AI-Powered Payroll Fraud Detection: Enhancing Financial Security in HR Systems

Abstract

Payroll fraud is a significant threat to organizational financial integrity, and traditional fraud detection methods are becoming inadequate due to their inability to handle large, complex datasets. This paper explores the use of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing payroll fraud detection within HR systems. The study outlines a comprehensive methodology, starting from data collection to model training, anomaly detection, and automated fraud response mechanisms. By leveraging AI, organizations can achieve real-time monitoring, proactive fraud detection, and automated responses, significantly reducing the risk of financial losses and improving the overall accuracy of payroll systems. Case studies demonstrate the successful application of AI-powered systems in preventing payroll fraud, offering substantial cost savings and operational efficiency. The integration of advanced AI techniques promises a future where payroll fraud detection systems are more adaptive, predictive, and scalable, safeguarding organizations against evolving fraud tactics.