Optimizing credit card fraud detection with random forests and SMOTE

Optimizing credit card fraud detection with random forests and SMOTE

Abstract In the financial world, Credit card fraud is a budding apprehension in the banking sector, necessitating the development of efficient detection methods to minimize financial losses. The usage of credit cards is experiencing a steady increase, thereby leading to a rise in the default rate th...

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Bibliographic Details
Main Authors: P. Sundaravadivel, R. Augustian Isaac, D. Elangovan, D. KrishnaRaj, V. V. Lokesh Rahul, R. Raja
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Credit card fraud detection
Machine learning
Random forest
Imbalanced data
SMOTE
Classification algorithms
Online Access:https://doi.org/10.1038/s41598-025-00873-y
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https://doi.org/10.1038/s41598-025-00873-y

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