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研究生:康建民
研究生(外文):Chien-Min Kang
論文名稱:個人貸款信用評分模型-以儲蓄互助社為例
論文名稱(外文):Credit scoring model for individual loans:An example of Credit Unions
指導教授:林霖林霖引用關係
指導教授(外文):Lin-Lin
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:財務金融學系
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:62
中文關鍵詞:儲蓄互助社信用評分模型
外文關鍵詞:credit unionscredit scoring modelLogistic Regression
相關次數:
  • 被引用被引用:13
  • 點閱點閱:811
  • 評分評分:
  • 下載下載:175
  • 收藏至我的研究室書目清單書目收藏:0
本研究實證結果發現,在儲蓄互助社個人貸款信用評分模型中有個人屬性、償債能力、信用往來,財產狀況、貸放條件、外在總體因素等六個方面,經由這些內容可得知申請人之風險承擔能力之優劣與否。儲蓄互助社可依這些觀點當作放款批駁、額度多寡的依據,或是衍生出新的模型變數,讓信用評分模型更加有效、更趨完整,以提升放款品質,減少儲蓄互助社的損失。此外,亦將此評分模型轉化為第一線審核人員可直接運用的信用評分表,使之能直接應用於個人貸款審核業務上,使得信用評分模型及信用評分表能發揮其實務價值。
This research results:there are individual attribute、payment ability、credit、finance、loan condition and external macro environmental factor aspects for individual loans of credit scoring model in credit unions.According to those content, it is clear to know the risk exposure of applicant.It is the good point for Credit Unions to use these viewpoints as verification and amount of loan .Perhaps by these viewpoints,it is more effective and complete for credit scoring model to derivate new model factors so as to promoteing loan quality, reduceing organization loss.In addition, this research also transform the credit scoring model into the credit scoring sheet that the first line examination personnel can use directly so that it can be applied directly on individual loan examination. In so doing, the credit scoring model and the credit scoring sheet can bring its practical value to full play .
目次
目錄頁 ................................ A
圖次頁 ................................ C
表次頁 ................................ C
第一章 緒論.............................. 1
第一節 研究背景............................ 1
第二節 研究動機與目的......................... 4
第三節 研究架構............................ 8
第二章 相關理論與文獻回顧....................... 10
第一節 儲蓄互助社簡介......................... 10
第二節 儲蓄互助社個人貸款特性..................... 10
第三節 信用風險評估原則........................ 12
第四節 信用風險評估方法相關文獻.................... 15
第五節 信用風險分析評估方法...................... 17
第六節 信用風險評估模型統計方法簡介.................. 20
第三章 研究設計與研究方法....................... 25
第一節 資料來源及研究方法說明..................... 25
第二節 變數衡量及說明......................... 27
第三節 最佳截斷點(optimal cut-off point) .............33
第四章 實證分析............................ 34
第一節 資料分析............................ 34
第二節 估計測試結果.......................... 37
第三節 變數篩選及模型之建立...................... 39
第四節 最適截斷點之決定........................ 43
第五節 信用申請評分表之編製...................... 46
第五章 研究結論與建議......................... 50
第一節 研究結論............................ 50
第二節 對研究對象之建議及限制 .................... 54
第三節 對後續研究者之建議....................... 54
參考文獻 ............................... 57
中文文獻 ............................... 57
英文文獻 ............................... 59
