Optimization of Customers Credit Evaluation for Iran Khodro Leasing Company using the Neural Network Algorithm

Background/Objectives: Although in recent decades the capability of computers in data saving, recovering, office automation and other affairs are undeniable, there are also cases where a person is forced to do them by himself. Methods/Statistical Analysis: This study focuses on the developing a proper model for investigation of credit behavior of the facilities costumers by using a neural network for credit rating. In this way, the model firstly identifies the credit behavior of the costumers and then calculates their creditworthy points. In the next step, the neural network models were tested by experimental data followed by designing and training using training data. Results: The results of fitting and analysis of the data showed that this model could be applied as one of the models for determining the credit ratings of the customers. Thus, since the lending the facilities for purchase of cars are as the main business of the company leasing companies do not desire to refuse receiving mortgage lending, except in special cases. If by the help of rating process, the branch manager determines that a loan will be deferred or fuel, he can cancel the applicant’s lending or requests for more guarantees. Conclusion/Application: Since the lending the facilities for purchase of cars are as the main business of the company leasing companies do not desire to refuse receiving mortgage lending, except in special cases. If by the help of rating process, the branch manager determines that a loan will be deferred or fuel, he can cancel the applicant’s lending or requests for more guarantees.