using multi-state markov models to identify credit card risk
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ID: 246614
2016
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Abstract
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.
| Reference Key |
rgis2016productionusing
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| Authors | ;Daniel Evangelista Régis;Rinaldo Artes |
| Journal | Neotropical entomology |
| Year | 2016 |
| DOI |
10.1590/0103-6513.160814
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| URL | |
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