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Fraud Detection in Financial Transactions: A Survey of Machine Learning Models and their Applications in Credit Card Security

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This review discusses fraud detection in credit card transactions using machine learning, highlighting challenges and advancements.

Machine learning models enhance fraud detection accuracy in financial transactions and address security issues.
Outstanding accuracy was achieved using ensemble methods, indicating their effectiveness against credit card fraud.
The review employs benchmark datasets to evaluate supervised and unsupervised learning methods for fraud detection.
Real-time processing and explainable AI are crucial for the development of advanced fraud detection systems.

R et al. (2025) studied this question.

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View Full Paper

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Authors

This review discusses fraud detection in credit card transactions using machine learning, highlighting challenges and advancements.

Machine learning models enhance fraud detection accuracy in financial transactions and address security issues.
Outstanding accuracy was achieved using ensemble methods, indicating their effectiveness against credit card fraud.
The review employs benchmark datasets to evaluate supervised and unsupervised learning methods for fraud detection.
Real-time processing and explainable AI are crucial for the development of advanced fraud detection systems.

R et al. (2025) studied this question.

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