Risk & Anomaly Detection
Proactive detection of fraud patterns, bid rigging, and compliance anomalies across your supply chain.
What It Does
Machine learning and rule-based analysis monitor procurement data in real time, flagging anomalies such as: unusual bid patterns, split procurement to avoid thresholds, suppliers consistently winning by narrow margins, price deviations from market benchmarks, and duplicate supplier identities. Alerts are routed to designated compliance officers with full context.
Configurable risk thresholds and investigation workflows ensure that flagged items are reviewed and resolved systematically. Historical analysis identifies recurring patterns that may indicate systemic issues requiring structural intervention.
Why It Matters for South African SCM
South African procurement is vulnerable to bid rigging, collusion, and fronting. Traditional detection methods are reactive — identified months or years later during audits. AzaniaSCM's proactive approach catches anomalies as they occur, enabling intervention before losses occur and demonstrating a commitment to good governance.
The Competition Commission and Special Investigating Unit have identified procurement fraud as a significant drain on public resources. By implementing proactive detection, organs of state demonstrate the "reasonable steps" required by PFMA to prevent irregular, fruitless, and wasteful expenditure.