ANALYSIS OF LOAN APPLICATION USING GENERALIZED LINEAR MODEL (GLM) WITH LOGIT LINK FUNCTION AND BY USING INFORMATION VALUE (IV)
Banking industry may be used to measure the economics growth of a country. However, bank stability is affected by many risks, one of which is credit risk. In this final <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br...
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| 主要作者: | |
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| 格式: | Final Project |
| 語言: | Indonesia |
| 在線閱讀: | https://digilib.itb.ac.id/gdl/view/15878 |
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| 機構: | Institut Teknologi Bandung |
| 語言: | Indonesia |
| 總結: | Banking industry may be used to measure the economics growth of a country. However, bank stability is affected by many risks, one of which is credit risk. In this final <br />
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project, the performance of a customer on his or her credit history is modelled using Generalized Linear Model (GLM) with logit link function and by using information value. The probability of rejecting or accepting loan application is determined based on a number of independent variables. In this final project, a case study on Bank XYZ application data is conducted. At 5% of significance level, it is found that the rejection or acceptance of a customer loan application is determined by gender and the model showed that male customers will have higher odds of default than female customers. A combination of GLM and IV, at 5% significance level, showed that the rejection or acceptance of a customer loan application is determined by gender, income, length of work, education level, and number of credit card owned by the customer. |
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