基于数据挖掘技术的商业银行个人信用风险评估模型及其应用

发布时间：2018-04-17 00:09

本文选题：信用风险 + 数据挖掘技术　；参考：《南京财经大学》2015年硕士论文

【摘要】：网络金融和虚拟经济的发展给传统银行业务造成冲击和挑战的同时,也给商业提供了前所未有的发展机遇。随着大数据时代的到来,商业银行每天的业务信息数据呈爆炸式增长,不仅给数据的存储工作造成困难,还极大增加了商业银行利用数据的难度。近年来,我国商业银行的个人信贷业务迅猛发展,个人信贷市场的规模和信贷业务的多样性都有着显著的提高。个人信贷业务作为银行盈利来源的同时,也存在不良贷款和坏账损失的情况。如何通过商业银行掌控的数据资源进行个人信用违约评估,降低不良贷款率和坏账损失成为研究热点。个人信用违约评估不仅可以帮助商业银行消除信息不对称和管理上存在的风险,而且能够提高商业银行整体收益。面对海量数据给商业银行信用风险管理工作带来的挑战,数据处理技术的不断更新也给商业银行提供了更好的机遇。本文借助Logistic模型和数据挖掘技术,在充分利用南京市某家城市商业银行近30000例个人信贷业务数据的基础上,对商业银行个人信用违约风险进行评估,并对个人信用违约概率进行预测分析。文章以个人信用违约为研究对象,结合数据挖掘技术并充分利用数据挖掘软件,建立个人信用违约评估模型,并针对商业银行风险管理上存在的薄弱环节提出改进措施。
[Abstract]:The development of network finance and virtual economy not only brings challenges and challenges to traditional banking business, but also provides unprecedented development opportunities for business.With the arrival of big data's era, the business information data of commercial banks are increasing explosively every day, which not only makes it difficult to store the data, but also greatly increases the difficulty for commercial banks to use the data.In recent years, the personal credit business of commercial banks in China has developed rapidly, and the scale of personal credit market and the diversity of credit business have improved significantly.Personal credit business as a source of bank profits, but also bad loans and bad debt losses.How to evaluate personal credit default through the data resources controlled by commercial banks and reduce non-performing loan rate and bad debt loss has become a hot research topic.Personal credit default assessment can not only help commercial banks eliminate information asymmetry and management risks, but also improve the overall income of commercial banks.In the face of the challenges brought by the massive data to the credit risk management of the commercial banks, the continuous updating of the data processing technology also provides a better opportunity for the commercial banks.With the help of Logistic model and data mining technology, this paper evaluates the personal credit default risk of commercial banks on the basis of making full use of nearly 30000 personal credit business data of a city commercial bank in Nanjing.The probability of personal credit default is predicted and analyzed.This paper takes personal credit default as the research object, combines the data mining technology and makes full use of the data mining software, establishes the personal credit default evaluation model, and puts forward the improvement measures in view of the weak link in the commercial bank risk management.
【学位授予单位】：南京财经大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F832.33;TP311.13

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