商业银行信用风险管理模型探究——基于BP-Adaboost强分类器的分析  

The Study of the Commercial Bank Credit Risk Model: Based on BP-Adaboost strong classifier

作　　者：程冬民[1] 彭雷[2] 

机构地区：[1]山东财经大学马克思主义学院,山东济南250014 [2]山东临朐中国建设银行,山东临朐262600

出　　处：《山西大学学报（哲学社会科学版）》2013年第4期116-119,共4页Journal of Shanxi University(Philosophy and Social Science Edition)

摘　　要：文章从理论层面阐述了可以应用于商业银行信用风险管理的BP-Adaboost强分类器信用风险管理模型,并以2012年350家上市公司的财务数据为样本基础,考察了该系统应用于商业银行信用风险管理的可行性,并比较了该模型与原有的BP神经网络系统的优劣。最后对该系统在商业银行的应用前景进行了分析评价。From the theoretical plane,this paper expounds the credit risk model of BP-Adabooxt strong classifier which can be applied to the credit risk management of commercial banks and on the basis of financial data of 350 listed companies in 2012 it not only examines the feasibility of applying this system to the credit risk management of commercial banks,but also compares the strength and weakness of the model with that of original BP network.In the end,the paper makes an analytical assessment on the application prospect of this system in the commercial banks.

关 键 词：BP-Adaboost强分类器 信用风险模型 主成分分析 

分 类 号：F830.33[经济管理—金融学]