在傳統的住宅抵押貸款核貸過程中，銀行授信人員依據申請人之信用狀況做為貸放基礎，授信之准駁與審核人員經驗之主觀判斷有關，在此作業流程下，容易因為人為疏忽、判斷錯誤、同業競爭等因素而造成授信品質低落，因此建立客觀之信用評分模型，以分數高低作為貸放標準，藉以降低授信之違約風險，實屬必要。本研究即以此精神為出發點，將不同借款人之經濟狀況、財務特性量化，以計算其違約機率，並將違約機率轉換成分數，建立客觀的信用評分模型 (credit scoring model)，期能提供銀行在住宅抵押貸款核貸過程中有一客觀且公正之評分依據，以藉此提高授信品質並保障銀行債權。

In conventional mortgage lending process, bank manager decides whether to approve the mortgage applications based on the credit risk of applicants. However, the evaluation result may be distorted due to operational error such as lack of experience, manager’s subjective decision, or business competition. Therefore, it is essential to build a criterion to help bank manager to make right decisions.
Credit scoring comprises a set of statistical models that quantify credit risks of loan applicants. It is also a process of assigning a single quantitative measure, the score, to represent the borrower’s probable future loan performance. Once credit scoring model has been set up, bank manager can deal with large volumes of lending decisions in an efficient, consistent, and controlled manner.
The intent of this article is to develop a numerical credit evaluation model to quantify the applications’ financial status, and personal characteristic. With the help of the credit scoring model, bank manager can distinguish between “good” applicants and “bad” applicants in an efficient, stable, and accurate manner.

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