本文在探討新冠肺炎(COVID-19)期間，融資租賃產業延滯率的影響因子。實證2017年到2022年間，在個案租賃公司融資的中小企業財務結構、貨幣政策及總經數據與延滯率的關係。以各項敘述統計資料、差異性t檢定及多元迴歸等方法分析後，得到疫情期間，延滯率確實得到顯著改善的結論。但延滯率似乎與貸款企業本身的財務結構沒有顯著關係。而是與政府的貨幣政策與整體經濟環境有關。可能的原因是，中小企業的財報揭露較具彈性，再者，受限觀察值的數量，亦無法依照產業別個別分析，以致有些影響因此被互相抵消了。
因為租賃業的資金來自銀行、票券，故成本相對高昂。拆借成本與放款利率間的利差被視為衡量貸款剩餘風險的指標，並以此作為監控及貸款風險的補償。疫情期間，寬鬆的貨幣及銀行授信的緊縮產生的外溢效果使租賃業得到財務體質較佳的客戶。實證顯示，個案租賃公司的延滯率明顯降低，利差也微幅縮小。而利差及延滯率的雙降，似乎可以合理解釋為授信品質的提高。以Tang (2019) 實證出，若銀行與非銀之間為互補關係，則移轉至非銀行的授信品質會提高的結論而言，租賃產業與銀行之間似乎存在著互補的關係。但不論關係為何，銀租之間確有合作的必要，運用彼此不同的監管技術才能獲得銀行、租賃及社會三贏的結果。

This thesis explores the factors influencing the delinquency rate in the leasing industry during the COVID-19 period. Empirical analysis was conducted on the relationship between the financial structure of small and medium-sized enterprises (SMEs) receiving financing from leasing companies, monetary policy, macroeconomic data, and delinquency rates from 2017 to 2022. Descriptive statistics, t-tests, and multiple regressions were employed to analyse the data, leading to the conclusion that the delinquency rate improved significantly during the pandemic. However, the delinquency rate appears to have no significant relationship with the financial structure of the borrowing companies themselves but rather with government monetary policy and the overall economic environment. Possible reasons for this include the flexibility of financial reporting contents in SMEs and the limited number of observations, which prevented industry-specific analysis and resulted in certain influence factors being mutually offset.
As the leasing industry relies on funds from banks and bills, the cost is relatively high. The spread between borrowing costs and lending rates is considered an indicator of remaining loan risk and serves as a compensation measure for monitoring and loan risks. During the pandemic, the loose monetary policy and tightening of bank credit had a spillover effect, leading to leasing companies attracting clients with better financial conditions. Through proactive monitoring techniques and post-management of repayment, the delinquency rate of the leasing company in question significantly decreased, and the spread also slightly narrowed. The dual decrease in the spread and delinquency rate can be reasonably interpreted as an improvement in credit quality. Based on the empirical findings of Tang (2019), which concluded that if there is a complementary relationship between banks and non-banks, the credit quality of non-banks will improve, it seems that there is a complementary relationship between the leasing industry and banks. Regardless of the nature of this relationship, cooperation between banks and leasing companies is necessary, utilizing different credit monitoring techniques to achieve a win-win result for banks, leasing companies, and society as a whole.

目次	iv
表次	v
圖次	vi
目次
第一章	緒論	1
第一節	金融環境變化與租賃產業沿革	1
第二節	租賃業的法源與管理	8
第三節	研究架構	14
第二章	文獻回顧	15
第一節	銀行機構與非銀行機構融資	15
第二節	影響逾放比的相關因子	18
第三節	代理變數的選取	22
第三章	資料來源及研究方法	23
第一節	租賃公司資料分析	23
第二節	樣本資料來源	26
第三節	變數定義及迴歸模型	26
第四章	實證結果與分析	31
第一節  樣本資料數據	31
第二節  延滯率的決定因子	35
第五章	結論	40
參考文獻：	43
表次
表 1、近十年銀行業與租賃業對中小企業放款金額統計表	5
表 2、相關租賃產業近年來股價表現	7
表 3、世界各國對租賃相關產業之管理	10
表 4、疫情期間相關信用寬鬆措施	11
表 5、疫情期間中央銀行相關信用管制措施	12
表 6、近6年銀行對中小企業融資餘額VS租賃公司融資契約額統計  單位:億元	13
表 7、授信作業的5P及5C原則	19
表 8、2022年租賃市場承作案件-依資本額區分                單位:件;百萬	24
表 9、2022年租賃市場承作案件-依項目別區分                    單位:仟元	24
表 10、歷年租賃市場承作金額                               單位:百萬	25
表 11、2017年至2022年個案租賃公司貸放契約財務結構因子與貨幣政策	32
表 12、疫情前後期個案租賃公司貸放契約財務結構因子與貨幣政策	33
表 13、個案公司授信利率及延滯比率VS銀行平均放款利率及逾放比率	36
表 14、個案租賃公司近六年的延滯狀況	37
表 15、延滯率和公司財務結構及總經數據關連性	38
圖次
圖 1、銀行業、融資租賃業與實質GDP成長率及貨幣供給關係	6
圖 2：銀行端採行的資產型還款模式	20
圖 3：租賃端採行的現金流量型還款模式	20
圖 4、2003年1月到2022年12月向個案融資租賃公司貸放件數	31
圖 5、個案公司授信利率及延滯比率VS銀行平均放款利率及逾放比率 單位:仟元	36

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