Machine learning-based anomaly detection understands your data, identifies anomalies, and helps you avoid damage.
Be it errors in entering invoice numbers or amounts, misallocation of charges on invoices, or fraudulent activities such as credit card or voucher fraud.
Anomaly detection systems:
- Analyze large volumes of transactional data to detect anomalies in underlying patterns
- Can respond in real time to detected fraud with user suspensions, transaction cancellations or notifications
Examples of anomaly detection techniques include:
- Analyze multiple ID or credit card parameters using machine learning algorithms to prevent fake ID and credit card transactions.
- Prevent abuse of promo codes and loyalty programs by detecting users who use multiple accounts or proxy servers to make unlawful purchases and gain benefits
- Examine and interpret the components of supporting documents to identify errors and discrepancies and avoid erroneous entries
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