Real-time transaction risk systems operate under strict latency budgets, often making decisions in under 100ms. As transaction volume grows, maintaining accuracy becomes increasingly expensive.
moco reduces compute required per fraud decision by approximately 48%, enabling payment systems to process nearly 2× more transactions on the same inference infrastructure while preserving precision and recall.
Accuracy and model complexity are constrained by strict real-time latency requirements and infrastructure costs.
moco identifies low-risk transactions that can bypass expensive model execution while routing uncertain cases through the full pipeline.
Reduces unnecessary inference on easy transactions, freeing capacity for more sophisticated models and richer feature computation.
Teams can increase intelligence and throughput within existing latency and infrastructure constraints.