Customer Validation Using Hybrid Logistic Regression and Credit Scoring Model: A Case Study

Customer Validation Using Hybrid Logistic Regression and Credit Scoring Model: A Case Study
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فصل: 
دوره: 
۱۹
شماره: 
۱۶۷
شماره صفحه (از - تا): 
۵۴-۵۸
چکیده

In this paper a regression model is applied for validating the customers of a company.‎ Using a Delphi method beside the expert panel the main variables which construct the regression model are extracted.‎ A credit scoring system for validation of the customers is developed based on applied regression model.‎ Then a Newton-Raphson method is used for determining the coefficients of regression model.‎ Furthermore the MacFadden statistical value is calculated for approving the regression model.‎ A case study is presented for application of proposed model.‎ Three factors of sponsor’s job, applicant’s jobs and income are extracted as the main factors which are affecting the customer validation in the case.‎ The result of the proposed model based on the case study showed that using a regression model which is empowered by Delphi system can provide a robust model for validation of the customers for deciding on granting to the customers.‎ 

استناد: 

Ershadi, Mohammmad Javad, and Davood Omidzadeh.‎ 2018.‎ Customer Validation Using Hybrid Logistic Regression and Credit Scoring Model: A Case Study.‎ Quality- Access to Success ۱۹ (۱۶۷): ۵۴-۵۸.

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