Credit Card Fraud Detection System using Machine Learning
The global danger posed by credit card fraud to financial institutions and customers makes the development of strong fraud detection systems imperative. In this study, we suggest a novel method for detecting credit card fraud that makes use of Convolutional Neural Networks (CNNs) and synthetic data generation. Inadequate feature representations and unbalanced datasets are common problems for traditional fraud detection algorithms. We use synthetic data generation techniques to build a balanced dataset that accurately represents the intricacies of fraudulent transactions in order to overcome these difficulties.
Authors
- Aarth Dahale
- Saurav Naik
Institutions
- MIT World Peace University (IN)
Publication Details
- Journal
- Journal of IoT and Machine Learning.
- Published
- 2024-08-16
- DOI
- https://doi.org/10.48001/joitml.2024.1219-23
- Citations
- 1
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.35