The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example
碩士 === 國立高雄應用科技大學 === 企業管理系碩士在職專班 === 100 === This study explores credit risk factors of preferential loans for housing project. Served as a reference indicator for banks to evaluate future housing loan customers, this study expects to elevate credit quality and lower late payment case numbers. The...
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ndltd-TW-100KUAS41210142015-10-13T22:01:09Z http://ndltd.ncl.edu.tw/handle/24232667291833896615 The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example 政府優惠購屋專案貸款授信風險評估 —以個案銀行為例 Tsong Wei Lee 李聰威 碩士 國立高雄應用科技大學 企業管理系碩士在職專班 100 This study explores credit risk factors of preferential loans for housing project. Served as a reference indicator for banks to evaluate future housing loan customers, this study expects to elevate credit quality and lower late payment case numbers. The purposes of this study are as follows: I. To identify significant influencing factors of borrowers’ credit defaults by examining research data variables. This will provide reference for credit decision makers, as well as establishing objective guidelines. II. To help establish an objective verifying system model for housing loan credit , for the purpose of enhancing credit quality, reducing ratio and amount of Non - Performing Loans, strengthening bank asset structures and increasing bank competitiveness. III. This loan is limited to house purchases, lowers the borrower’s financial burden, and has a per household line of credit. When comparing credit risk factors, this loan is superior because it has legitimate purpose of the capital and generates less financial burden, which lowers the default probablity in comparison to other housing loans. By employing the principle of credit risk assessment (the 5P principle: Personal, Purpose, Payment, Protection and Perspective), as well as verification factor and housing loan contract factor, i.e. the three dimensions, this study explores the major characteristic factors that influence this loan credit risk. We deployed nine independent variables, and tested them with SPSS software, discriminant analysis and decision trees. The empirical result after Model Validation revealed that the four significant variables that have the highest accuracy rates are profession, level of education, term of payment and payment status. This empirical result serves as a reference for banks when formulating credit policies. Key words: discriminant analysis, decision tree. Dr. Hui-Chung Yeh 葉惠忠 2012 學位論文 ; thesis 82 zh-TW |
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碩士 === 國立高雄應用科技大學 === 企業管理系碩士在職專班 === 100 === This study explores credit risk factors of preferential loans for housing project. Served as a reference indicator for banks to evaluate future housing loan customers, this study expects to elevate credit quality and lower late payment case numbers. The purposes of this study are as follows:
I. To identify significant influencing factors of borrowers’ credit defaults by examining research data variables. This will provide reference for credit decision makers, as well as establishing objective guidelines.
II. To help establish an objective verifying system model for housing loan credit , for the purpose of enhancing credit quality, reducing ratio and amount of Non - Performing Loans, strengthening bank asset structures and increasing bank competitiveness.
III. This loan is limited to house purchases, lowers the borrower’s financial burden, and has a per household line of credit. When comparing credit risk factors, this loan is superior because it has legitimate purpose of the capital and generates less financial burden, which lowers the default probablity in comparison to other housing loans.
By employing the principle of credit risk assessment (the 5P principle: Personal, Purpose, Payment, Protection and Perspective), as well as verification factor and housing loan contract factor, i.e. the three dimensions, this study explores the major characteristic factors that influence this loan credit risk. We deployed nine independent variables, and tested them with SPSS software, discriminant analysis and decision trees. The empirical result after Model Validation revealed that the four significant variables that have the highest accuracy rates are profession, level of education, term of payment and payment status. This empirical result serves as a reference for banks when formulating credit policies.
Key words: discriminant analysis, decision tree.
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Dr. Hui-Chung Yeh |
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Dr. Hui-Chung Yeh Tsong Wei Lee 李聰威 |
author |
Tsong Wei Lee 李聰威 |
spellingShingle |
Tsong Wei Lee 李聰威 The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
author_sort |
Tsong Wei Lee |
title |
The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
title_short |
The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
title_full |
The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
title_fullStr |
The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
title_full_unstemmed |
The Credit Risk Assessment of Government Preferential Loans for Housing Project – Take the Case Bank as an Example |
title_sort |
credit risk assessment of government preferential loans for housing project – take the case bank as an example |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/24232667291833896615 |
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