Financial fraud continues to undermine institutional integrity, investor confidence, and broader economic stability. As fraudulent schemes grow more sophisticated — leveraging digital platforms, complex ownership structures, and regulatory loopholes — traditional auditing methods prove increasingly insufficient for timely detection. This study investigates the role of forensic accounting as a superior alternative framework for detecting financial fraud and compares its effectiveness against conventional audit processes. Using a quantitative research design, primary data were collected from 50 participants — including chartered accountants, auditors, financial analysts, and MBA scholars — through a structured Likert-scale questionnaire. The study examined four key constructs: forensic accounting practices, professional expertise, organizational support, and technological adoption, with fraud detection effectiveness as the dependent variable. Multiple linear regression, mediation, and moderation analyses were employed to test five research hypotheses. Findings reveal that forensic accounting significantly improves fraud detection outcomes (β = 0.47, p < 0.001), with professional expertise and technological adoption serving as critical enablers. The study further demonstrates that forensic accounting detects fraud 2–3 times faster than traditional auditing and reduces organizational fraud losses by up to 54%, consistent with findings from ACFE (2022), PwC (2022), and Deloitte Insights (2022). All five hypotheses were supported at statistically significant levels. The research concludes that forensic accounting must be embedded into routine organizational governance rather than deployed reactively. Implications for practitioners, policymakers, and institutions are discussed alongside recommendations for structured adoption in emerging market contexts.
Dr. Shivaprasad Syed Abdullah (Sun,) studied this question.