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研究生: 黃啟倫
Huang, Chi-Lun
論文名稱: 資料包絡分析在銀行信用評分之應用
Application of Data Envelopment Analysis In Banking Credit Scoring
指導教授: 許永明
Shiu, Yung-Ming
學位類別: 碩士
Master
系所名稱: 管理學院 - 企業管理學系碩士在職專班
Department of Business Administration (on the job class)
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 56
中文關鍵詞: 信用評分信用評等資料包絡分析法風險評估銀行業
外文關鍵詞: Data Envelopement Analysis, Credit Scoring, Credit Rating, Risk Assessment, The banking Industry
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  • 「信用」與「風險」向來係為金融機構用以評估企業償債能力之主要面向,鑑於近期全球經濟環境快速變化,以及「新巴賽爾資本協定」(New Basel Capital Accord)以明文規定,金融機構可使用自行創立之內部評等法來衡量自身之資產內容,進而給予不同權重之資本計提,因此,如何建立一套合理之信用評分機制來檢視放款品質並適當降低資本計提,為現今金融機構相當重視之課題。

    本研究主要係應用資料包絡分析法(Data Envelopment Analysis),並以目前金融機構授信時所著重之財務比率數字,建構一評估企業信用之評分系統,並將本系統套用至國內上市、櫃之光電、半導體及網通三大族群企業,共286間企業,並將信用評分之結果與台灣經濟新報所提供之企業風險指標(Taiwan Corporate Credit Risk Index)對照,比對本研究之準確性及實際違約企業之命中率,依本研究之結果顯示,僅需輸入企業之主要財務比率數字,即可獲得相關之信用評分,且依信用評分之結果顯示,本次研究對於企業違約之辦別確屬有效,可提供銀行業一簡便且實用之信用評分系統,進而建立相關之信用評等。

    "Credit" and "Risk" has always been the two main dimensions for financial institutions to assess the repayment abilities of enterprises. According to the recent rapid changes in global economic environment and the "New Basel Capital Accord", financial institutions could use their own internal rating method to evaluate the grade of their loan assets, thereby giving different weights of the related capital cost. Therefore, how to establish a reasonable credit scoring system to evaluate individual enterprise would be an important issue for today's financial institutions.

    This study proposes a DEA-based approach to credit scoring. For the empirical evidence, this methodology was applied to current financial data of 286 listed firms in Taiwan. Using financial ratios, the methodology could calculate a firm’s overall performance into a single financial credibility score. The results were also validated by Taiwan Corporate Credit Risk Index(TCRI) and by testing the model’s discriminatory power using actual default cases of 11 firms.

    目錄 第一章 前言 1 第一節 研究動機 1 第二節 研究範圍及研究目的 2 第二章 文獻回顧與探討 3 第一節 信用風險與巴賽爾協定 3 第二節 信用評分分析模型的歷史演進 5 第三節 資料包絡分析 7 第四節 目前銀行運用信用評分之現況 9 第三章 研究設計與研究方法 11 第一節 研究設計與架構 11 第二節 利用資料包絡分析法(DEA)進行信用評分 23 第三節 與Min(2007)之模型進行比較分析 24 第四章 研究結果 27 第一節 樣本於經濟新報評等分布之情形 27 第二節 樣本使用本研究方法之分佈情形 30 第三節 樣本於Min(2007)研究方法之分佈情形 31 第四節 Min(2007)與本次研究樣本之分佈差異 32 第五節 Min(2007)與本研究模式與經濟新報評等之比較 33 第五章 結論與建議 35 第一節 研究結論 35 第二節 研究建議 37 參考文獻 38 附錄 41

    中文文獻
    1. 吳萬益(2005),企業研究方法,華泰文化事業。

    2. 張大成(2003),違約機率與信用評分模型,台灣金融財務季刊,第四輯
    第一期,頁19-37。

    3. 陳妙真(2004),現金流量分析簡介,華南銀行業務報導NO.22,頁21-27。

    4. 台灣經濟新報,TCRI方法論:TEJ企業信用風險指標(Taiwan Corporate
    Credit Risk Index),台灣經濟新報網站。


    英文文獻
    1. Bergendahl, G. (1998). "DEA and benchmarks - an application to
    Nordic banks." Annals of Operations Research 82: 233-249.

    2. Cheng, E. W. L., Y. H. Chiang, et al. (2007). "Alternative
    approach to credit scoring by DEA: Evaluating borrowers with
    respect to PFI projects." Building and Environment 42(4):
    1752-1760.

    3. Cook, W. D. and L. M. Seiford (2009). "Data envelopment analysis (DEA) - Thirty years on." European Journal of Operational Research 192(1): 1-17.

    4. Crook, J. and J. Banasik (2004). "Does reject inference really improve the performance of application scoring models?" Journal of Banking & Finance 28(4): 857-874.

    5. Emel, A. B., M. Oral, et al. (2003). "A credit scoring approach for the commercial banking sector." Socio-Economic Planning Sciences 37(2): 103-123.

    6. Hu, Y. C. and J. Ansell (2007). "Measuring retail company performance using credit scoring techniques." European Journal of Operational Research 183(3): 1595-1606.

    7. Kumra, R., R. M. Stein, et al. (2006). "Assessing a knowledge-based approach to commercial loan underwriting." Expert Systems with Applications 30(3): 507-518.

    8. Liu, F.-H. F. and H. Hsuan Peng (2008). "Ranking of units on the DEA frontier with common weights." Computers & Operations Research 35(5): 1624-1637.

    9. Lopez, J. A. and M. R. Saidenberg (2000). "Evaluating credit risk models." Journal of Banking & Finance 24(1-2): 151-165.

    10. Min, J. H. and Y.-C. Lee (2006). "A practical approach to credit scoring." Expert Systems with Applications In Press, Corrected Proof.

    11. Paradi, J. C., M. Asmild, et al. (2004). "Using DEA and worst practice DEA in credit risk evaluation." Journal of Productivity Analysis 21(2): 153-165.

    12. Pille, P. and J. C. Paradi (2002). "Financial performance analysis of Ontario (Canada) Credit Unions: An application of DEA in the regulatory environment." European Journal of Operational Research 139(2): 339-350.

    13. Pille, P. and J. C. Paradi (2002). "Financial performance analysis of Ontario (Canada) Credit Unions: An application of DEA in the regulatory environment." European Journal of Operational Research 139(2): 339-350.

    14. Premachandra, I. M., G. S. Bhabra, et al. (2009). "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique." European Journal of Operational Research 193(2): 412-424.

    15. Riding, A., J. Madill, et al. (2007). "Incrementality of SME loan guarantees." Small Business Economics 29(1-2): 47-61.

    16. Stanton, K. R. (2002). "Trends in relationship lending and factors affecting relationship lending efficiency." Journal of Banking & Finance 26(1): 127-152.

    17. Sueyoshi, T. and M. Goto (2009). "DEA-DA for bankruptcy-based performance assessment: Misclassification analysis of Japanese construction industry." European Journal of Operational Research 199(2): 576-594.

    18. Treacy, W. F. and M. Carey (2000). "Credit risk rating systems at large US banks." Journal of Banking & Finance 24(1-2): 167-201.

    19. Troutt, M. D., A. Rai, et al. (1996). "The potential use of DEA for credit applicant acceptance systems." Computers & Operations Research 23(4): 405-408.

    20. Yeh, Q. J. (1996). "The application of data envelopment analysis in conjunction with financial ratios for bank performance evaluation." Journal of the Operational Research Society 47(8): 980-988.

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