Loading...
Modeling SMEs Credit Default Risk: The Case of Saudi Arabia
Senan, Nermean Tayachi, Tahar BenSaïda, Ahmed
Senan, Nermean
Tayachi, Tahar
BenSaïda, Ahmed
Citations
Altmetric:
Type
Supervisor
Subject
Date
2022-11
Collections
Files
Research Projects
Organizational Units
Journal Issue
Abstract
This study assesses the credit risk of small and medium-sized enterprises (SMEs) to minimize unexpected risk events. We construct a hybrid statistical model based on factor analysis and logistic regression to predict enterprise default on loans and determine the factors predicting SMEs default. We assess the credit risk of SMEs listed on the Saudi stock market. The results indicate that the SMEs acid-test ratios are the most influential factors in predicting SMEs credit risk. Therefore, the designed logistic model can be used by financial institutions during the decision-making process of granting loans to SMEs. This study sheds light on challenging access to bank credits due to the lack of financial transparency of most Saudi SMEs.