A Semi-Supervised Machine Learning Approach to Detect Anomalies in Big Accounting Data

Anomaly detection in large scale accounting data is one of the long-standing challenges in the financial audit practice. Accounting professionals have resorted to advanced machine learning techniques to address this. This approach is applied to an insurance policy dataset consisting of approximately 32 million records.

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https://aisel.aisnet.org/ecis2020_rp/100