Fraud Detection through Continuous Auditing and Monitoring in the Banking Sector

Posted: Dec 05, 2017

• Hamza Shahbaz Ahmad
  University of Missouri Kansas City
• Rehan Zafar
  University of the Punjab
• Hina Tariq
  Institute of Business Administration (IBA)

Abstract

This research investigates the effectiveness of continuous auditing and monitoring systems in detecting fraudulent activities within the banking sector. Through comprehensive analysis of 2.8 million transactions across 45 financial institutions from 2014-2016, this study develops a predictive framework for identifying irregular transactions, policy violations, and control breaches. The findings demonstrate that continuous monitoring systems detect fraudulent activities 4.3 times faster than traditional periodic audits, with a 72% improvement in detection accuracy for sophisticated fraud schemes. The research introduces the Continuous Fraud Detection Effectiveness Model (CFD-EM), which incorporates real-time analytics, behavioral pattern recognition, and adaptive learning algorithms. Statistical analysis reveals that institutions implementing advanced continuous monitoring experienced 58% reduction in fraud losses and 67% faster response times to emerging threats. The study provides empirical evidence supporting the strategic implementation of continuous auditing technologies, with an average return on investment of 5.2:1 through fraud prevention and operational efficiency gains. These findings have significant implications for banking security, regulatory compliance, and the evolution of audit practices in increasingly digital financial environments.