Performance Analysis of Machine Learning Techniques in Credit Card Fraud Detection
Year: 2025
Type: article
Abstract: The rapid growth of e-commerce and online banking has resulted in a substantial rise in credit card fraud incidents. Consequently, machine learning and advanced deep learning techniques have emerged as critical solutions. This study integrates the findings of a few researchers, examining diverse methodologies, including Naïve Bayes, K-Nearest Neighbor (KNN), Logistic Regression, CNN, RNN, and ensemble learning. A comparative performance analysis, emphasizing the challenges posed by imbalanced datasets, demonstrates the superior performance of hybrid models, in enhancing the accuracy of detecting the fraudulent in credit card transactions.
Authors: Suganya I, Naveen K., Ragul P., Sangeeth M.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407259396