相關網站 ............................... 62
參考文獻
中文資料
1.王濟川、郭志剛(2004),Logistic 迴歸模型-方法及應用,五南圖書。
2.王保進(2004),多變量分析:套裝程式與資料分析,台北:高等教育出版社。
3.江世傑(2000),模糊類神經網路在消費性貸款之應用,國立成功大學工業管理研究所碩士論文。
4.呂美慧(2000),銀行授信評等模式-Logistic Regression之應用,政治大學金融研究所碩士論文。
5.江淑娟(2002),信用評等因素與信用卡違約風險之關係,逢甲大學保險研究所碩士論文。
6.李美笑(2002),信用卡持卡人信用風險之研究,逢甲大學保險學系研究所碩士論文。
7.何貴清(2002),消費者小額信用貸款之信用風險研究--以一商業銀行客戶為例,國立中山大學人力資源管理研究所碩士論文。
8.吳明隆、涂金堂(2006),SPSS與統計應用分析-二版,五南圖書。
9.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。
10.林勉今(2003),消費性貸款授信風險評估之研究-以X銀行為例,大同大學事業經營研究所碩士論文。
11.施孟龍、尤清芳、李佳珍(1999),Logit Model 應用於信用卡信用風險審核之研究,金融財務月刊。
12.葉秋南(1997),美國金融業風險管理,台北:財團法人金融聯合徵信中心編輯委員會。
13.張仁哲(1982),我國信用卡現代化問題之研究,國立政大企研所碩士論文。
14.孫炳焱(2001),台灣儲蓄互助社發展史,合作經濟,70,1-17。
15.郭迪賢(2001),儲蓄互助社經營理念原則,合作經濟,68,37-42。
16.郭迪賢(2002), 論儲蓄互助社的本質,合作經濟,72,1-10。
17.陳鴻文(2002),個人小額信用貨款授信模式之個案研究,國立高雄第一科技大學財務管理系碩士論文。
18.曾俊堯(1991),信用卡信用管理之研究」國立政大企研所碩士論文。
19.莊傑富(2005),不同信用評分模型對信用評等之影響,東吳大學經濟學系碩士論文。
20.詹育晟(2005),個人信用行為評分模式之研究—以現金卡用戶為例,國立政治大學資訊管理研究所碩士學位論文。
21.劉泰谷(2003),信用卡信用評分模型之建構與分析,私立世新大學財務管理研究所碩士論文。
22.鄭志新(2005),小額信貸信用評分模型之建構,世新大學管理學院經濟學系碩士學位論文。
23.戴堅(2004),個人消費性信用貸款授信評量模式之研究,國立中正大學國際經濟研究所碩士論文。
24.簡安泰(1977),消費者信用評分制度之研究,國立政大企研所碩士論文。
25.儲蓄互助社法(2002)。
26.儲蓄互助社手冊(2006)。
27.儲蓄互助社法規彙編(2004)。
28.龔昶元(1998),Logistic Regression 模式應用於信用卡信用風險審核之研究,台北銀行月刊,28卷9期,頁35-49。

英文資料
Altman, E., 1968, Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, Journal of Finance, 23,589–609.
Altman, E., Haldeman, R. and Narayanan, P., 1977, Zeta analysis:a new model to identify bankruptcy risk of corporations,Journal of Banking Finance, 1, 29–54.
Ann‐Marie, Ward and Donal, McKillop G., 2005, An investigation into the link between UK credit union characteristics, location and their success, Annals of Public and Cooperative Economics, 76(3), 461-489.
Allen, N. Berger and Scott, W. Frame, 2007, Small business credit scoring and credit availability, Journal of Small Business Management, 45(1), 5-22.
Benjamin, Lehn, Rubin, Julia Sass and Zielenbach, Sean, 2004, Community development financial institutions: current issues and future prospects, Journal of Urban Affairs, 26(2), 177-195.
Boyer, Kenneth K. and Tomas, G. M. Hult, 2005, Customer behavior in an online ordering application: a decision scoring model, Decision Sciences, 36(4), 569-598.
Cheng-Lung, Huang , Mu-Chen, Chen and Chieh-Jen, Wang, 2007, Credit scoring with a data mining approach based on support vector machines, Expert Systems with Applications, 33(4), 847-856.
Donal, G. McKillop, Anne-Marie, Ward and John, O. S. Wilson, 2007, The development of credit unions and their role in tackling financial exclusion, Public Money and Management, 27(1), 37-44.
David, Martens, Bart, Baesens, Tony, Van Gestel and Jan, Vanthienen, 2007, Comprehensible credit scoring models using rule extraction from support vector machines, European Journal of Operational Research, 183(3), 1466-1476.
