Modeling the Credit Risk of SMEs : Evidence from Saudi Marke
|Senan, Nermean M.
|Despite the critical role SMEs paly in economic growth and job creation, SMEs access to bank credit is still challenging due to lack of financial transparency of most Saudi SMEs. The difficulties facing SMEs financing can be estimated through credit risk assessment. Good risk assessment can set a strong format of risk pricing to charge suitable loan premiums and make sound decision about issuing loans. There are scientific statistical methods to assess credit risk of enterprises. This study employs the internal factors most affecting a company?s performance to construct logistic regression model using panel data of over 60 Saudi firms (with revenues less than 200 SAR) to assess the credit risk of Saudi SMEs. The data sample includes all Saudi SMEs listed in Saudi main market, Tadawul. Based on the empirical results, the study determines the default predictors (variables) of Saudi SMEs. The developed model suggests that acid-test ratios are most affecting credit default of Saudi SMEs. Lastly, the paper puts recommendations and suggests several future studies.
|Modeling the Credit Risk of SMEs : Evidence from Saudi Marke
|Graduate Studies and Research