台灣產業結構以中小企業的為主，根據《2021年中小企業白皮書》資料，資本額１億以下或雇用人數未滿200人為中小企業，2020年中小企業約154萬家，佔全體企業約98.93%，就業人數達931萬人，佔總就業人口80.94%，由此可知中小企業為台灣經濟發展的基礎；中小企業財務報表以少繳稅為原則，常見有營收短開、資產未入帳、財務資訊不透明等現象，而銀行不輕易借款給財務不透明的中小企業，而且中小企業交易條件相對於大型企業弱勢，收款期長，付款期短，導致營運週轉金缺口，此時融資租賃公司提供一種更適合中小企業的融資管道。
相較於銀行通常只接受不動產擔保融資，融資租賃公司可以融物方式進行融資，可以接受的動產如機器設備、航空器、船舶、車輛、甚至不動產次順位抵押，針對借款人的風險程度與抵押品的價值，以差異條件提供融資方案，可以為中小企業提供銀行無法補足的資金缺口，融資租賃公司的融資方式多元且彈性，收取利率也較銀行高，面臨借款人違約風險也更大，故需透過控管風險才能確保授信之獲利。
本研究對象為租賃公司2018年~2022年間已往來270筆客戶，其中210筆正常客戶、60筆違約客戶，以下列方法進行研究(1)卡方檢定及T檢定進行各項授信評量因子與違約戶是否存在顯著差異、(2)生存分析法預測借款人發生違約時點(3)羅吉斯Logistic迴歸模型進行違約戶與授信評量因子之預測與關聯性分析。
研究分析中小企業各項授信評量因子與違約的關聯性，並預測借款人發生違約時點，可幫助租賃公司評估借款人條件，調整利息、還款期數與強化抵押品，確保回收資金與獲利之重要參考

Taiwan's industrial structure is dominated by small and medium-sized enterprises (SMEs). According to the "2021 SMEs White Paper ", SMEs are considered to have a capital of less than 100 million or employ less than 200 people. In 2020, the amount of SMEs were about 1.54 million, accounting for about 98.93% of all enterprises. , the number of employed people reached 9.31 million, accounting for 80.94% of the total employed population, therefore SMEs are the foundation of Taiwan's economic development; the financial statements of SMEs are based on the principle of paying less tax, and it is common to have short revenue, unaccounted assets, and financial statements are not transparent. and banks do not easily lend to SMEs with window dressing, and the trading conditions of SMEs are weaker than large enterprises, the collection period is long, and the payment period is short, resulting in a gap in operating working capital. At this time, financial leasing companies provide a more Financing channels for SMEs.
Compared with banks that usually only accept real estate secured, leasing companies can acceptable movable properties such as machinery and equipment, aircraft, ships, vehicles, and even real estate mortgages in the second order are based on the borrower's risk level and collateral. leasing companies provide financing solutions with different conditions, which can provide SMEs with funding gaps that cannot be filled by banks. The financing methods of leasing companies are diversified and flexible, and the interest rates charged are higher than banks. Only control risk can ensure the profit of credit
The sample of this study is the leasing company's 270 customers from 2018 to 2022, including 210 normal customers and 60 default customers. The following methods are used (1) Chi-square test and T test to evaluate the relationship between various credit assessment and default, (3) Logistic regression model to predict and correlate between defaulters and credit evaluation factors, (2) Survival analysis to predict the time of borrower default.
This study analyzes the correlation between various credit assessment factors and defaults of SMEs, and predicts the time when the borrower defaults, which can help leasing companies evaluate borrower conditions, adjust interest, repayment period and strengthen collateral, so as to ensure that the recovery of funds and an important reference for profit.

目錄
國立中山大學研究生學位論文審定書 i
摘要 ii
Abstract iii
圖次 vii
表次 viii
第一章 緒論1
第一節 研究背景1
第二節 研究動機2
第三節 研究目的:3
第四節 研究流程與方法:4
第二章 租賃業務5
第一節 放款市場5
第二節 租賃公司6
第三節 租賃往來方式:10
第四節 案件審查的授信五大重點:14
第三章 文獻探討18
第一節 中小企業:18
第二節 授信原則19
第三節 財務指標:21
第四節 信用風險模型:22
第四章 研究方法24
第一節 研究對象：24
第二節 研究方法:32
第五章 結論與未來展望51
參考文獻53
附錄 56