Edward, I. Altman and Gabriele, Sabato, 2007, Modelling credit risk for SMEs: evidence from the U.S. market, Abacus, 43(3), 332-357.
Hosmer and Lemeshow, 2000, Applied Logistic Regression, 2nd.
Hamer, M., 1983, Failure prediction: sensitivity of classification accuracy to alternative statistical methods and variable set, Journal of Accounting and Public Policy, 2, 289–307.
Hand;D. J. and Henley, W. E., 1997, Statistical classification methods in consumer credit scoring: a review, Journal of the Royal Statistical Society., 160(3), 523-541.
Johnson, L. A., G. R. Welch, W. Rens, and J. R. Dobrinsky., 1998, Enhanced flow cytometric sorting of mammalian X and Y sperm: High speed sorting and orienting nozzle for artificial insemination, Theriogenology, 49-361.
Jalal, Akhavein, Scott, W. Frame and White, Lawrence J., 2005, The diffusion of financial innovations: an examination of the adoption of small business credit scoring by large banking organizations, The Journal of Business, 78(2).
Jih-Jeng, Huang, Gwo-Hshiung, Tzeng and Chorng-Shyong, Ong, 2005, Two-stage genetic programming (2SGP) for the credit scoring model, Department of Information Management, National Taiwan University, Institute of Management of Technology and Institute of Traffic and Transportation College of Management, National Chiao Tung University, Department of Business Administration, Kainan University.
Kasper, Roszbach, 2004, Bank lending policy, credit scoring, and the survival of loans, MIT Press journals, 86(4), 946-958.
Kevin, Wei-yu Chiang, Zhang, Dongsong and Lina, Zhou, 2006, Predicting and explaining patronage behavior toward web and traditional stores using neural networks: a comparative analysis with logistic regression, Decision Support Systems, 41(2),514-531.
Lin, L. and Piesse, J., 2004, Identification of Corporate Distress in UK Industrials: A Conditional Probability Analysis Approach, Applied Financial Economics, 14(2), 73-82.
Maddala, G., 1983, Limited-dependent and qualitative variables in econometrics, Cambridge University Press, Cambridge.
Manski, C. and McFadden, D., 1981, Alternative estimators and sample designs for discrete choice analysis, in structural analysis of discrete data and econometric applications, MIT Press, London.
Mays, E., 2001, The basics of scorecard development and validation, handbook of credit scoring, 5, 89-106.
McFadden, D., 1974, Conditional logit analysis of qualitative choice behaviour, in Frontiers in Econometrics (Ed.), P. Zaremba, Academic Press, New York.
Ohlson, J., 1980, Financial ratios and the probabilistic prediction of bankruptcy, Journal of Accounting Research, 18, 109–131.
Palepu, K., 1986, Predicting takeover targets: a methodological and empirical analysis, Journal of Accounting and Economics,8, 3–35.
Robert, B. Avery, Paul, S. Calem and Glenn B. Canner, 2004, Consumer credit scoring:Do situational circumstances matter?, Journal of Banking & Finance, 28, 835–856.
Ryota, Tomioka, Kazuyuki, Aihara1 and Klaus-Robert, Muller, 2007, Logistic regression for single trial EEG classification, Advances in Neural Information Processing Systems.
Steenackers, A. and Goovaerts, M.J., 1989, A credit scoring model for personal loans, Insurance Mathematics Economics, 31-34.
Tian-Shyug, Lee ,Chih-Chou, Chiu, Yu-Chao, Chou and Chi-Jie, Lu, 2006, Mining the customer credit using classification and regression tree and multivariate adaptive regression splines, Computational Statistics and Data Analysis, 50(4), 1113-1130.
Thomas, Lyn C., 2000, A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers, International Journal of Forecasting, 16, 149–172.

網路資料
1.中華民國儲蓄互助協會網站,http://www.culroc.org.tw/。
2.行政院主計處,http://www.dgbas.gov.tw/。
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