臺灣博碩士論文加值系統

銀行與金融機構放款予申貸企業前須衡量其信用風險，然可用以評估企業體質的變數眾多，在中、外文獻中並無一致的建議。除此之外，在實務上金融機構的申貸案件通常是依借款金額大小而由具不同審查權限的授信人員批核，而各階層之授信人員對各變數之重視程度也可能不同。本研究以中小企業為放款對象的金融機構的授信人員為研究對象，擷取其在決定對中小企業的放款決策時所考量之因素，並進一步分析各因素間的相對重要性。本研究首先以整理文獻與訪談實際從事企業金融授信人員的方式，歸納整理出實務上金融機構在評估中、小企業的放款風險時所考量的因素，再運用層級結構之概念將各因素分類，並設計問卷，交由金融機構的授信人員填寫。本研究利用層級分析法分析所回收之問卷資料，並深入探討授信人員對這些因素的偏好程度，將各變數的主觀判斷量化為權重。本研究將所設計的問卷交由台灣某專門從事中小企業貸款之金融機構授信人員填寫，在案例分析後得到以下結論：該金融機構授信決策者最重視中小企業的償債能力、公司領導者與管理階層的素質、企業本身財務結構與會計制度以及企業來往客戶的評價；且研究發現不同管理階層之決策者對企業能力要求確有不同，建議未來建立風險評估模式與信用評等模型時，可將權重結果代入資料，並針對案件批核層級建立多個風險評估或信用評等模型，增加模型產出結果之參考價值。

Banks and financial institutions have to evaluate their applicants’ credit risks before granting loans. However, the number of possible variables to assessing applicants’ credit is numerous. There has not been any firm conclusion found in literature as of the choice of assessing variables. In practice, loan applications are usually approved by different credit officers in accordance with the loan amounts. However, different credit officers might put different emphasis on assessing variables. This study examines the decision factors affecting credit officers’ loan decisions in financial institutions whose borrowers are mainly small- and medium-sized enterprises. Base on literature and the results concluded from interviewing field experts, this study summarized the variables that could be included in assessing enterprises’ credit risk. The concept of hierarchical structure was applied to classify these factors and a questionnaire was constructed and distributed to be filled out by credit officers. Using analytic hierarchy process to analyze the data collecting from credit officers, this study explored their preference on the decision variables and assigned weights to these variables based on these preferences. This study conducted a survey targeted at credit officers in a Taiwanese financial institution and found that the credit officers in that financial institution value solvency、leadership of management、corporate financial structure and the accounting system、and customers’ evaluation most. The study also found that the credit officers at different management levels do have different viewpoints toward the importance of these assessing variables. Base on the finding of this study, it is suggested that financial institutions could consider to associate different weights with different assessing variables and use multiple credit-rating models in accordance with different level of credit officers.

目錄
摘 要 i
英文摘要 ii
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1研究背景與動機 1
1.2 研究目的 4
1.3 研究方法 5
1.4 研究限制 5
1.5 研究架構 5
第二章 文獻探討 6
2.1 信用風險 6
2.1.1 新巴賽爾協資本協定與信用風險 6
2.1.2 金融機構授信原則 7
2.2 信用評等與風險評估 8
2.2.1 信用評等與風險評估之定義 8
2.2.2 信用評等與風險評估之比較 9
2.2.3 信用評等與風險評估之相關文獻 9
