From General Ledger to Big Data: The Transformation of Forensic Accounting and Fraud Detection in the Digital Age

Abstract

The global digitalization of financial ecosystems has fundamentally altered the morphology of economic crime, giving rise to so-called «Fraud 2.0»—a systemic, automated, and often invisible threat that renders traditional sampling-based auditing methods obsolete. This article examines the critical paradigm shift from manual review toward Forensic Data Analysis. Through the analysis of the integration of Big Data, Artificial Intelligence, and applications of Benford's Law, this study posits that the «Full Population Testing» approach is the only viable methodology for detecting irregularities in modern Enterprise Resource Planning (ERP) environments. Furthermore, the document addresses emerging challenges such as Blockchain immutability, crypto-asset tracing, and the legal admissibility of digital evidence. Finally, it concludes that the contemporary forensic accountant must evolve into a hybrid professional who bridges the gap between data science, legal compliance, and financial expertise.