REAL-TIME FRAUD DETECTION: A BANKING INDUSTRY CASE STUDY

This comprehensive article examines the implementation and evolution of real-time fraud detection systems in modern banking environments. The article explores the transformation of digital payment landscapes, focusing on the architectural frameworks, implementation strategies, and performance metrics of advanced fraud detection systems. The article demonstrates how financial institutions can effectively combat sophisticated fraud patterns while maintaining operational efficiency through detailed analysis of system components, stream processing, machine learning models, and data management strategies. The article encompasses core infrastructure components, data processing pipelines, performance achievements, operational challenges, and future improvements, providing valuable insights into best practices and lessons learned from enterprise-scale deployments.