2.3 分析層級程序(AHP)法 17
2.3.1 AHP法之簡介 17
2.3.2 層級分析法之施行步驟 19
2.3.3 層級分析法之優點 21
2.3.4 層級分析法相關研究 22
第三章 研究方法 24
3.1 研究架構 24
3.2資料蒐集與變數整理 25
3.3建立層級分析架構 29
3.4權重分析 29
第四章 實例分析 31
4.1 問卷回收與資料整理 31
4.2 層級構面分析 33
4.3 重要變數界定 36
4.4管理階層決策分析 38
4.5 實例分析結果彙總 42
第五章 結論 44
5.1 結論 44
5.2 建議 45
參考文獻 46

參考文獻
[1] 方珍玲、陳怡芬，台灣地區農會組織績效衡量指標系統之研究－分析層級程序法之應用，台北大學合作經濟學研究所論文，2006。
[2] 王小璠，多準則決策分析，滄海書局•鼎隆圖書股份有限公司。
[3] 台灣經濟新報， TCRI企業信用風險指標資料庫，網址：http://www.tej.com.tw。
[4] 行政院金融監督委員會銀行局，金融統計指標98年1月版，網址： http://www.banking.gov.tw/lp.asp?ctNode=1845&CtUnit=499&BaseDSD=7 ，查詢日期：2009/03/10。
[5] 吳佩珊，建構台灣中小企業兩階段風險評估模型，國立交通大學工業工程與管理學系碩士論文，2008。
[6] 吳達凱，銀行業建立企業信用評等以管理授信信用風險之研究，東吳大學商學院企業管理學系碩士在職專班碩士論文，2007。
[7] 沈大白、張大成、劉宛鑫，信用評等模型之簡介，中國商銀月刊，2002。
[8] 沈俊誠，整合金融機構風險評估與信用風險評估流程之研究，國立交通大學工業工程與管理學系碩士論文，2004。
[9] 李沃牆、朱竣平，信用評等,公司違約與財務危機預測之探討，真理財經學報，第18期，頁33-70，2008。
[10] 汪美香、許溪南， AHP應用於外幣選擇權投資策略之研究-以國際金融業務分行(OBU)為例，企業管理學報，四十六期，頁115-134，1999。
[11] 林孟宏，中小企業抵押貸款決策流程之建構，國立交通大學工業工程與管理學系碩士論文，2005。
[12] 莊欣霖，應用邏輯斯迴歸構建銀行放款信用評等模式，國立交通大學工業工程與管理學系碩士論文，2002。
[13] 陳生祥，運用資料探勘技術建構企業財務危機預警模式-結合財務與非財務資料，中原大學資訊管理所碩士論文，2005。
[14] 陳英豪，應用自組性演算法建構企業信用評等模型，國立交通大學工業工程與管理學系碩士論文，2005。
[15] 陳淑萍，資料探勘應用於財務危機預警模式之研究，私立銘傳大學資訊管理研究所碩士論文，2003。
[16] 華南商業銀行，信用風險IRB小組，新巴塞爾資本協定—信用風險內部評等法簡介，華南商業銀行專題論述，2004024期，2004。
[17] 馮志綱，公營與民營金融機構個人擔保與信用放款授信評估，高雄工學院管理科學研究所碩士論文，1996。
[18] 黃美慧，我國銀行業上市公司股票評等之研究，國立政治大學企業管理學系碩士論文，1998。
[19] 黃振豊、呂紹強，企業財務危機預警模式之研究－以財務及非財務因素構建，當代會計，第一卷，第一期，頁19-40，2000。
[20] 經濟部中小企業處， 2008 中小企業白皮書，網址：http://www.moeasmea.gov.tw/ct.asp?xItem=7416&CtNode=513&mp=1 ，查詢日期：2009/03/07。
[21] 鄧振源、曾國雄，層級分析法(AHP)的內涵特性與應用(上)，中國統計學報，二七卷六期，頁13707-13724，1989。
[22] 鄧振源、曾國雄，層級分析法(AHP)的內涵特性與應用(下)，中國統計學報，二七卷六期，頁13707-13724，1989。
[23] 龐中懿，巴塞爾銀行監理委員會對銀行外部稽核規範之探討，元智大學會計研究所碩士論文，2004。
[24] Altman, E. I.,” Financial ratio discriminant analysis and the prediction of corporate bankruptcy,” Journal of Finance, Vol. 23, pp. 588-609, 1968.
[25] Azis, I.J., “Analytic hierarchy process in the benefit-cost framework: a post-evaluation of the Trans-Sumatra highway project,” European Journal of Operational Research, 48, pp. 38-48, 1990.
[26] Beaver, W.H., “Financial ratios as predictors of failure,” Journal of Accounting Research, pp.71-111, 1966.
[27] Bhutta, K.S. and Huq, F., “Supplier selection problem: a comparison of the total cost of ownership and analytical hierarchy process,” Supply Chain Management, Vol. 7, pp. 126–135, 2002.
[28] Dutta, S. and Shekhar, S., ” Bond rating: a nonconservative application of neural networks,” Proceedings of the IEEE International Conference on Neural Networks, SanDiego, pp. 443-450, 1988.
[29] Edmister, R. O., “An empirical test of financial ratio analysis for small business failure prediction,” The Journal of Financial and Quantitative Analysis, Vol. 7, No. 2, pp. 1477-1493, 1972.
