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 propagation 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 student´s personal credit situation.