Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan)
Loans are essential in today's banking industry, most of the assets of a bank loan payments are made to individuals and companies. Considering the increasing number of loan applicants and regard to the risk of these activities, it is essential to provide a way to manage the loans. In this study...
| Format: | Article |
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| Language: | fas |
| Published: |
University of Sistan and Baluchestan
2013-01-01
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| Series: | پژوهشهای مدیریت عمومی |
| Subjects: | |
| Online Access: | https://jmr.usb.ac.ir/article_1019_31cfdee2c4eeaf271d06307de5f30388.pdf |
| _version_ | 1797904231242399744 |
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| collection | DOAJ |
| description | Loans are essential in today's banking industry, most of the assets of a bank loan payments are made to individuals and companies. Considering the increasing number of loan applicants and regard to the risk of these activities, it is essential to provide a way to manage the loans. In this study, using logistic regression, a random sample of 519 cases (284good customers accounts and 235bad customers account) from actual customers who have received facilities from Sepah bank of Zahedan between years 2006 to 2011 have been selected. First 22 explanatory variable sinclude quantitative and qualitative variables models. However, due to the significance of the15 variables which have significant effect on credit risk and differentiate between two groups of happy clients and bad credit clients have been chosen & they’ve fitted the final model. Significance of coefficients in the fitted model rejects the hypothesis of independent variables to be in effective and could result insignificant regression model. The results indicate the significance and high reliability of statistical parameters, the functions of the coefficients and effect of resolution. So, in order to decreasing the credit risk it is beneficial to concentrate on some applicants characteristics which have maximum effect in final regression. |
| first_indexed | 2024-04-10T09:46:37Z |
| format | Article |
| id | doaj.art-9469de51edf94a8c854c713646795672 |
| institution | Directory Open Access Journal |
| issn | 2538-3418 2676-7880 |
| language | fas |
| last_indexed | 2024-04-10T09:46:37Z |
| publishDate | 2013-01-01 |
| publisher | University of Sistan and Baluchestan |
| record_format | Article |
| series | پژوهشهای مدیریت عمومی |
| spelling | doaj.art-9469de51edf94a8c854c7136467956722023-02-17T05:26:19ZfasUniversity of Sistan and Baluchestanپژوهشهای مدیریت عمومی2538-34182676-78802013-01-0151813515210.22111/jmr.2013.10191019Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan)Loans are essential in today's banking industry, most of the assets of a bank loan payments are made to individuals and companies. Considering the increasing number of loan applicants and regard to the risk of these activities, it is essential to provide a way to manage the loans. In this study, using logistic regression, a random sample of 519 cases (284good customers accounts and 235bad customers account) from actual customers who have received facilities from Sepah bank of Zahedan between years 2006 to 2011 have been selected. First 22 explanatory variable sinclude quantitative and qualitative variables models. However, due to the significance of the15 variables which have significant effect on credit risk and differentiate between two groups of happy clients and bad credit clients have been chosen & they’ve fitted the final model. Significance of coefficients in the fitted model rejects the hypothesis of independent variables to be in effective and could result insignificant regression model. The results indicate the significance and high reliability of statistical parameters, the functions of the coefficients and effect of resolution. So, in order to decreasing the credit risk it is beneficial to concentrate on some applicants characteristics which have maximum effect in final regression.https://jmr.usb.ac.ir/article_1019_31cfdee2c4eeaf271d06307de5f30388.pdfcredit ratingcredit riskrisk managementdiscrete regression models |
| spellingShingle | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) پژوهشهای مدیریت عمومی credit rating credit risk risk management discrete regression models |
| title | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) |
| title_full | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) |
| title_fullStr | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) |
| title_full_unstemmed | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) |
| title_short | Loan Customers Validation Using Credit Scoring model (Case Study : Sepah Bank Branches Zahedan) |
| title_sort | loan customers validation using credit scoring model case study sepah bank branches zahedan |
| topic | credit rating credit risk risk management discrete regression models |
| url | https://jmr.usb.ac.ir/article_1019_31cfdee2c4eeaf271d06307de5f30388.pdf |