Enterprise Credit Guarantee Program Risk Assessment: Based on BP-ANN Evaluation Model

Abstract

We evaluated the projects risk by using the Back Propagation neural network model, then set up the risk evaluation indexes of enterprise credit guarantee projects. The training samples, verification samples and testing samples that the model needed were generated by the randomly get arms method in the range of single-index evaluation standard. The case study indicates that the methodology for generating samples and the process for establishing BP-ANN model are effective and reliable. The phenomenon of over-training and over fitting can be effectively escaped, the model possesses good generalization. Comparing to the methodology of Fuzzy theory, the influence by personal factors can be escaped.