Real-Time AI-Based Fraud Detection Systems with Neural Networks

Abstract

Fraud detection is a critical component of financial systems, as fraudulent activities continue to evolve in sophistication and scale. Artificial intelligence (AI) and neural networks have emerged as powerful tools for real-time fraud detection, enabling systems to analyze vast amounts of data and identify suspicious activities with high accuracy. This article explores the role of AI and neural networks in developing real-time fraud detection systems, highlighting their applications, challenges, and future directions. It focuses on how deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are being utilized to enhance fraud detection across various industries