Financial Fraud Detection and Prevention: Automated Approach Based on Deep Learning

Abstract

Financial fraud has always been a serious challenge in the financial sector. With the continuous development of technology, fraud in the financial market has become increasingly complex and hidden. Therefore, financial fraud detection and prevention have become particularly important to our lives. But as of today, the financial fraud detection methods that have emerged often leave something to be desired. Traditional detection methods based on rules and statistical methods perform poorly when processing large-scale and high-dimensional data, and are prone to false positives and false negatives. Moreover, as fraud techniques continue to evolve, the adaptability of traditional methods is also challenged. As a powerful machine learning technology, deep learning has excellent feature extraction and pattern recognition capabilities, and has achieved remarkable achievements in various fields, including image recognition, natural language processing, and speech recognition. In the financial field, the application of deep learning is also gradually emerging.