīng)網(wǎng)絡(luò)模塊的構(gòu)建要求,確定包括傳遞函數(shù)、訓(xùn)練算法等在內(nèi)的網(wǎng)絡(luò)初始參數(shù),從而構(gòu)建了供應(yīng)鏈融資信用風(fēng)險(xiǎn)評(píng)價(jià)仿真模型。在此基礎(chǔ)上,通過(guò)運(yùn)用查詢公開數(shù)據(jù)及調(diào)查問(wèn)卷相結(jié)合的方法采集到十三組供應(yīng)鏈融資信用風(fēng)險(xiǎn)樣本并對(duì)其進(jìn)行歸一化處理。根據(jù)研究的需要,本文隨機(jī)選取其中的十組樣本數(shù)據(jù)作為訓(xùn)練樣本,把剩余三組數(shù)據(jù)作為檢驗(yàn)樣本。最后通過(guò)訓(xùn)練樣本與神經(jīng)網(wǎng)絡(luò)工具箱在MATLAB7.0平臺(tái)上對(duì)供應(yīng)鏈融資信用風(fēng)險(xiǎn)評(píng)價(jià)模型進(jìn)行仿真,并通過(guò)檢驗(yàn)樣本來(lái)檢驗(yàn)該模型的有效性。 本文在構(gòu)建商業(yè)銀行供應(yīng)鏈融資信用風(fēng)險(xiǎn)評(píng)價(jià)指標(biāo)體系的基礎(chǔ)上,基于BP神經(jīng)網(wǎng)絡(luò)結(jié)合該體系建立起具有良好風(fēng)險(xiǎn)評(píng)估能力的供應(yīng)鏈融資信用風(fēng)險(xiǎn)評(píng)價(jià)模型,且對(duì)所建立的模型進(jìn)行比較充分的實(shí)證分析驗(yàn)證,相信該模型的不斷完善及應(yīng)用能為商業(yè)銀行降低供應(yīng)鏈融資業(yè)務(wù)信用風(fēng)險(xiǎn)提供借鑒,具有很強(qiáng)的現(xiàn)實(shí)意義。
[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.
【學(xué)位授予單位】：浙江工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.2;F224

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本文編號(hào)：2337728