Use Case:

Organizations need to ensure that employee expenses align with company policies and flag any unusual activity that could indicate fraud, policy violations, or errors. Expenses in categories such as meals, lodging, or airfare can occasionally show unexpected variations, warranting closer attention.

The Anomaly Detection risk analytic identifies transactions that deviate from typical patterns by calculating a z-score, which measures how far a transaction’s value is from the average of similar transactions within a comparable group over a one-year historical period. The analysis groups transactions based on both payment method (e.g., cash, T&E cards, P-cards) and expense type (e.g., meals, lodging), establishing an expected range or "norm" for each group. Transactions that exceed two standard deviations from this average are flagged for review, helping organizations detect potential issues and ensure policy compliance.