信用風險模型修正時機之判定程序

Abstract

銀行及金融機構主要業務在於管理客戶存款，藉由吸取存款者的資金，再放款給需要資金者以獲取利潤。而在放款時，必需考慮放款風險以及利潤，如果不能掌控信用風險，一旦授信客戶發生違約、無法償還貸款而造成呆帳，銀行反而承受重大損失。現有之風險評估模式之文獻中，大多僅針對預測企業是否會違約的準確率進行研究，未針對修模時機點進行研究。而過於頻繁修正模型會導致實務上操作的困難；而若過長時間未修正模型，則會導致模型對於未來預測樣本之準確率下降。本研究首先利用部分最小平方法的路徑模型，找出變數中具有交互作用之變數加入考慮，再利用逐步邏輯斯迴歸建構模型後，投入變數及交互作用因子，挑選出影響模型之顯著變數，再比較不同年度間預測樣本，顯著變數發生明顯變異之個數，若其佔總顯著變數1/3以上，則表示模型對於未來預測樣本之準確率有誤差，則應加入新資料以修正模型；若其總顯著變數1/3以下，則表示此模型對於不同年度之預測樣本準確率誤差較小，因此可繼續使用此模型對未來樣本預測。在建構此流程後，銀行及金融機構可利用此機制判斷修正模型之時機點，以避免修正模型次數頻繁，或模型長時間未修正造成準確率之誤差。

The principal activities of banks or financial institutions is the management of customer deposits, depositors of funds through the lessons, and then lending those funds to the need for profits. In lending, it is necessary to consider the lending risk and return. If banks or financial institutions could not control the credit risk of the customer, the credit default or bad loans would lend to heavy losses. Literature of credit risk model, the most part are studying the forecast accuracy about the probability of default. There are few about the timing point for the revision of model studies. The modified model too often lead to practical difficulties in operation. If it is too long to modified the model, would result in model prediction decreased for the future accuracy. First, this study used partial least squares path model to identify variables with the interaction, and then using stepwise logistic regression to constructed model. The input use original variables and the interaction of factors. Find the significant variables of the model, and then compare the inter-annual forecast sample. Count apparent variation of the number of significant variables. If the apparent variation of significant variables ratio larger than 1/3, then the model forecast for the future accuracy rate will be error. It should add new information to correct the model. If the total significant variables ratio less than 1/3, then the model predict for different years of the accuracy of error is small. This model can predict the future sample. After the construction of this process, banks and financial institutions can use this mechanism to determine the timing to modified the model. In order to prevent too often or too long to modified model.