本文選題：網(wǎng)絡(luò)借貸 + 信用風(fēng)險(xiǎn)��； 參考：《哈爾濱商業(yè)大學(xué)》2017年碩士論文

【摘要】：當(dāng)前傳統(tǒng)銀行業(yè)貸款發(fā)放的標(biāo)準(zhǔn)和要求越來越嚴(yán)格和苛刻,中、小微企業(yè)和普通老百姓想要獲得銀行發(fā)放的貸款也越來越困難。在此背景下,作為一種互聯(lián)網(wǎng)金融模式的代表,同時(shí)又是一種新型民間借貸方式的網(wǎng)絡(luò)借貸應(yīng)運(yùn)而生。網(wǎng)絡(luò)借貸具有快速、高效、門檻低等傳統(tǒng)金融無法比擬的優(yōu)勢(shì),正在以驚人的速度在全國(guó)范圍內(nèi)不斷發(fā)展壯大。然而其火爆的外表下卻隱藏了巨大的風(fēng)險(xiǎn)和危機(jī)。平臺(tái)倒閉、跑路、借款人不履約還款等問題頻發(fā),給投資者造成了極大的損失。網(wǎng)絡(luò)借貸的信用風(fēng)險(xiǎn)問題引起了全社會(huì)的重視。深入研究網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)的形成原因,并據(jù)此制定出有效的信用風(fēng)險(xiǎn)防范措施,已經(jīng)成為了保障網(wǎng)絡(luò)借貸健康發(fā)展的首要任務(wù)。文章在前人科研成果的基礎(chǔ)上,結(jié)合當(dāng)前我國(guó)網(wǎng)絡(luò)借貸行業(yè)的現(xiàn)狀,運(yùn)用信息不對(duì)稱理論、信貸配給理論和委托代理理論等理論和方法,首先分析我國(guó)網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)的表現(xiàn)和來源。其表現(xiàn)包括網(wǎng)絡(luò)借貸不良貸款率高、違約行為涉及投資人多、涉及金額大、網(wǎng)絡(luò)借貸平臺(tái)倒閉事件頻發(fā)以及網(wǎng)絡(luò)借貸經(jīng)營(yíng)者跑路現(xiàn)象嚴(yán)重等;而其來源主要包括來自借款人的信用風(fēng)險(xiǎn)、來自平臺(tái)的信用風(fēng)險(xiǎn)以及來自擔(dān)保機(jī)構(gòu)的信用風(fēng)險(xiǎn)等三大類別。同時(shí)文章運(yùn)用博弈論來分析借款人和貸款人的決策過程,并得出結(jié)論:信息不對(duì)稱增加了網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn);目前我國(guó)信用體系不夠完善,借款人得不到履約激勵(lì),需要加大對(duì)于借款人違約的懲罰;平臺(tái)的貸款利率越低,債務(wù)人違約的可能性就越小,需要找出科學(xué)的網(wǎng)絡(luò)借貸利率的測(cè)算方法。接下來運(yùn)用Logistic回歸模型進(jìn)一步分析網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)的成因,得出的結(jié)論基本印證了博弈論的分析結(jié)果,并且證明了平臺(tái)對(duì)借款人的信用評(píng)級(jí)結(jié)果不準(zhǔn)確也是導(dǎo)致網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)較高的成因。文章總結(jié)概括了當(dāng)前我國(guó)網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)的防范措施及其缺陷,最后結(jié)合網(wǎng)絡(luò)借貸信用風(fēng)險(xiǎn)的成因,提出了相應(yīng)的信用風(fēng)險(xiǎn)防范措施和建議:首先要加快完善征信體系;其次提高網(wǎng)絡(luò)借貸借款人的違約成本;制定合理的網(wǎng)絡(luò)借貸借款利率;加快落實(shí)和完善客戶資金保護(hù)制度;同時(shí)平臺(tái)要健全內(nèi)部控制體系,提高投資者的風(fēng)險(xiǎn)防范意識(shí);最后要充分發(fā)揮行業(yè)自律組織的作用。本文希望能夠?yàn)橛嘘P(guān)部門完善信用風(fēng)險(xiǎn)防范措施、加強(qiáng)行業(yè)信用風(fēng)險(xiǎn)管理,促進(jìn)行業(yè)規(guī)范、健康發(fā)展等提供參考。
[Abstract]:At present, the standards and requirements of the traditional banking lending are becoming more and more stringent and demanding. In the case of small and micro enterprises and ordinary people, it is becoming more and more difficult to get the loans issued by the bank. In this context, as a representative of the Internet financial model and a new type of private lending, the network has emerged as the times require. Lending has the advantages of fast, high efficiency and low threshold, which is unparalleled in traditional finance. It is growing at an amazing speed throughout the country. However, the huge risks and crises are hidden under its hot appearance. The problems of the failure of the platform, the running road, the borrower's non performance and repayment are frequent, causing great losses to the investors. The credit risk of collateral loan has aroused the attention of the whole society. It has become the primary task to ensure the healthy development of network lending by studying the causes of the formation of the credit risk of Internet lending and making effective measures for the prevention of credit risk. The present situation, using information asymmetry theory, credit rationing theory and principal-agent theory and other theories and methods, first analyzes the performance and source of the credit risk of Internet lending in China. Its performance includes the high rate of non-performing loan, many investors, large amount of gold, frequent failures of the network lending platform and the network. There are three major sources of credit risk from borrowers, credit risk from the platform and credit risk from guarantee institutions. At the same time, the article uses game theory to analyze the decision-making process of borrowers and lenders, and draws a conclusion that information asymmetry increases network lending. Credit risk; at present, the credit system of our country is not perfect enough, the borrower can't get the incentive of the performance, and need to increase the penalty for the borrower's default; the lower the interest rate of the platform, the less the possibility of the debtor's default, we need to find a scientific method to calculate the interest rate of the network loan. Then the Logistic regression model is used to further analyze the net. The cause of the credit risk of collateral loan is basically confirmed by the conclusion of the analysis of game theory, and proves that the inaccurate result of the credit rating of the borrower is also the cause of the higher credit risk of the network lending. On the basis of the causes of the credit risk of network lending, the corresponding precautionary measures and suggestions are put forward: first of all, we should speed up the improvement of the credit system; secondly, improve the default cost of the borrowers on the Internet; establish a reasonable interest rate of the network loan; speed up the implementation and improvement of the system of customer fund protection; at the same time, the platform should improve the internal control system. In the end, we should give full play to the role of the self-discipline organization of the industry. This article hopes to provide some reference for the relevant departments to improve the credit risk prevention measures, strengthen the management of credit risk in the industry, promote the industry standard and healthy development, etc.
【學(xué)位授予單位】：哈爾濱商業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F724.6;F832.4

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