Fraud Detection on E-Transaction Payment Systems Using Deep Neural Networks

This study proposes a method for employing deep neural networks (DNNs) to identify online fraud in electronic card (eCard) payment systems. Advanced detection methods are required because of the substantial rise in fraudulent and unscrupulous incidents brought on by the expansion of e-commerce and online payments. Due to convenience and the lack of a cashless economy, cardholders now make both online and offline purchases. To improve the precision and effectiveness of fraud detection systems, this study investigates many deep learning architectures. The primary goal of this study is to use deep learning to evaluate financial records, flag and stop transactions, and uncover new patterns to detect the possibility of fraud.