Modeling SMEs Credit Default Risk: The Case of Saudi Arabia

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.

Impact of FinTech Growth on Bank Performance in GCC Region

“…This article focuses on the financial service industries in the GCC region, more precisely, in the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE), since they represent the leading countries in the region (Senan et al, 2022). Indeed, according to MAGNiTT (2022), the FinTech sector in the GCC in the past few years has witnessed a steady annual growth of 36 percent on average since 2017, where the UAE and the KSA combined contain more than 70 percent of the total FinTech investment in the region in 2021.…”