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A Credit Rating Model in a Fuzzy Inference System Environment

Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, North Iranshahr 233, Tehran 19585/466, Iran
Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, Riggenbachstrasse 16, 4600 Olten, Switzerland
Department of Marketing, West Chester University, 700 South High Street, West Chester, PA 19383, USA
Industrial & Systems Engineering Department, Chung Yuan Christian University, Taoyuan, Taoyuan City 32023, Taiwan
Author to whom correspondence should be addressed.
Algorithms 2019, 12(7), 139;
Received: 21 May 2019 / Revised: 29 June 2019 / Accepted: 30 June 2019 / Published: 9 July 2019
PDF [372 KB, uploaded 11 July 2019]


One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and commercial risks in international trade. The agents assess the buyers based on financial and non-financial indicators to determine whether it is advisable to grant them credit. Because many of these indicators are qualitative and inherently linguistically ambiguous, the agents must make decisions in uncertain environments. Therefore, to make the most accurate decision possible, they often utilize fuzzy inference systems. The purpose of this research was to design a credit rating model in an uncertain environment using the fuzzy inference system (FIS). In this research, we used suitable variables of agency ratings from previous studies and then screened them via the Delphi method. Finally, we created a credit rating model using these variables and FIS including related IF-THEN rules which can be applied in a practical setting. View Full-Text
Keywords: credit rating; export credit agencies; uncertainty environment; fuzzy inference system; Delphi method credit rating; export credit agencies; uncertainty environment; fuzzy inference system; Delphi method

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Karbassi Yazdi, A.; Hanne, T.; Wang, Y.J.; Wee, H.-M. A Credit Rating Model in a Fuzzy Inference System Environment. Algorithms 2019, 12, 139.

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