Personal Credit Rating Using Artificial Intelligence Technology for the National Student Loans
National student loans have the general features of commercial loans, and are a financial credit services provided by commercial banks. But the general personal credit rating assessment system of commercial bank can not make the correct credit rating because the lender, college students, have no credit history. To avoid the credit risk, a rational credit assessment system must to be established for college Students. With the self-learning, self-organizing, adaptive and nonlinear dynamic handling characteristics of Artificial Neural Network, a Back Propagatio neural network was developed to evaluate the credit rating about a college student. Several samples, which were provided by a bank, were 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 students personal credit situation.
National Student Loans credit rating Artificial Intelligence Back Propagatio neural network
Jian HU
School of Electrical and Electronic Engineering Shandong University of Technology Zibo, China
国际会议
第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)
南京
英文
103-106
2009-07-25（万方平台首次上网日期，不代表论文的发表时间）