Evaluating the Effectiveness of Information Systems Audits in Detecting and Preventing Financial Fraud in Banks

Abstract

This comprehensive study examines the effectiveness of Information Systems
(IS) audits in detecting and preventing financial fraud within commercial banking institutions. Through analysis of 285 documented fraud cases across 42 U.S.
banks from 2010-2014, coupled with survey data from 180 IS auditors, this research develops a predictive model for fraud detection effectiveness. The findings
demonstrate that organizations with robust IS audit functions detect fraudulent
activities 3.2 times faster and prevent 67% more potential fraud incidents compared to those with basic audit capabilities. The research introduces the Fraud
Detection Capability Maturity Model (FDC-MM), which identifies five critical dimensions influencing audit effectiveness: data analytics integration, control environment assessment, forensic capabilities, organizational independence, and continuous monitoring. Statistical analysis reveals strong correlation (r=0.79, p¡0.001)
between FDC-MM scores and actual fraud prevention outcomes. The study provides empirical evidence supporting strategic investments in IS audit functions as
a cost-effective fraud mitigation strategy, with an estimated return on investment
of 4.3:1 for mature audit programs. These findings have significant implications for
banking regulators, audit committees, and security professionals seeking to enhance
financial system integrity.