Chinese area´s macroscopical credit evaluation model based on fuzzy neural network

An excellent evaluating model on credit should evaluate the credit environment impersonally and comprehensively. However, traditional credit evaluation models are only focusing on microcosmic credit, thus yielding the partial evaluation according to which estimators can only know the single evaluated object´s credit situation without mastering the whole risks of credit environment. In order to complement the deficiency of traditional research, a novel area´s macroscopical credit evaluation model basing on fuzzy neural network is constructed and applied to the practice for the first time. In this model, we first design a set of scientific and reasonable evaluating indexes extracted from feature space of macroscopical credit, then basing on these indexes construct a fuzzy neural network (FNN) model on credit evaluation and finally apply it to the practical credit evaluation of some Chinese provinces randomly selected. Applications show our model is both practical and capable. Using this model, authorities can analyse the credit situation of the area and investors can make a wise decision for investment while saving his running cost and the credit investigating cost. Most important of all, this model can help to urge the local governors, enterprises, and even every person to cultivate a good atmosphere of credit culture, thus enhancing the ability of competition and attraction for the areas.