The Study of Credit Rating Model for Collateral Loan of Bank

碩士 === 國立高雄第一科技大學 === 財務管理所 === 95 === The impact of credit and cash card debts caused the high growth of non-performing loan rate last year; these banks which issued credit cards and cash cards have received the high amount of money of bad debts and faced the decrease of profits. Compared with the...

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Bibliographic Details
Main Authors: Wen-hao Chang, 張文豪
Other Authors: Weissor Shiue
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/80656898233725373529
Description
Summary:碩士 === 國立高雄第一科技大學 === 財務管理所 === 95 === The impact of credit and cash card debts caused the high growth of non-performing loan rate last year; these banks which issued credit cards and cash cards have received the high amount of money of bad debts and faced the decrease of profits. Compared with the loans of cash card and credit card, collateral loans had lower risks because the assets had to be used as collaterals. In addition, the real estate market is recovering and the better qualities of collateral loans are strictly controlled by banks, however the limitation that the amount of non-collateral loans can’t beyond 22 times of monthly personal incomes has been loosened. In order to increase the applications of loans, these banks are willing to offer the higher amount of loans and reduce the rate of interest. Good or bad credit records of cardholders, therefore, influence profits and debts of banks. Good credit records can increase profits and reduce bad debts, but bad credit records bring the opposite result. The purpose of this study is to explore the influence of credit rating on the profits and debts of banks. 200 samples of collateral loans during 2002 to 2005 are drawn from a bank which locates in the south of Taiwan, including 100 samples lift loans normally and 100 samples are in default on loans. This study is applied Discriminant analysis, Classification and Regression Tree(C&RT) and Logit model to construct the credit rating model for collateral loan of bank. The empirical results provide evidence that the best model is Logit model, which has better credit scoring accuracies, and then the relation between the amount of loan and the probability of default is negative and significant.