本文選題：房貸　切入點(diǎn)：信用風(fēng)險(xiǎn)評(píng)估　出處：《哈爾濱理工大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：2008年美國次貸危機(jī)的爆發(fā),使房貸信用風(fēng)險(xiǎn)引起全世界的關(guān)注。根據(jù)巴塞爾委員會(huì)提出的《新巴塞爾資本協(xié)議》的要求,金融市場風(fēng)險(xiǎn)或信用風(fēng)險(xiǎn)等單一風(fēng)險(xiǎn)已經(jīng)不再是影響銀行業(yè)經(jīng)營困難的主要因素,而是多種因素(如：金融市場風(fēng)險(xiǎn)、信用風(fēng)險(xiǎn)、操作風(fēng)險(xiǎn)等)共同作用的結(jié)果。然而我國銀行風(fēng)險(xiǎn)評(píng)估尚處于初級(jí)階段,尤其對(duì)個(gè)人信用風(fēng)險(xiǎn)評(píng)估、管理方面的經(jīng)驗(yàn)和方法都較為缺乏�；诖爽F(xiàn)狀,本文以銀行客戶數(shù)據(jù)為依據(jù)對(duì)個(gè)人信用風(fēng)險(xiǎn)進(jìn)行評(píng)估,為完善銀行監(jiān)管體系具有現(xiàn)實(shí)意義。 本文開篇論述了國內(nèi)外信用風(fēng)險(xiǎn)評(píng)估的研究現(xiàn)狀以及研究成果,簡單介紹了決策樹算法和房貸信用風(fēng)險(xiǎn),在分析房貸信用風(fēng)險(xiǎn)評(píng)估現(xiàn)狀的基礎(chǔ)上,進(jìn)一步分析了房貸信用風(fēng)險(xiǎn)評(píng)估中存在的問題。對(duì)影響房貸信用風(fēng)險(xiǎn)評(píng)估的因素進(jìn)行了分析,并設(shè)計(jì)出相應(yīng)的評(píng)估指標(biāo),給出評(píng)估指標(biāo)篩選的具體步驟,最終確定影響比較大的十個(gè)指標(biāo)。緊接著通過對(duì)房貸信用風(fēng)險(xiǎn)評(píng)估方法的比較分析,選擇了決策樹算法來對(duì)房貸的信用風(fēng)險(xiǎn)進(jìn)行評(píng)估,闡述了決策樹算法所依托的原理和評(píng)估模型。根據(jù)以上對(duì)評(píng)估指標(biāo)的設(shè)計(jì)以及評(píng)估方法的選擇,選取了A銀行為研究對(duì)象,對(duì)其房貸信用風(fēng)險(xiǎn)進(jìn)行了評(píng)估,并根據(jù)評(píng)估結(jié)果提出了降低A銀行房貸信用風(fēng)險(xiǎn)的策略。 本文所采用的決策樹算法能夠準(zhǔn)確的評(píng)估出房貸客戶的信用等級(jí),既適用于銀行對(duì)老客戶信用的跟蹤評(píng)估,也適用于對(duì)新客戶信用等級(jí)的預(yù)測,其評(píng)估結(jié)果可以成為銀行為客戶提供貸款的決策依據(jù),能夠?yàn)榻档豌y行的房貸信用風(fēng)險(xiǎn)發(fā)揮巨大作用,保障銀行業(yè)健康平穩(wěn)的發(fā)展。
[Abstract]:In 2008, with the outbreak of the subprime mortgage crisis in the United States, the mortgage credit risk attracted worldwide attention. According to the request of the Basel Committee of the New Basel Capital Accord, The single risk, such as financial market risk or credit risk, is no longer the main factor that affects the banking management difficulty, but a variety of factors (such as: financial market risk, credit risk, etc.). However, the bank risk assessment in China is still in the initial stage, especially for the personal credit risk assessment, management experience and methods are relatively lacking. Based on bank customer data, this paper evaluates personal credit risk, which has practical significance for perfecting bank supervision system. At the beginning of this paper, the research status and achievements of credit risk assessment at home and abroad are discussed, and the decision tree algorithm and mortgage credit risk are briefly introduced. On the basis of analyzing the present situation of mortgage credit risk assessment, This paper further analyzes the problems existing in the assessment of mortgage credit risk, analyzes the factors that affect the assessment of mortgage credit risk, designs the corresponding evaluation index, and gives the concrete steps for the screening of the evaluation index. Then, through the comparative analysis of the methods of assessing the credit risk of housing loans, the decision tree algorithm is chosen to evaluate the credit risk of housing loans. This paper expounds the principle and evaluation model of decision tree algorithm. According to the design of evaluation index and the selection of evaluation method, Bank A is selected as the research object, and the credit risk of housing loan is evaluated. According to the evaluation results, the paper puts forward some strategies to reduce the credit risk of A bank. The decision tree algorithm used in this paper can accurately evaluate the credit rating of mortgage customers, which is not only suitable for the bank to track and evaluate the credit of the old customers, but also for the prediction of the credit rating of the new customers. The evaluation results can be used as the basis for banks to provide loans to customers, and can play a great role in reducing the risk of mortgage credit of banks, and ensure the healthy and stable development of banks.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.45;F224

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