Published in: 14th International Industrial Engineering Conference
COI code: IIEC14_064
Paper Language: English
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Authors Forecasting the loan repayment behavior by banks loan receivers using discrete Markov chainFarid Hassanvand - Farid Hassanvand, MSc of Industrial Engineering, Department of Industrial Engineering, KNToosi university of Technology, Tehran
Hamed Daneshvari - PhD student of Industrial Engineering, Department of Industrial Engineering, KNToosi university of Technology, Tehran
Abstract:The banks charge due date and delayed payment is always one of the most important crisis in the loan lenders progression towards customers. The increase in the charges and delayed payments cause an inevitable losses to the banks. If banks estimate their future charges properly, they can prevent their capital losses by making some decisions such as surplus budget determination and confidence saving. In this research we investigated the forecasting modeling of the customers loan repayment behaviors. Theproposed model contains 4 states: 1. active; 2. payment with 1_2 month delay; 3. payment with 2_3 months delay; 4. delayed. The transmission matrix among various states has been obtained from historical data about the repayment manner of one of the domestic banks based on which the forecasting has been conducted. Results show that Markov chain model can forecast loan repayment behavior by customers well.
COI code: IIEC14_064
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Hassanvand, Farid & Hamed Daneshvari, 2017, Forecasting the loan repayment behavior by banks loan receivers using discrete Markov chain, 14th International Industrial Engineering Conference, تهران, انجمن مهندسي صنايع ايران - دانشگاه علم و صنعت ايران, https://www.civilica.com/Paper-IIEC14-IIEC14_064.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Hassanvand, Farid & Hamed Daneshvari, 2017)
Second and more: (Hassanvand & Daneshvari, 2017)
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Type: state university
Paper No.: 9382
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