Using Advanced Machine Learning Techniques for Anomaly Detection in Financial Transactions

Financial transaction anomaly detection has become a critical component of financial security, especially in light of the growing complexity of fraudulent activity and the increasing digitalization of financial transactions. The application of cutting-edge machine learning techniques has great potential in this regard, since they may leverage algorithmic accuracy and processing capacity to detect abnormalities that can point to fraudulent activity. The purpose of this introduction is to explore the basics, evolution, significance, research gaps, and the need for this study.