本文選題：汽車金融公司 + 個人汽車貸款風險　； 參考：《西南大學(xué)》2017年碩士論文

【摘要】：我國現(xiàn)正處于經(jīng)濟高速發(fā)展時期,汽車產(chǎn)業(yè)正是支撐經(jīng)濟增長的重要組成部分。而在整個汽車產(chǎn)業(yè)鏈中,汽車金融業(yè)的利潤占到了近20%。汽車金融公司作為專業(yè)從事該行業(yè)的金融機構(gòu),隨著利潤的增長近幾年內(nèi)相繼成立。中國個人汽車按揭貸款買車量占汽車銷售總量的比例,即貸款滲透率在10年前尚不足5%,目前已經(jīng)達到25%-35%,但距離很多發(fā)達國家70%以上的滲透率相比還有很大的差距。因此,我國汽車金融市場有著巨大的發(fā)展?jié)摿?到2020年中國汽車金融的滲透率將達到50%,市場規(guī)模將達到2萬億元。但與國外成熟汽車金融市場相比,目前國內(nèi)汽車金融市場還很混亂。由于存在信用體系建設(shè)不完善、個人收入信息不透明、地域廣闊、人口流動性較大等客觀原因,以及貸款審核效率不能滿足市場需求、個人信用評級不完善等主觀因素,造成了汽車金融公司違約風險的增加。因此,研究汽車金融公司如何通過個人信用評級來有效地控制違約風險就具有理論和現(xiàn)實意義。本文首先對國內(nèi)外汽車金融的歷史發(fā)展和現(xiàn)狀進行了研究,并對國內(nèi)汽車金融公司當前存在的問題及風險進行了闡述。然后對國內(nèi)某大型汽車金融公司近三年個人汽車貸款客戶的信息和還款記錄進行了分析,研究如何通過建立信用評分模型來有效的對客戶進行風險等級評估,從而提高審核效率和降低違約風險。研究過程中抽取了該公司近3年約25000名客戶的資料,并通過問卷調(diào)查、借鑒行業(yè)先進經(jīng)驗等方式從基礎(chǔ)信息、貸款信息及征信信息等篩選出了對個人汽車貸款風險有顯著影響的8個變量,然后利用其中18592名客戶進行Logistic回歸建立個人信用評分模型,7970個客戶用于驗證個人信用評分模型區(qū)分能力。經(jīng)分析檢驗表明:建立的評分模型的所有變量回歸系數(shù)為負數(shù),WALD檢驗P0.05,模型變量趨勢與實際業(yè)務(wù)含義一致;方差膨脹系數(shù)VIF10,模型不存在多重共線性;K-S值為32.59,GINI系數(shù)為44.82,模型對好壞賬戶有較好的區(qū)分能力。最后根據(jù)評分模型對個人汽車貸款客戶進行信用評級,根據(jù)其評級結(jié)果審核人員對客戶實行差異化的審核,有效地提高了審核效率,還能較好地控制了個人汽車貸款風險。研究過程中還發(fā)現(xiàn),個人數(shù)據(jù)資料的真實性、完整性是保證評分模型可靠的關(guān)鍵。同時,本文還研究提出了提高汽車金融公司風險防范能力的措施和辦法:加強內(nèi)部培訓(xùn),提高審核人員綜合素質(zhì)和業(yè)務(wù)技能;根據(jù)等級評分模型統(tǒng)一審核要求;建立審核人員的資格認證,建立淘汰制度;針對不同評級客戶實行差異化審核政策和建立不同的金融產(chǎn)品;建立完善貸后管理,建立風險共擔的金融風險體制,明確單個客戶風險監(jiān)控主責任人,建立責任人負責制度和重點客戶管理制度。
[Abstract]:China is now in the period of rapid economic development, automobile industry is an important part of supporting economic growth. But in the whole automobile industry chain, the automobile finance industry profit accounted for nearly 20%. As a financial institution specialized in this industry, auto finance company has been established in recent years with the increase of profit. China's personal car mortgage loans as a proportion of total car sales, that is, the loan penetration rate of less than 5% 10 years ago, has now reached 25-35, but there is still a big gap between the penetration rate of more than 70 percent in many developed countries. Therefore, China's auto financial market has great potential for development. By 2020, the penetration rate of China's auto finance will reach 50%, and the market scale will reach 2 trillion yuan. But compared with the foreign mature automobile finance market, the domestic automobile finance market is still very chaotic. Because of the imperfection of credit system construction, the opaque personal income information, the vast area, the large population mobility, and other subjective factors, such as the loan audit efficiency can not meet the market demand, the personal credit rating is not perfect and so on. Caused the auto financing company default risk increase. Therefore, it is of theoretical and practical significance to study how auto financing companies can effectively control default risk through personal credit rating. In this paper, the historical development and present situation of automobile finance at home and abroad are studied, and the existing problems and risks of domestic auto finance companies are expounded. Then it analyzes the information and repayment records of a large auto financing company in China in the past three years, and studies how to effectively evaluate the risk rating of customers by establishing a credit rating model. In order to improve the efficiency of audit and reduce the risk of default. In the course of the research, the data of about 25000 clients of the company in the past three years were extracted, and the basic information was obtained from the basic information by means of questionnaire survey, advanced experience of the industry and so on. The loan information and credit information have screened out 8 variables that have significant influence on the risk of personal automobile loan. Then 18592 of them were used for Logistic regression to establish personal credit rating model, and 7970 customers were used to verify the distinguishing ability of personal credit rating model. The analysis and test show that the regression coefficient of all variables in the established scoring model is negative and WALD test (P0.05), and the trend of the model variable is consistent with the actual business meaning. The coefficient of variance expansion is VIF10, and the K-S value of multiplex collinearity is 32.59 and the coefficient of Gini is 44.82. The model has a good ability to distinguish between good and bad accounts. Finally, according to the rating model, the credit rating of individual car loan customers is carried out. According to the rating results, the auditor carries out the differentiated audit to the customers, which effectively improves the audit efficiency and controls the risk of personal automobile loans. It is also found that the authenticity and integrity of personal data is the key to ensure the reliability of the scoring model. At the same time, this paper also studies and puts forward the measures and methods to improve the risk prevention ability of auto finance companies: strengthening internal training, improving the comprehensive quality and professional skills of auditors, unifying the audit requirements according to the rating model; Establish qualification certification of auditors, establish elimination system; implement differentiated audit policy and establish different financial products for different rating clients; establish and perfect post-loan management, establish a risk-sharing financial risk system, Identify the main responsible person for individual customer risk monitoring, establish the responsible person responsibility system and key customer management system.
【學(xué)位授予單位】：西南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F832.4

【參考文獻】

相關(guān)期刊論文 前10條

1 劉開元;;隨機森林與邏輯回歸模型在違約預(yù)測中的應(yīng)用[J];信息與電腦(理論版);2016年21期

2 阿明翰;張達敏;李偉;;邏輯回歸在信用卡風險評估模型構(gòu)建中的應(yīng)用[J];內(nèi)江科技;2016年09期

3 徐U，

本文編號：1947162