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Automatic Data Collection Design for Neural Networks Detection of Occupational Frauds
Abstract
Automated data collection is necessary to alleviate problems inherent in data collection for investigation of management frauds. Once we have gathered a realistic data, several methods then exist for proper analysis and detection of anomalous transactions. However, in Nigeria, collecting fraudulent data is relatively difficult and the human labour involved is expensive and risky. This paper examines some formal procedures for data collection and proposes designing an automatic data collection system for detection of occupational frauds using artificial neural networks.
