Analysis of Default Factors of Small and Medium Enterprise-– A Case Study of C Leasing Company

• Main Authors: Tzu-Hao Su, 蘇子豪
• Other Authors: Dr.Chou-Wen Wang
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/unk5z6

碩士 === 國立中山大學 === 財務管理學系研究所 === 107 === Small and medium enterprises (SMEs) develop production and bring about prosperous economy in Taiwan. They''re the main parts of finance and economics of our country. At the meantime, leasing companies play significant roles helping the growing of SMEs, serving as important budget providers to SMEs. Because of business model and usual practice of SMEs, their financial reports can’t reflect actual status. There is severe information asymmetry between SMEs and banks, so it’s very difficult for them to get financial line from banks. Under such circumstances, leasing companies turn into be the critical budget providers. The target markets of leasing companies are SMEs, and serving as important fund providers. But the operational results of SMEs are often influenced by internal and external factors. Therefore it causes leasing companies to take more risk than bank industry. That’s why leasing industry need to analyze the default factors, developing effective prediction model. This study selectd 37 variables to forecast the risk factors whether cause to default, including 13 variables which banks often utilize, and other non-financial 24 variables regarding business operating, characters of operators, case structures and investigating processes. Applied machine learning tool of XGBoost as prediction model . It was found that after training the variables of samples, the tool has the prediction ability indeed. The results revealed the predictive accuracy reaching 87~88%. The default factors and prediction tool of this study could be for reference when leasing companies and banks predict the risk of default.