本文選題：供應(yīng)鏈金融　切入點(diǎn)：中小企業(yè)　出處：《廈門大學(xué)》2014年碩士論文

【摘要】：以往商業(yè)銀行對中小企業(yè)信用風(fēng)險(xiǎn)評價(jià)主要是將單個(gè)融資企業(yè)作為主體,關(guān)注融資企業(yè)的財(cái)務(wù)指標(biāo)。而這種風(fēng)險(xiǎn)評估方式忽略了企業(yè)作為供應(yīng)鏈的一環(huán),其信用風(fēng)險(xiǎn)很大程度上依賴于所在供應(yīng)鏈這一關(guān)鍵因素。因此,本文構(gòu)建了基于供應(yīng)鏈金融視角的中小企業(yè)信用風(fēng)險(xiǎn)評估體系,該體系結(jié)合了供應(yīng)鏈上核心企業(yè)的資信狀況以及供應(yīng)鏈關(guān)系情況,并采用基于自適應(yīng)遺傳算法的SVM方法建立信用風(fēng)險(xiǎn)評價(jià)分類模型。實(shí)驗(yàn)對比表明：該信用風(fēng)險(xiǎn)評價(jià)體系以及基于自適應(yīng)遺傳算法的SVM方法有助于提高商業(yè)銀行信用風(fēng)險(xiǎn)評價(jià)能力,并可以緩解中小企業(yè)融資難的現(xiàn)狀。
[Abstract]:In the past, commercial banks used to evaluate the credit risk of small and medium-sized enterprises (SMEs) by taking individual financing enterprises as the main body and paying attention to the financial indicators of financing enterprises.However, the risk assessment method neglects the enterprise as a supply chain, and its credit risk depends on the key factor of the supply chain to a great extent.Therefore, this paper constructs a credit risk assessment system for SMEs based on the perspective of supply chain finance, which combines the credit status of the core enterprises in the supply chain and the supply chain relationship.SVM method based on adaptive genetic algorithm is used to establish credit risk evaluation classification model.The experimental results show that the credit risk evaluation system and the SVM method based on adaptive genetic algorithm can improve the credit risk evaluation ability of commercial banks and alleviate the financing difficulties of SMEs.
【學(xué)位授予單位】：廈門大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F274;TP18;F832.4

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 吳屏;劉宏;劉首龍;;試析線上供應(yīng)鏈金融信用風(fēng)險(xiǎn)——基于BP神經(jīng)網(wǎng)絡(luò)的模型設(shè)計(jì)[J];財(cái)會月刊;2015年23期

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本文編號：1720658