A STUDY ON BANKING FRAUD DETECTION MECHANISMS

Abstract

Banking fraud has become a major challenge for financial institutions due to the rapid growth of digital banking, online transactions, and electronic payment systems. This study examines banking fraud detection mechanisms and their role in identifying, preventing, and minimizing fraudulent activities. It focuses on the use of advanced technologies such as artificial intelligence (AI), machine learning, data analytics, biometric authentication, multi-factor authentication, and real-time transaction monitoring to detect suspicious behavior and reduce financial losses. The study also highlights the importance of regulatory compliance, cybersecurity measures, employee awareness, and customer education in strengthening fraud prevention strategies. By analyzing existing fraud detection practices and their effectiveness, the research aims to identify key factors that enhance the security and reliability of banking operations. The findings are expected to provide valuable insights for banks to improve their fraud detection systems, protect customer assets, maintain trust, and ensure a secure digital banking environment.