Credit card fraud detection remains a critical challenge for financial institutions, particularly due to extreme class …: anomaly detection based on multivariate normal distribution and deep reinforcement learning using a Deep Q-Network. While … anomaly detection effectively identifies deviations from normal transaction patterns, its static nature limits adaptability in …

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 …

values exhibit a consistent downward trend. Overall, by combining anomaly detection, empirical inter-arrival estimation, and …

clustering-based topic detection and lexicon-based sentiment analysis is followed by a regression analysis, to identify factors …