Title: Design dynamic credit risk model with fuzzy rules for auto dealers

Authors: Ying Zhou

Addresses: Shanghai Automotive Group Finance Co., Ltd., Shanghai 200041, China

Abstract: Credit risk scoring is one of the risk assessment tools of auto dealers, but it is complicated, which is affected by various variables and factors in different behaviour mechanisms. This paper incorporates the behaviour style of auto dealers in their ability to pay debt in a dynamic system with fuzzy rules for uncertainty. We discuss credit risk assessment of auto dealers by establishing a relevant credit risk evaluation system and present a dynamic fuzzy credit scoring model to forecast the credit risk of auto dealers. Our work focuses on two aspects: 1) we are investigating the credit risk of auto dealers in a dynamic system; 2) fuzzy rules are also integrated into a dynamic system as fuzzy inference system. Simulation results of a dynamic fuzzy credit risk model are presented in five different classes. Numerical results of simulation are analysed, a dynamic trend of management variety, sell rate and credit risk score are also provided.

Keywords: credit risk; dynamic system; neural networks.

DOI: 10.1504/IJBFMI.2017.085364

International Journal of Business Forecasting and Marketing Intelligence, 2017 Vol.3 No.3, pp.248 - 258

Available online: 03 Jul 2017 *

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