中小企業貸款違約預警模式－以某商業銀行為例

Loan Default Predicting Model for Small and Medium Enterprises-A Case Study of Commercial Bank

蔡明春(Ming-Chun Tsai) ； 鄭青展(Ching-Chan Cheng) ； 馮淑鈴(Shu-Ling Feng) ； 陳坤志(Kun-Chih Chen)

《文大商管學報》 14卷1期 (2009/06) Pp. 19-40

https://doi.org/10.30163/BR.200906.0002

摘要

本研究旨在探討影響中小企業違約貸款之非財務面因素，並藉以建立中小企業貸款違約預警模式。本研究以國內某商業銀行中小企業授信戶爲研究對象，以近似3:1比例取得154戶正常戶及52戶違約戶之相關資料，資料取得後，主要藉由卡方檢定與邏輯斯迴歸進行分析。研究結果發現，在非財務變數方面，不同產業別、成立時間、擔保品、銀行關係、負責人年齡、負責人是否動用現金卡或信用循環額度之企業，其違約比例具有顯著地差異。最後本研究利用此具區別能力之非財務變數爲作爲預測變數，建立之中小企業貸款之違約預警模式，預測能力達85%。此研究結果期望提供金融機構作爲建構中小企業授信風險評估之參考。

關鍵字

中小企業 ； 非財務變數 ； 邏輯斯迴歸

並列摘要

The study explores non-financial factors which affect loan default for SMEs (small and medium enterprises), and create a predicting model for SMEs loan risk therewith. The object of this study is the SMEs loan customers of a commercial bank's branches located in Taiwan. The study gets 154 normal cases and 52 default cases by the ratio of 3:1 approximatively. The survey data were analyzed using chi-square test and logistic regression. According to the result of this research, in terms of non-financial factors, the ratio of default businesses were significant differences on the elements of different industries, period of establishment, collateral, relationship with banks, age of the person in charge and whether the person in charge of uses the credit line of cash card or revolving line or not. Finally, this study makes use of the non-financial factors, which have discriminating applicability to be the forecasting factors, and creates a loan default precaution model for SMEs thereby; the accurate ratio of the forecast is more than 85%. We hope the result of this study can help financial institutions to set up their SMEs loan risk evaluation model and adopt some key reference factors therein.

並列關鍵字

Small and Medium Enterprises ； Loan Default ； Non-financial Factor ； Logistic Regression

參考文獻

中小企業融資信用保證作業手冊

只要撐過五年，中小型製造業存活機率大

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