DocumentCode
3040014
Title
Personal Credit Rating Assessment for the National Student Loans Based on Artificial Neural Network
Author
Zhang, Xiaojie ; Hu, Jian
Author_Institution
Sch. of Econ., Shandong Univ. of Technol., Zibo, China
fYear
2009
fDate
24-26 July 2009
Firstpage
53
Lastpage
56
Abstract
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 Studentpsilas 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 studentpsilas personal credit situation.
Keywords
artificial intelligence; banking; neural nets; MATLAB; adaptive handling characteristics; artificial neural network; back Propagatio neural network; college subsidy policy; commercial banks; financial means; human brain; national student loans; nonlinear dynamic handling characteristics; personal credit rating assessment; self-learning; self-organizing; student credit rating; Artificial intelligence; Artificial neural networks; Biological neural networks; Business; Educational institutions; History; Humans; MATLAB; Mathematical model; Nonlinear dynamical systems; BP neural network; National Student Loans; assessment system; college student; credit rating;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
Conference_Location
Beijing
Print_ISBN
978-0-7695-3705-4
Type
conf
DOI
10.1109/BIFE.2009.22
Filename
5208936
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