EconPapers    
Economics at your fingertips  
 

Design dynamic credit risk model with fuzzy rules for auto dealers

Ying Zhou

International Journal of Business Forecasting and Marketing Intelligence, 2017, vol. 3, issue 3, 248-258

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. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=85364 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbfmi:v:3:y:2017:i:3:p:248-258

Access Statistics for this article

More articles in International Journal of Business Forecasting and Marketing Intelligence from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijbfmi:v:3:y:2017:i:3:p:248-258