Advances In Neural Network For Credit Card Fraud Detection
Credit card fraud is the most serious form of risk to financial security and it has a far-reaching effect on consumers and users in general; this makes it necessary that modern methods for machine learning like neural networks should be employed in order to improve their capacity and accuracy for detecting frauds. Various popular neural network architectures for fraud detection, including Feedforward Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTM), Autoencoders, and Generative Adversarial Networks (GAN) are investigated in this study.
Authors
- Shikha Srivastava (ORCID: https://orcid.org/0000-0001-8224-3038)
- A. C. Singh (ORCID: https://orcid.org/0009-0007-1839-3382)
Publication Details
- Journal
- International Journal on Science and Technology
- Published
- 2025-04-03
- DOI
- https://doi.org/10.71097/ijsat.v16.i2.3236
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00