影響中小企業貸款提前清償因素之實證分析

The Empirical Analysis of Affecting Factors for the Prepayment of the Small and Medium Enterprises Loans

林筱玲(Hsiao-Ling Lin)

指導教授 ： 王親仁

國立臺中科技大學/商學院/企業管理系事業經營碩士班/碩士(2013年)

https://doi.org/10.6826/NUTC.2013.00028

摘要

本研究以中部某公營銀行於2006年~2011年所承做336件中小企業貸款之授信案件為研究對象，從銀行授信審核及承作條件觀點，參酌銀行授信企業信用評等表及銀行往來狀況，選取20個變數分析影響中小企業貸款提前清償之關鍵因素，以提供銀行於承作中小企業貸款業務及擬定授信策略與風險的控管之參考，以避免資源成本的浪費，更期望能對銀行實質的收益及整體的經營績效有所助益。
透過卡方檢定與羅吉斯迴歸模式，分析影響中小企業貸款案件提前清償相關因素與發生機率之差異性。實證結果發現產品市場性、稅後淨利率、存貨週轉次數、應收帳款週轉率及貸款利率等變數，對於中小企業貸款案件提前清償因素有顯著影響，其中產品市場性、稅後淨利率、存貨週轉次數與貸款利率對中小企業貸款案件提前清償有顯著正向影響，而應收帳款週轉率對中小企業貸款案件提前清償則有顯著負向影響。
應用混淆矩陣預測，對未提前清償戶、提前清償戶及整體中小企業貸款案件之預測準確率分別為96.8%、69.0%及89.6%。然而使用資料期間將影響預測準確率，當刪除不穩定期間資料，將使預測準確率分別提高為98.1%、72.7%及91.4%。

關鍵字

中小企業貸款 ； 提前清償 ； 卡方檢定 ； 羅吉斯迴歸模型

並列摘要

The research objects are the 336 small and medium enterprises (SMEs) loans undertaken by a government-owned bank during 2006-2011. According to loan auditing, lending policies, the credit ranking of the business and records of interaction with banks, 20 variables are selected to analyze the critical factors of affecting the prepayment of SMEs loans. The results can offer banks handling SMEs loans business and framing loan policy and risk control strategy, then can ultimately avoid wasting resources, besteading physical revenue and overall operational achievement.
Chi-square test and Logistic regression analysis model will be applied to exam the differences the probability among relevant variables that has significant influence on the prepayment of SMEs loans. The results suggests that “product market”, “net after-tax profit margin”, “inventory turnover”, “Interest rate”, and “accounts receivable turnover” are significant influence on the prepayment of SMEs loans. The former four factors have positive impact while the last one has the negative influence on the prepayment of SMEs loans.
Applying the confusion matrix prediction, the prediction accuracy rates on “no prepayment cases”, “prepayment cases” and “overall SMEs loan cases” are 96.8%, 69.0% and 89.6% respectively. However, the prediction accuracy rates will be affected by the data stability. Those will significantly increase to 98.1%, 72.7% and 91.4%, respectively as deleting the fluctuating period of data.

並列關鍵字

Small and Medium Enterprises loans ； Prepayment ； Chi-square test

參考文獻

10. 吳佩芬(2012)。影響消費性貸款逾期因素之實證分析，國立台中科技大學企業管理系事業經營研究所碩士論文。台中。

11. 吳幸珍（2010）。中小企業經營特性與貸放違約率關係之實證研究，國立台中科技大學企業管理系事業經營研究所碩士論文。台中。

2. 石雨宸(2010 ) 。應用存活分析模型探討借款人提前清償之行為，朝陽科技大學

15. 陳冠宏(2011)。應用邏輯斯迴歸與支持向量機建構兩階段提前清償模型。國立交通大學工業工程與管理學系碩士論文。台北。

20. 莊昊翰(2011)。應用邏輯斯迴歸與存活分析建構台灣中小企業貸款提前清償預測模型。國立交通大學工業工程與管理學系碩士論文。台北。