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A Qualitative Study On Predictive Models In Accounting Fraud Detection, Anthony Cecil
A Qualitative Study On Predictive Models In Accounting Fraud Detection, Anthony Cecil
Doctoral Dissertations and Projects
Companies lose an estimated 5% of revenue each year due to occupational fraud. This level of fraud can significantly disrupt the capital markets and cause companies to go bankrupt. Unless organizations, the government, and the accounting profession develop a systematic approach for accounting fraud detection, investors and employees will continue to lose money. This study explored subject matter experts’ perceptions of building and deploying artificial intelligence and predictive models to detect accounting fraud. This case study consisted of interviews with 10 participants with expertise in predictive modeling, auditing, and investigating, as well as a systematic literature review of research and …