工業革命以來，汽車就一直與人們有著密不可分的關係。而各種先進科技不斷的用在改良汽車的安全、性能、品質上，全球各汽車廠商無不積極的開發新穎的產品，行銷策略也以推展到世界各地的市場為目標，並結合汽車分期付款的辦法來拓展市場，近年來更設計出零利率、低頭期款、半價車、免保人等多項符合市場需要的融資商品來促銷。

　　汽車貸款授信品質的良窳，最重要的就是要找出影響貸款風險的主要因素。在授信過程中能儘量排除這些風險因子，而授信後為了減少逾期損失的發生，也宜建立一套風險管理的預警模式，以降低企業發生呆帳的機率。本研究應用統計方法中的存活分析、羅吉斯迴歸及區別分析等方法來找出影響逾期之重要因素，此三種統計方法皆有不錯的結果，其中職業狀況是各研究方法中最顯著的變數。貸款公司以此來評估消費者的風險程度，可提高授信的品質並加速作業流程，對客戶的風險管理也能更加準確。

　After the Industrial Revolution , the vehicles and the mankind have very strong relationship each other. Several state-of-the-art innovation and technology on the safety, function and quality improvement have also stirred the vehicle manufacturers to concentrate the investment on new product development. On marketing strategy, globalization oriented with the installation promotion has wide spread out aggressively, the new promotion policies of Zero Interest Rate, Low Down Payment, 50% Off, No Guarantee Acknowledged Requirement, and various financing options are the new designs for expanding their market share.

　Therefore, the quality of the procedures of car loan would be the very important index for the loaning business institutions to adjust their loan allowance by the related influence factors to control the financing crisis. To reduce the crisis factor on the overdue losses in the installing effectively would rely on the precaution alarm model of “Risk Management”, and it would be helpful for business to reduce the bad loan occurred. In this research, we use the survival analysis, logistic regression and discriminant analysis to find the key factors and positive conclusion on influencing the overdue conditions. According to the results of this research, the “career” would be the most important variable found by these three analysis, the financing companies would use this criteria to evaluate its crisis index and to adjust the loan volume, respectively.

中文部份：
1.王俊傑(2000)，財務危機預警模式──以現金流量觀點，台北大學企業管理研究所碩士論文。

2.李宗龍(2001)，信用卡使用特性對消費性貸款行為之預測，台灣大學國際企業研究所。

3.李美笑(2002)，信用卡持卡人信用風險之研究，逄甲大學保險研究所碩士論文。

4.李柔靜(1991)，台灣股票上市公司財務危機預測模式之研究，文化大學企業管理研究所碩士論文。

5.林佐鼎(1998)，存活分析方法於公車事故因素之研究，行政院國家科學委員會研究計畫成果報告，計畫編號：NSC88-2211-E006-042。

6. 林建州(2001)，銀行個人消費信用貸款授信風險評估模式之研究，中山大學財務管理學系研究所碩士論文。

7.吳宗正(1995)，迴歸分析，理論與應用，復文書局。

8.吳萬益、林清河(2000)，企業研究方法，華泰書局。

9.陳順宇(1997)，迴歸分析，華泰書局。

10.陳順宇(2000)，多變量分析，華泰書局。

11.黃文隆(1993)，「財務危機預警模式建立與驗證」，東吳大學管理學研究所碩士論文。

12.郭志安 (1997)，以Cox模型建立財務危機預警模式，逢甲大學統計與精算研究所碩士論文。

13.曾素娟(2000)，「考慮經濟景氣變動之企業失敗預警模式──台灣上市公司之研究」，成功大學企業管理研究所碩士論文。

14.張文生(2000)，銀行建購「信用卡信用風險即時預警系統」之研究，中原大學企業管理研究所碩士論文。

15.溫建志(2001)，以存活分析建立企業危機預警模型，朝陽科技大學財務金融研究所碩士論文。

16.賴麗月(1994)，「企業失敗的預測──比例危機模型應用」，東吳大學會計研究所碩士論文。

17.賴允勻(2000)，機車失竊影響因素與因應對策之研究──以新竹市為例，交通大學運輸工程與管理學系碩士論文。

英文部份
1.Altman,E.I.(1968),“Financial Ratios, Discriminant Analysis, and the Prediction of Corporate Bankruptcy, ”Journal of Finance, 23,pp.589-609.

2.Beaver,W. (1966),“Financial Rations as Predictors of Failure, Empirical Research in Accounting: Selected Studies,”Supplement to journal of Accounting Research,4,pp.71-111.

3.Blum,M.(1974),“Failing Company Disriminant Analysis,”Journal of Accounting Research, 12 ,pp.1-25.

4.Coats, P. and Fant,F.(1993) “Recognizing Financial Distress Patterns Using a Neural Network Tool,” Financial Management 22, pp142-165.

5.Cox,D.R.(1972),“Regression models and life-tables,”Journal of the Royal Statistical Society, Series B ,PP.187-220.

6.Henebry,K.L.(1996),“Do Cash Flow Bariables Improve the Predictive Accuracy of a Cox Proportional Hazards Model for Bank Failure?,”The Quarterly Review of Economics and Finance, 36,Fall , pp.395-409.

7.Kleinbaum,D. G.(1996),“Survival Analysis,”A Self-Learning Text, Springer-Verlag, New York.

8.Klein, J.P .and Moeschberger, M.L.(1997),Survival Analysis Techniques for Censored and Truncated Data, Springer.

9.Lane,W.R.,S.W.Looney and J. W. Wansley(1986),“An Application of the Cox Proportional Hazards Model to Bank Failure,”Journal of Banking and Finance, 10,pp .511-531.

10.Lee,S.H. and J. L. Urrutia(1996),“Analysis and Prediction of Insolvency in the Property-Liability Insurance Industry:A Comparison of Logit and Hazard Model,”The Journal of Risk and Insurance, 63,pp.121-130.

11.Mossman, C. E., G. G. Bell, L.M. Swartz, and H. Turtle(1998), “An Empirical Comparison of Bankruptcy Models,” Financial Review Vol 3,pp35-53.

12.Vandell,K.D.,W.Barnes,D.Hartzell,D.Kraft,and W.Wendt(1993),Commercial Mortgage Defaults:Proportional Hazards Estimation Using Individual Loan Histories,”Journal of the American Real Estate and Urban Economics Association, 21,pp.451-480.