CREDIT CARD DEFAULT PREDICTION USING MACHINE LEARNING: A LOGISTIC REGRESSION MODEL APPROACH Article Swipe
Quang Le Minh
,
Hung Le Minh
,
Linh Nguyen Hoang Anh
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.33564/ijeast.2025.v09i11.002
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.33564/ijeast.2025.v09i11.002
This comprehensive analysis explores the application of logistic regression models in predicting credit card defaults, a critical concern for financial institutions worldwide. Current research demonstrates that logistic regression provides an effective framework for identifying potential defaulters based on demographic, financial, and behavioral features. Studies across various datasets reveal prediction accuracies ranging from 85- 90%, with key predictors including payment history, credit utilization, income levels, and demographic factors. While more complex algorithms may offer marginal performance improvements, logistic regression remains valuable for its interpretability and practical implementation advantages in financial risk management systems.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.33564/ijeast.2025.v09i11.002
- https://doi.org/10.33564/ijeast.2025.v09i11.002
- OA Status
- diamond
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409903861
All OpenAlex metadata
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https://openalex.org/W4409903861Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.33564/ijeast.2025.v09i11.002Digital Object Identifier
- Title
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CREDIT CARD DEFAULT PREDICTION USING MACHINE LEARNING: A LOGISTIC REGRESSION MODEL APPROACHWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-03-01Full publication date if available
- Authors
-
Quang Le Minh, Hung Le Minh, Linh Nguyen Hoang AnhList of authors in order
- Landing page
-
https://doi.org/10.33564/ijeast.2025.v09i11.002Publisher landing page
- PDF URL
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https://doi.org/10.33564/ijeast.2025.v09i11.002Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.33564/ijeast.2025.v09i11.002Direct OA link when available
- Concepts
-
Logistic regression, Credit card, Computer science, Artificial intelligence, Machine learning, Regression, Econometrics, Statistics, Mathematics, World Wide Web, PaymentTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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5Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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