The increasing complexity of business processes and the development of information technologies create new opportunities for intentional misstatement of financial statements, posing serious challenges to the audit profession. The identification of fraud during an audit is complicated by insufficient methodological base: international standards establish only framework principles, existing research is fragmented, and modern approaches to fraud detection are often not adapted to the specifics of audit activities. This study contributes to solving this problem by systematizing methodological approaches to conducting audit procedures in response to fraud risks. The paper analyzes the requirements of international auditing standards regarding fraud, presents a five-stage model of auditor responsibilities, and structures the principles for conducting responsive procedures at the financial statement and assertion levels. Special attention is given to the methodology for testing the appropriateness of accounting entries (journal entry testing) and indicators of intentionally misstated accounting entries. The applicability of Benford's Law in conjunction with data mining technologies as a comprehensive statistical toolkit for identifying signs of fraud is analyzed. The research results are intended to optimize auditors' work in planning and conducting procedures in response to fraud risks and to enhance the effectiveness of detecting intentional misstatements in financial statements.
Viktor M. Sushkov (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: