This paper investigates the determinants of loan repayment default among Small and Medium Agro-Food Enterprises (SMEs) in Lebanon. Data used in this study was retrieved from KAFALAT S.A.L. a Lebanese financial institution that assists SMEs to access bank financing by providing loan guarantees. The study employ the Logistic Regression model to investigate factors that influence borrower’s loan repayment default. The results showed that loan period, regions, legal structure and guarantee program affect significantly the likelihood of loan repayment default. Longer repayment periods are more likely to increase loan repayment default for all five sectors examined. However, guaranteed loans under the “Basic guarantee program (75percent)” are less likely to default than other programs. These results lay the foundation for a credit-scoring model, which could decrease KAFALAT’s underwriting costs while maintaining their social mission. Credit scoring models help financial institutions quantify their risks, which often allows them to extend more credit in the small to medium Agro-food business community.
Description:
Thesis. M.S. American University of Beirut. Department of Agriculture, 2016. ST:6458
Advisor : Dr. Ali Chalak, Assistant Professor, Department of Agriculture ; Members of Committee : Dr. Jad Chaaban, Associate Professor, Department of Agriculture ; Dr. Samer Khalil, Convenor and Associate Professor, Olayan School of Business.
Includes bibliographical references (leaves 56-59)
