| 摘要: | 本研究以A銀行B分行為探討個案，蒐集2020年至2023年間曾申貸紓困貸款
共134家中小企業資料，利用二元選擇及多元羅吉斯迴歸模型進行分析，探討19個可能因素與貸款違約、延滯繳款及倒帳之關聯性，並將因素分類為兩種特性：貸款特性、企業及其負責人特性，期望能提供銀行徵授信人員在審核紓困授信案件中，可著重觀察相關態樣之參考建議，有助於控管授信風險。
本研究實證結果顯示：首先，貸款特性包含企業申貸央行A、B方案者、寬緩期、貸款金額及貸款期限等與貸款違約有顯著影響。其中，申貸央行A、B方案者，相較申貸央行C方案或其他紓困貸款方案者較不易違約；反之，寬緩期、貸款金額及貸款期限皆與貸款違約呈現正向關係。再者，企業及企業負責人特性包含貸款銀行家數、員工人數、批發零售業及負責人已婚者等亦與貸款違約具相關性。當中貸款銀行家數越多，發生貸款違約情況較高，而員工人數較多、批發零售業及負責人已婚者，違約情況則較低。
本研究進一步分別探討延滯繳款或倒帳因素，實證結果顯示於貸款特性中，
企業申貸央行A、B方案較不易發生延滯繳款，而貸款金額越大及貸款期間越長者，發生延滯機率越高。至於企業及企業負責人特性與延滯繳款則無相關性。最後，貸款倒帳與貸款特性、企業及企業負責人特性均無顯著影響。
綜上所述，紓困貸款非申貸央行A、B方案者、寬緩期越長、貸款金額越大、貸款期限越長、貸款銀行家數越多、員工人數越少、非批發零售業及負責人未婚者，較易發生貸款違約。
而與既往文獻所探討企業貸款逾期(違約)因素分析或紓困貸款態樣分析之
差異，本研究除了著重紓困貸款違約因素分析外，進一步探討與延滯繳款之影響，並從研究結果發現貸款特性中，企業申貸央行A、B方案、貸款金額及貸款期限與貸款違約、延滯皆有顯著影響。;This case study uses branch B of Bank A data on 134 SMEs that applied for relief loans between 2020 and 2023. The analysis employs binary choice and multiple logistic
regression models to investigate the relationship between 19 potential factors and loan default and delinquency (i.e., delayed repayment). These factors are classified into two
categories: loan features and the characteristics of the enterprises and their owners. The aim of this study is to provide valuable suggestions for bank credit officers to observe related patterns when reviewing relief credit cases, and thus aiding in future credit risk control.
The empirical results of this study are as follows:
1. Loan Features: Significant factors affecting loan default include whether the enterprise applied for the Central Bank′s Scheme A or B loans, the grace period, total loan amount, and loan term. Where enterprises applying for Scheme A or B are less likely to default; in contrast, a longer grace period, larger loan amount, and longer loan term are positively related to loan default.
2. Enterprise and Business Owner Characteristics: Significant factors include the number of banks from which the enterprise has borrowed, number of employees, they are in wholesale and retail industry, and whether the owner is married. In details, a higher number of borrowing banks is associated with a higher likelihood of default, while a greater number of employees, operating in wholesale or retail industry, and having a married business owner are associated with a lower likelihood of default.
Further analysis on delayed repayment or bankruptcy indicates the following. First, for loan features, enterprises applying for Scheme A or B are less likely to experience delayed repayment. Conversely, borrowing larger loan amounts and longer loan terms increase the likelihood of delayed repayment for enterprises. Secondly, there is no
significant relationship between enterprise and business owner characteristics and delayed repayment. Lastly, neither loan features nor enterprise and owner characteristics significantly affect the possibility that firms go bankrupt.
In conclusion, this study not only focuses on the analysis of factors affecting relief loan default but also extends to the impact on delayed repayment. The findings reveal
that within loan features, the application for Scheme A or B, loan amount, and loan term significantly influence both loan default and delayed repayment. |
