Leveraging Machine Learning and Artificial Intelligence for Fraud Prevention

Abstract

- Fraud remains a pervasive global issue, affecting individuals and organizations alike. In the modern technology-driven landscape, the role of machine learning (ML) and artificial intelligence (AI) has become paramount in combating fraud across various sectors. This article critically examines traditional fraud prevention methods, highlighting their limitations in the face of ever-evolving fraudulent tactics. It further explores how ML and AI technologies revolutionise fraud prevention efforts by facilitating rapid digitalization. By harnessing the power of ML algorithms and AI techniques, organizations can effectively analyze massive volumes of data, uncover patterns, and identify abnormal behaviors that often signify fraudulent activities. This article delves into the invaluable role played by ML and AI in augmenting fraud prevention through advanced data analytics, anomaly detection, and predictive modeling. It emphasizes how these technologies enable organizations to detect and mitigate fraud risks proactively, thus safeguarding their operations and stakeholders.