Machine learning methods for ensuring transaction integrity in credit card systems: A comprehensive review

Le résumé fourni par la source

The continuing threat of credit card fraud targeting financial institutions demands more advanced data analysis techniques to ensure accurate detection and prevention. This research suggests a unique way to categorize Support Vector Machines that can improve fraud detection systems’ accuracy and performance dramatically. To identify areas of worry or suspicion, this proposed technique looks at various points of contact or databases, effective fraud detection and procurement, as well as odd behavior in transaction data processing. By proving the efficacy of classification and training techniques like SVM in preventing significant transactional-based fraud, this study will fill the present knowledge gap. The model runs between cycles of data, which allows it to detect fraudulent transactions rather well, according to the SVM-based results.

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