Information Systems Auditing and Cyber-Fraud Prevention in the U.S. Banking Sector: A Comprehensive Framework for Digital Channel Security (gjstudies, 2018)
This research paper examines the effectiveness of Information Systems (IS) auditing procedures in detecting and preventing cyber-fraud attempts across digitalchannels in the U.S. banking sector. With the rapid digital transformation of financial services, institutions face increasing threats from phishing attacks, accounttakeover schemes, and sophisticated cyber-fraud attempts. The study develops acomprehensive analytical framework that integrates machine learning algorithmswith traditional audit controls to enhance fraud detection capabilities. Throughempirical analysis of banking transaction data and audit logs from 2015-2017, wedemonstrate that integrated IS audit systems can reduce false positives by 42%while improving detection accuracy by 67%. The research proposes a novel RiskWeighted Audit Scoring (RWAS) model that dynamically adjusts audit proceduresbased on real-time risk assessment. Findings indicate that banks implementingadaptive IS audit frameworks experienced a 58% reduction in successful cyberfraud incidents compared to those relying on conventional static audit approaches.The study contributes to both academic literature and practical implementationsby providing a scalable framework for cyber-fraud prevention in digital bankingenvironments.