Using multi-state markov models to identify credit card risk
Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Associação Brasileira de Engenharia de Produção (ABEPRO)
2016-06-01
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| Series: | Production |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132016000200330&lng=en&tlng=en |
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| Summary: | Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk. |
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| ISSN: | 1980-5411 |