Personal Credit Rating Assessment for the National Student Loans based on Artificial Neural Network

被引:2
|
作者
Zhang, Xiao Jie [1 ]
Hu, Jian [2 ]
机构
[1] Shandong Univ Technol, Sch Econ, Zibo, Peoples R China
[2] Shandong Univ Technol, Sch Elect & Elect Engn, Zibo, Peoples R China
关键词
National Student Loans; credit rating; college student; BP neural network; assessment system;
D O I
10.1109/BIFE.2009.22
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
National Student Loans are the use of the financial means to improve the college subsidy policy. State Student Loan is a personal credit loan, but the personal credit assessment system of commercial banks could not make a correct assessment for a college Student's credit rating because the students have no records about their credit. To avoid the credit risk,it must to establish a rational credit assessment system for college Students. Artificial neural network can simulate, to some extent, how neural network in human brain deals with, searches and stores information. With its self-learning, self-organizing, adaptive and nonlinear dynamic handling characteristics, a Back Propagatio neural network was developed to evaluate the credit rating about a college student. 16 samples was used for network training and testing by MATLAB. The maximum value of the error between the prediction value of the network and actual value is only 2.92%. Simulation results demonstrate that the algorithm developed is fairly efficient for the assessment about the college student's personal credit situation.
引用
收藏
页码:53 / 56
页数:4
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