本文選題：小微貸款　切入點(diǎn)：貸款風(fēng)險評價　出處：《杭州電子科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：中小企業(yè)對我國的經(jīng)濟(jì)發(fā)展具有重要作用，然而由于我國現(xiàn)階段金融市場以及社會信用體系建設(shè)還不完善加之中小企業(yè)經(jīng)營難以監(jiān)管的特點(diǎn)，導(dǎo)致中小企業(yè)普遍存在融資困難的局面，嚴(yán)重限制了中小企業(yè)的發(fā)展。 對于以上問題，本文首先對中小企業(yè)的經(jīng)營特點(diǎn)以及銀行貸款業(yè)務(wù)的流程進(jìn)行了分析，找出影響銀行對中小企業(yè)貸款積極性的主要原因，針對這些影響因素，在基于銀行現(xiàn)有貸款業(yè)務(wù)流程的基礎(chǔ)上，通過簡化小微貸款業(yè)務(wù)流程并將其移植到移動客戶端，來減小銀行在小微貸款中的成本投入和提高客戶經(jīng)理的工作效率。 同時針對中小企業(yè)貸款風(fēng)險難控的問題，本文首先對現(xiàn)有預(yù)測模型建模方法進(jìn)行了研究，根據(jù)不同建模方法的使用環(huán)境，結(jié)合本文評價模型的輸入是以定量數(shù)據(jù)為主，，加之少量定性數(shù)據(jù)的特點(diǎn),選擇采用BP神經(jīng)網(wǎng)絡(luò)來構(gòu)建風(fēng)險評價模型為銀行貸款提供決策支持。然后在分析了小微貸款企業(yè)的經(jīng)營特點(diǎn)、影響小微貸款企業(yè)還款能力主要因素以及某銀行貸款評價指標(biāo)的基礎(chǔ)上，以工業(yè)企業(yè)為例制定了本文評價模型的評價指標(biāo)體系，同時針對BP網(wǎng)絡(luò)具有的局部極小化問題，收斂速度慢等問題，文中又對BP網(wǎng)絡(luò)算法做了部分改進(jìn)，最后通過Matlab對評價模型進(jìn)行了訓(xùn)練及測試，證明該模型具有一定的實(shí)用性。
[Abstract]:Small and medium-sized enterprises play an important role in the economic development of our country. However, due to the imperfect construction of financial market and social credit system in our country at present, it is difficult to supervise the management of small and medium-sized enterprises. As a result, SMEs generally have financing difficulties, which seriously limit the development of SMEs. For the above problems, this paper first analyzes the management characteristics of small and medium-sized enterprises and the process of bank loan business, finds out the main reasons that affect the enthusiasm of banks to SMEs loans, and aims at these factors. Based on the existing loan business process of the bank, we can reduce the cost investment and improve the work efficiency of the account manager by simplifying the micro-loan business process and transplanting it to the mobile client. At the same time, aiming at the problem of difficult to control the loan risk of small and medium-sized enterprises, this paper first studies the existing forecasting model modeling methods, according to the use environment of different modeling methods, combined with the evaluation model of this paper, the input of the model is based on quantitative data. Combined with the characteristics of a small amount of qualitative data, BP neural network is used to build a risk assessment model to provide decision support for bank loans. Then, the management characteristics of small and micro loan enterprises are analyzed. On the basis of the main factors affecting the repayment ability of small and micro loan enterprises and the evaluation index of a certain bank loan, the evaluation index system of the evaluation model is established for industrial enterprises as an example. At the same time, the local minimization problem of BP network is pointed out. In this paper, the BP neural network algorithm is partly improved. Finally, the evaluation model is trained and tested by Matlab, and the model is proved to be practical.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F276.3;F832.4;TP183

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