A Credit Rating Model in a Fuzzy Inference System Environment

Yazdi Yazdi,Hanne Hanne,Wang Wang,Wee Wee

doi:10.3390/a12070139

Abstract

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.

Highlights

Due to the strong expansion of international trade, many countries have established export credit agencies (ECAs) to protect exporters from bankruptcy due to political and commercial risks
The results showed that two factors were effective for mapping via fuzzy inference system (FIS)
The results revealed that this model performed better than linear discriminate analysis, logistic regression analysis, and an artificial neural network

Summary

Introduction

Due to the strong expansion of international trade, many countries have established export credit agencies (ECAs) to protect exporters from bankruptcy due to political and commercial risks. Their agents evaluate foreign buyers and determine whether to grant credit to these exporters to protect them from risks. The agents evaluate the buyers based on their countries’ sovereign credit. We use a Fuzzy Inference System (FIS) to evaluate exporters’ credit in an uncertain environment. This study helps them to evaluate the ability of buyers to repay their debt, and to determine the probability of default. There are two types of credit ratings: (1) sovereign credit rating and (2) corporate credit rating

Objectives

Methods

Conclusion