參考文獻
1. 沈君玲. (2018). 銀行授信適用經營判斷法則之探究. 法令月刊, 69(5), 94-112.
2. 林祝英, & 詹博翔. (2016). 銀行對中小企業授信評估因子與授信風險關係之探討. 科際整合管理研討會, 150-167.
3. 柯志騰. (2008). 商業銀行對中小企業授信評估因素與品質關係之個案研究 亞洲大學]. 台中市. https://hdl.handle.net/11296/bgu64s
4. 高裕豐. (2013). 銀行對中小企業授信決策與授信風險關聯性之研究.
5. 蔡鏞斌. (2000). 中小企業及其評估指標架構之設計 國立臺灣大學]. 台北市. https://hdl.handle.net/11296/99nv9a
6. 鄭定洲, & 林政憲. (2010). 銀行信貸的企業風險因子分析評價研究. Journal of China Institute of, 42.
7. 簡國安. (2010). 信用資產組合之集中度, 風險貢獻與壓力測試逆境值實證研究.
8. Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The journal of finance, 23(4), 589-609.
9. Barber, B. M., & Lyon, J. D. (1997). Detecting long-run abnormal stock returns: The empirical power and specification of test statistics. Journal of financial economics, 43(3), 341-372.
10. Berg, J., Furrer, M., Harmon, E., Rani, U., & Silberman, M. S. (2018). Digital labour platforms and the future of work. Towards decent work in the online world. Rapport de l’OIT.
11. Berger, A. N., & Udell, G. F. (1995). Relationship lending and lines of credit in small firm finance. Journal of business, 351-381.
12. Brigham, E. F. (2016). Financial management: Theory and practice. Cengage Learning Canada Inc.
13. Chatterjee, S., Corbae, D., Nakajima, M., & Ríos‐Rull, J. V. (2007). A quantitative theory of unsecured consumer credit with risk of default. Econometrica, 75(6), 1525-1589.
14. Chen, K. H., & Shimerda, T. A. (1981). An empirical analysis of useful financial ratios. Financial management, 51-60.
15. Crook, J. N., Edelman, D. B., & Thomas, L. C. (2007). Recent developments in consumer credit risk assessment. European Journal of Operational Research, 183(3), 1447-1465.
16. Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of business finance & Accounting, 30(3‐4), 573-588.
17. Dong, H. P., & Su, J.-t. (2010). The relationship between working capital management and profitability: a Vietnam case. International research journal of finance and economics, 49(1), 59-67.
18. Fidrmuc, J., Hainz, C., & Malesich, A. (2007). Default Rates in the Loan Market for SMEs.
19. Focarelli, D., Pozzolo, A. F., & Casolaro, L. (2008). The pricing effect of certification on syndicated loans. Journal of Monetary Economics, 55(2), 335-349.
20. Frank, M. Z., & Goyal, V. K. (2009). Capital structure decisions: which factors are reliably important? Financial management, 38(1), 1-37.
21. Gitman, L. J., Juchau, R., & Flanagan, J. (2015). Principles of managerial finance. Pearson Higher Education AU.
22. Khandani, A. E., Kim, A. J., & Lo, A. W. (2010). Consumer credit-risk models via machine-learning algorithms. Journal of Banking & Finance, 34(11), 2767-2787.
23. Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of finance, 29(2), 449-470.
24. Morgan, J. (1997). Creditmetrics-technical document. JP Morgan, New York, 1, 102-127.
25. Ortiz-Molina, H., & Penas, M. F. (2008). Lending to small businesses: The role of loan maturity in addressing information problems. Small Business Economics, 30, 361-383.
26. Petersen, M. A., & Rajan, R. G. (1997). Trade credit: theories and evidence. The review of financial studies, 10(3), 661-691.
27. Petty, J. W., & Bygrave, W. D. (1993). What does finance have to say to the entrepreneur? Journal of Small Business Finance, 2(2), 125-137.
28. Agarwal, S., & Hauswald, R. (2010). Distance and private information in lending. The review of financial studies, 23(7), 2757-2788.
29. Degryse, H., & Van Cayseele, P. (2000). Relationship lending within a bank-based system: Evidence from European small business data. Journal of financial Intermediation, 9(1), 90-109.
30. Jimenez, G., Salas, V., & Saurina, J. (2006). Determinants of collateral. Journal of financial economics, 81(2), 255-281.
31. 中租迪和2021財報(https://doc.twse.com.tw/server-jav57sb01?co_id=5871&colorchg=1&kind=F&step=9&filename=2021_5871_20220520F04.pdf)
32. 台北市租賃公會網站(http://tpeleasing.com/)
33. 中華民國銀行商業同業公會全國聯合會http://www.ba.org.tw/
34. 金融監督管理委員會銀行局http://www.banking.gov.tw/ch/index.jsp
35. 台灣證券交易所公開資訊觀測站http://mops.twse.com.tw/mops/web/index
36. 中小企業白皮書 - 經濟部中小企業處 (moeasmea.gov.tw)
37. 金融監督管理委員會http://www.fsc.gov.tw/ch/index.jsp