Fraud Detection through Continuous Auditing and Monitoring in the Banking Sector (gjstudies, 2017)
This research investigates the effectiveness of continuous auditing and monitoring systems in detecting fraudulent activities within the banking sector. Throughcomprehensive analysis of 2.8 million transactions across 45 financial institutionsfrom 2014-2016, this study develops a predictive framework for identifying irregular transactions, policy violations, and control breaches. The findings demonstratethat continuous monitoring systems detect fraudulent activities 4.3 times fasterthan traditional periodic audits, with a 72% improvement in detection accuracyfor sophisticated fraud schemes. The research introduces the Continuous FraudDetection 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 emergingthreats. The study provides empirical evidence supporting the strategic implementation of continuous auditing technologies, with an average return on investmentof 5.2:1 through fraud prevention and operational efficiency gains. These findingshave significant implications for banking security, regulatory compliance, and theevolution of audit practices in increasingly digital financial environments.