Beyond Traditional Auditing: Forensic Accounting As A Strategic Mechanism For Detecting Financial Fraud and Corruption
DOI:
https://doi.org/10.56956/mbxdkm21Keywords:
forensic accounting, financial fraud, corruption, fraud detection, forensic analyticsAbstract
Financial fraud and corruption threaten the integrity of financial reporting, organizational accountability and the trust of investors. The core of auditing and internal control systems are essential to safeguard financial reporting, but misconduct is limited if the misconduct is collusion, management overrides or concealed transactions or sophisticated financial information is manipulated. Forensic accounting is a complementary type of investigation, but literature tends to examine its methods separately and does little to explain how they work and the conditions. The article provides a conceptual view of forensic accounting as a strategic tool in a system of financial accountability in which forensic accounting is regarded as a mechanism of strategic investigations and is conceived as a purposeful technique in the field of investigation. Based on fraud theory, agency theory, internal control and fraud risk management guidance and research into accounting manipulation and its detection, the authors define five investigative methods: forensic examination of financial data, analysis and digital investigation, internal control and governance assessment, evidence collection and documentation and coordination with the legal and regulatory authorities. It then defines four enabling conditions (professional competence, investigator independence, data accessibility and quality, institutional support) and proposes testable propositions that connect the mechanisms to measurable detection results. The analysis distinguishes between identifying suspicious transactions and rooting out fraud and financial statement manipulation from corruption. The article offers a theoretical basis for empirical research and practical advice on how to embed forensic accounting in governance structures. There is no empirical data that is presented.
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