本文關(guān)鍵詞：基于數(shù)據(jù)挖掘技術(shù)的商業(yè)銀行個人信用評分模型研究　出處：《湖南大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 數(shù)據(jù)挖掘 個人信用評分 模糊層次分析法

【摘要】：隨著我國經(jīng)濟(jì)的持續(xù)快速發(fā)展和人們收入水平的不斷提高，人們的消費觀念也隨之發(fā)生了巨大的變化，個人信貸消費已經(jīng)成為日常消費中的重要組成部分。因此，建立個人信用等級評估與預(yù)測體系既是我國銀行業(yè)發(fā)展的需要，也是促進(jìn)個人信貸業(yè)務(wù)發(fā)展的有效措施。這就要求我國構(gòu)建個人信用體系，個人信用評分是個人信用體系建設(shè)的關(guān)鍵，通過對個人進(jìn)行科學(xué)的信用評分，可以準(zhǔn)確的了解個人的信用狀況，正確識別個人信用風(fēng)險，節(jié)約交易成本，提高交易效率，促進(jìn)信用資源的優(yōu)化配置。隨著計算機(jī)技術(shù)、數(shù)據(jù)庫技術(shù)的快速發(fā)展和廣泛應(yīng)用，各行業(yè)中積累的數(shù)據(jù)越來越多，金融行業(yè)尤其如此�？茖W(xué)數(shù)據(jù)的大量積累和各種數(shù)據(jù)庫的廣泛使用，人們逐步認(rèn)識到海量數(shù)據(jù)的利用十分困難、效率低下，而且很難從中獲得有價值的指導(dǎo)性意見。在這種情況下，數(shù)據(jù)挖掘技術(shù)應(yīng)運而生。數(shù)據(jù)挖掘是一種新的商業(yè)信息處理技術(shù)，其主要功能是對商業(yè)數(shù)據(jù)庫中的大量業(yè)務(wù)數(shù)據(jù)進(jìn)行抽取、轉(zhuǎn)換、分析和其他模型化處理，從中提取輔助商業(yè)決策的關(guān)鍵性數(shù)據(jù)。 本文將數(shù)據(jù)挖掘技術(shù)運用于商業(yè)銀行的個人信用評分。本文在總結(jié)國內(nèi)外個人信用評分發(fā)展現(xiàn)狀的基礎(chǔ)上，從數(shù)據(jù)挖掘角度對當(dāng)前國內(nèi)商業(yè)銀行成熟的個人信用評分模型進(jìn)行介紹和分析。借助于模糊層次分析法進(jìn)行個人信用評價指標(biāo)體系的建立，有助于綜合考慮個人風(fēng)險、個人信用狀況以及不同指標(biāo)等情況，避免單一指標(biāo)考核所存在的問題，，且操作簡單有助于規(guī)避潛在的信用風(fēng)險。與此同時，針對模糊矩陣中約束條件的缺陷，本文通過引入總體均值檢驗理論對模糊層次分析法進(jìn)行了改進(jìn)。最后重點分析了基于層次分析法的個人信用評分體系，借鑒國內(nèi)外的研究成果構(gòu)建了個人信用評分指標(biāo)體系，并運用模糊層次分析法確定了個人信用評分指標(biāo)體系中各指標(biāo)的權(quán)重，將結(jié)果應(yīng)用于實例。本文的研究從理論上豐富了商業(yè)銀行進(jìn)行個人信用評分的方法，為商業(yè)銀行選擇最合適的數(shù)據(jù)挖掘方法進(jìn)行個人信用評分提供了決策參考，有利于商業(yè)銀行控制經(jīng)營風(fēng)險和提高自身競爭力。
[Abstract]:With China's sustained and rapid economic development and continuous improvement in people's income level, people's consumption concept has also undergone tremendous changes, the personal credit consumption has become an important part in daily consumption. Therefore, to establish the development of personal credit evaluation and prediction system is China's banking industry, but also to promote the effective measures for the development of personal credit business. This requires the construction of China's personal credit system, personal credit scoring is the key to the construction of personal credit system, through scientific credit score for the individual, can accurately understand the personal credit, the correct recognition of personal credit risk, reduce transaction costs, improve transaction efficiency, promote optimal allocation of credit resources. With the development of computer technology, the rapid development and wide application of the database technology, the data accumulated in the industry more and more, especially in the financial industry So it is widely used. The accumulation of scientific data and databases, people gradually realize that the utilization of massive data is very difficult, inefficient, and difficult to obtain guidance value from it. In this case, the data mining technology. Data mining is a new business information processing technology. Its main function is to a large number of commercial databases in the business of data extraction, transformation, analysis and handling of other models, key data extraction from business decisions.
This paper will use data mining technology in the commercial bank personal credit score. Based on summarizing the domestic and foreign development status of credit rating in this paper on the mining perspective on the introduction and analysis of the current domestic commercial banks mature individual credit scoring model from the data. Using fuzzy AHP to establish evaluation index system of personal credit. Contribute to the comprehensive consideration of personal risk, personal credit conditions and different indicators, to avoid the existing single index evaluation of the problem, and the operation is simple and helps to avoid the potential credit risk. At the same time, aiming at the defects of fuzzy constraints in the matrix, through the introduction of the overall mean test theory of fuzzy analytic hierarchy process improved. Finally the article analyses the AHP of personal credit scoring system based on the reference of the research results at home and abroad to build a personal letter With the evaluation index system, and uses fuzzy AHP to determine the weight of each index in the personal credit scoring system, the results can be applied in examples. This study has enriched the theory of commercial bank personal credit scoring methods, choose the most suitable data mining methods for personal credit scoring provides decision-making reference for commercial bank, commercial bank can control the risk and improve their competitiveness.

【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP311.13;F832.4

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