层次分析法和支持向量机在个人信用评估中的应用
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- 英文论文题名：Application of Analytic Hierarchy Process and Support Vector Machine in Personal Credit Evaluation
- 论文作者：许艳秋 ; 潘美芹
- 英文论文作者：XU Yan-qiu ; PAN Mei-qin ; Graduate School ; Shanghai International Studies University ; School of Business Administration ; Shanghai International Studies University
- 年：2016
- 作者机构：上海外国语大学研究生院;上海外国语大学国际工商管理学院;
- 论文关键词：层次分析法 ; 支持向量机 ; 个人信用评估 ; 信用风险
- 英文论文关键词：Analytic Hierarchy Process ; Support Vector Machine ; personal credit evaluation ; Credit Risks
- 会议召开时间：2016-11-12
- 会议录名称：第十八届中国管理科学学术年会论文集
- 英文会议录名称：Proceedings of the 18th Chinese Annual Conference on Management Science
- 语种：中文
- 分类号：F224;F832.4
- 学会代码：ZHYJ
- 会议名称：第十八届中国管理科学学术年会
- 会议地点：中国陕西西安
- 主办单位：中国优选法统筹法与经济数学研究会、西安交通大学、中国科学院科技战略咨询研究院、《中国管理科学》编辑部
- 学会名称：中国优选法统筹法与经济数学研究会
- 页数：7
- 文件大小：1005k
- 原文格式：O
- 会议级别：全国
摘要
信用贷款在国内正蓬勃开展,但由于目前我国的征信系统还不完善,银行因信息不对称不断提高个人信贷的标准,步骤也很繁琐,从而导致信用贷款的受益面不广。针对此现状,本文着力研究个人信用评估指标的定量化,并在评估方法上进行了创新。论文首先选取了合适的评估指标,完成了定性指标的定量化;为刻画评估指标作用的主次性,利用层次分析法计算出指标权重,依权重来处理数据;最后用支持向量机对数据进行分类。实验结果表明,采用层次分析法进行数据预处理大大提高了个人信用评估预测的准确度。
Credit loan is quite popular domestically nowadays.However,since credit reference system in China is still not that mature.Banks begin to raise the standards of personal credit loans.The steps are also very tedious,which causes the narrowness of benefits.Based on the situation,the quantification of indexes of personal credit loans is studied.It also innovates on the evaluation methods in personal credit loans.Firstly,appropriate indexes are chosen and the quantification of the indexes is finished.Secondly,the weight of each index is calcuated via AHP,by which it processes the data.Thirdly,the data is classified by SVM.The results show that using AHP to process the data greatly improves the accuracy of personal credit evaluation.
Credit loan is quite popular domestically nowadays.However,since credit reference system in China is still not that mature.Banks begin to raise the standards of personal credit loans.The steps are also very tedious,which causes the narrowness of benefits.Based on the situation,the quantification of indexes of personal credit loans is studied.It also innovates on the evaluation methods in personal credit loans.Firstly,appropriate indexes are chosen and the quantification of the indexes is finished.Secondly,the weight of each index is calcuated via AHP,by which it processes the data.Thirdly,the data is classified by SVM.The results show that using AHP to process the data greatly improves the accuracy of personal credit evaluation.
引文
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[2]闻红利.C2C电子商务网站信用评价研究[D].杭州:浙江工业大学,2013.
[3]金晶.基于第三方评级机构的我国中小企业信用评级体系研究[D].西安:西安电子科技大学,2008.
[4]吴刚.基于SVM的商业银行对中小企业信用评级研究[D].西安:西安理工大学,2011.
[5]汪晶瑶.信用评估的常用方法简析[J].时代金融,2013,15:228-229.
[6]陈朴.我国商业银行信用风险普股模型研究[D].哈尔滨:哈尔滨工业大学.2012.
[7]汪辉,邓晓梅,杨伟华,等.中小企业信用再担保体系演化稳定条件分析[J].中国管理科学,2016,24(7):1-10
[8]Liang.Han,Greene F.The determinants of online loan applications from small business[J].Journal of Small Business and Enterprise Development,2007,14(3):478-486.
[9]Abdou H A,Pointon J.Credit scoring,statistical techniques and evaluation criteria:A review of the literature[J].Intellect Systems in Accounting Finance&Management,2011.18(2-3):59-88.
[10]李玉娘.基于AHP的我国个人住房贷款信用风险评估研究[D].长沙:湖南大学,2007.
[11]李浦生.网络微小企业贷款信用评价体系研究[D].杭州:浙江大学,2011.
[12]周少飞,王亮.基于AHP层次分析法的中小企业信用评级模型构建[J].征信,2014,32(5):38-42.
[13]张超,朱维娜.基于层次分析法的互联网金融中小企业信用评价体系构建[J].征信,2014,32(10):25-29.
[14]王学东,安楠,崔志恒,等.网商信用指数测度研究——基于改进的AHP法[J].现代情报,2013,33(9):1-6
[15]Lee S H.Ability and willingness to service debt as explanation for commercial and official rescheduling cases[J],Journal of Banking and Finance,1991,15(1):5-27.
[16]李虹.支持向量机在个人信用评估中的应用[D].天津:天津大学,2007.
[17]王润华.基于改进支持向量机的消费信贷中个人信用评估模型[J].统计与决策,2010,11:54-56.
[18]郑丽丽.基于遗传算法和多类支持向量机的信用卡行为评估模型研究[D].杭州:浙江工商大学,2010.
[19]张杰.基于支持向量机的中小企业技术信贷违约预测[J].统计与决策,2013,20:66-69.
[20]刘春航,陈璐.银行集团的风险并表:风险计量及评估方法[J].国际金融研究,2009,2:88-96.
[21]曹文松.基于SVM的银行间同业拆借利率预测方法研究[D].长沙:湖南大学.2010.
[22]陈朝晖、胡玉芬.局域SVM的我国商业银行风险预警研究[J].武汉理工大学学报,2012,34(4):504-508.
[23]陆爱国,王珏,刘红卫.基于改进的SVM学习算法及其在信用评分中的应用[J].系统工程理论与实践,2012,32(3):515-521.
[24]Gumus E,Kilic N,Sertbas A,et al.Evaluation of Face Recognition Techniques Using PCA,Wavelets and SVM[J].Expert Systems with Applications,2010,37(9):6404-6408.
[25]衣柏衡,朱建军,李杰.基于改进SMOTE的小额贷款公司客户信用风险非均衡SVM分类[J].中国管理科学,2016,24(3):24-30.