Development of a Hybrid Credit Scoring Model for the Banking System

In developed countries, the existence of credit scoring agencies helps to reduce risk banks across globe by ensuring their good scores through a variety techniques, including use machine learning and artificial intelligence. Nevertheless, banking system in poor developing countries is plagued lack reputable for customers. As result, tend internalize according Basel II & III Central Bank regulations. this study, eight techniques were used rank legal customers an Iranian bank. The optimal probabilistic neural network (PNN) algorithm has been presented we performance comparison between these 8 models illustrate where financial-services fall into category or bad based on different techniques. Because combined technique, system, especially weak can categorize its ones. fact, purpose paper create hybrid approach banks' clients, thus obtaining probability default system.