臺灣博碩士論文加值系統

銀行授信行為在商業社會中，一直扮演著重要的角色。而銀行在辦理放款業務時，卻或多或少具有某些程度的風險，也因此評估申貸者之信用是非常重要的。在傳統上，銀行評估借款者主要係依據台北市銀行工會所頒布的授信企業信用評等表，其可分為三大部分：1.財務狀況平評等、2.經營管理、3.產業特性暨展望。第一部分評分之方式乃計算企業之各個財務比率後分別給予1分、2分、……、或5分。這樣的評分方式往往會導致驟變性問題，且不能滿足敏感性。為了克服，本研究乃利用模糊集合論中所定義的梯形模糊數及三角形模糊數，來描述企業財務狀況在各項財務比率中所應得分數之程度，並藉由平均之觀念來做為評分之計算。而經營管理、產業特性暨展望兩部分多為主觀性的語意描述，我們利用模糊理論來處理語言性的描述。更具體來說，我們採用Chen&Hwang所提出的方法，將語言性的描述轉換為模糊數並合成後，再利用Delgado，Vila及Voxman,所提出模糊數之值的計算方式，來表達於此二部分之評分。

Making loans by commercial banks to firms is an important behavior in financial economy. However, when a bank processes a loan business, it also carries some credit risks. Therefore, assessing the loaner’s credit is critical. Traditionally, a bank evaluates a customer’s credit according to “The credit rating standard for lending to enterprises” published by Committee of the Bank of Taipei City. This standard can be divided into the following three categories: 1.Financial condition of the enterprise, 2.Management, and 3.The particular characteristics of the main product, competition and expectation. In the first category, financial ratios are calculated to evaluate the financial condition of an enterprise and each ratio is represented by five different variables, from 1 to 5. This is due to the problems of anticatastrophism and does not satisfy with the property of sensitivity. Thus, instead of using the five variables, we make the crisp scores into corresponding normal fuzzy numbers, with trapezoidal (or triangular) membership functions. By applying the concept of mean and fuzzy set theory, we proposed a reasonable algorithm to evaluate enterprises financial conditions. No numerical numbers can be obtained for the other two categories and thus only a linguistic representation can be used. It is proven that a fuzzy set theory can handle the linguistic representation, which is generally used in describing the various parameters, effectively. Hence, we convert linguistic terms to fuzzy numbers by Chen&Hwang conversion scale. And then aggregate these fuzzy numbers, and evaluate the value of the fuzzy numbers, which is proposed by Delgado, Vila, and Voxmen, in order to represent the rating of the two categories.

第一章 緒論
第一節 研究背景
第二節 研究動機與目的
第三節 研究範圍
第四節 論文架構
第二章 授信決策與信用評等
第一節 授信的意義與種類
第二節 授信作業流程
第三節 授信原則
第四節 信用評等制度
第三章 文獻探討
第一節 模糊集合
第二節 模糊數的加法
第三節 模糊數的排序
第四節 模糊數之值與模糊測度
第五節 企業財務狀況評等
第六節 企業財務狀況評等模式之問題
第四章 信用評等模式之建構
第一節 財務比率各個分數模糊集合歸屬函數之建立
第二節 財務狀況評等
第三節 經營管理與產業特性暨展望評等
第四節 信用評等模糊綜合評估模式架構
第五章 信用評等模擬個案
第一節 財務狀況評等模擬個案
第二節 經營管理與產業特性暨展望評等模擬個案
第六章 結論與建議

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