Accounting fraud poses significant financial and reputational risks for organizations. Traditional detection methods … data. In contrast, artificial intelligence technologies, including machine learning, anomaly detection, and natural … conventional fraud detection techniques with AI-driven approaches, highlighting their respective strengths and limitations in terms …

Accounting fraud poses significant financial and reputational risks for organizations. Traditional detection methods … data. In contrast, artificial intelligence technologies, including machine learning, anomaly detection, and natural … conventional fraud detection techniques with AI-driven approaches, highlighting their respective strengths and limitations in terms …

Anomaly detection approaches have become critically important to enhance decision-making systems, especially regarding … anomaly detection have examined mainly abnormalities that translate into fraud, such as fraudulent credit card transactions or … database, tests with different dimensional sizes of data and indicators of the detection models' effectiveness. Therefore, the …

community detection algorithms to find the most important results and relationships in the literature. The final results show …

detection by a hybrid classifier due to optimal hyper parameter tuning, which is performed by the proposed intelligent preying …

community detection algorithms to find the most important results and relationships in the literature. The final results show …