[30] Fan, A. and Palaniswamiet, M., “Selecting bankruptcy predictors using a support vector machine approach,” Proceedings of the International Joint Conference on Neural Networks, Vol.6, pp.354-359, 2000.
[31] Frame, W. S., Srinivasan, A., and Woosley, L., “The effect of credit scoring on small business lending,” Journal of Money, Credit, and Banking, Vol.33, pp.813-825, 2001.
[32] Grunert, J., Norden, L. and Weber, M., “The role of non-financial factors in internal credit ratings,” Journal of Banking & Finance, Vol. 29, pp. 509–531, 2005.
[33] Hafeez, K., Zhang, Y. B., and Malak, N., “Determining key capabilities of a firm using analytic hierarchy process,” International Journal Production Economics, Vol. 76, pp. 39-51, 2002.
[34] Handfield, R., Waltion, S.V., Sroufe, R., and Melnyk, S. A., “Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process,” European Journal of Operational Research, Vol. 141, pp. 70-87, 2002.
[35] Huang, Z., Chen, H. C., Hsu, C. J., Chen, W. H. and Wu, S., “Credit rating analysis with support vector machines and neural networks: a market comparative study,” Decision Support Systems, 37, pp.543-558, 2004.
[36] Kim, C. N. and McLeod, Jr. R., “Expert, linear models and nonlinear models of expert decision making in bankruptcy prediction: a lens model analysis,” Journal of Management Information Systems, Vol. 16, No. 1, pp. 189–206, 1999.
[37] Kurttila, M., Pesonen, M., Kangas, J., and Kajanus, M., “Utilizing the analytic hierarchy process in SWOT analysis－a hybrid method and its application to a forest-certification case,” Forest Policy and Economics, Vol. 1, pp. 41-52, 2000.
[38] Laitinen, E. K., “Predicting a corporate credit analyst’s risk estimate by logistic and linear model,” International Review of Financial Analysis, pp. 97-121, 1999.
[39] Lau. A. H., ” A five-state financial distress prediction model,” Journal of Accounting Research, Vol. 25, No. 1, pp. 127-138, 1987.
[40] Maggie, C. Y. Tam, and V.M. Rao Tummala, “An application of the AHP in vendor selection of a telecommunications system,” Omega, Vol. 29, pp. 171-182, 2001.
[41] Manhiem, M. L. and Fall, F., “Abstract representation of goals: a method for making decisions in complex problems,” Transportation: A Service, Proceeding of the Sesquicentennial Forum, Academy of Science, American Society of Mechanical Engineers, pp. 732–740, 1967.
[42] Martin, D., “Early warning of banking failure,” Journal of Banking and Finance, Vol. 1, pp. 249-276, 1977.
[43] Mensah, Y. M., "An examination of the stationarity of multivariate bankruptcy prediction models," Journal of Accounting Research, Vol.22, No.1, pp. 380-395, 1984.
[44] Ohlson, J. A., “Financial ratios and the probabilistic prediction of bankruptcy,” Journal of Accounting Research, Vol.18, No.1, pp. 109-131, 1980.
[45] Odom, M. and Sharda, R., “Bankruptcy prediction using neural networks,” Proceedings of the IEEE International Conference on Neural Networks, SanDiego, pp. 133-168, 1990.
[46] Ong. M. K. (Ed.).,”Credit ratings :methodologies, rationale and default risk ,“ pp. 391-411. London :Risk Waters Group, 2002.
[47] Rose, P. S., Andrews ,W. T. and Giroux, G. A., “Predicting business failure : A macroeconomic perspective,” Journal of Accounting, Auditing & Finance, Vol. 6, No.1, pp. 20-31, 1982.
[48] Saaty, T. L., “The Analytic Hierarchy Process,” Mcgraw-Hill, 1980.
[49] Shin, K. S., Lee, T. S. and Kim H. J., “An application of support vector machines in bankruptcy prediction model,” Expert Systems with Applications, Vol.28, No.1, pp.127-135, 2005.
[50] Vaidya, O. S., and Kumar, S., “Analytic hierarchy process: an overview of applications,” European Journal of Operational Research, Vol. 169, pp. 1-29, 2006.
[51] Wu, C. Y., “Using non-financial information to predict bankruptcy: a study of public,” International Journal of Management, Vol. 21, No.2, pp. 194-201, 2004.
[52] Zahedi, F., “The analytic hierarchy process: a survey of the method and its applications,” Interfaces, Vol. 16, No. 4, pp. 96-108, 1986.