Fraud Detection Questions

Most integrations take 4-8 weeks from kickoff to live detection, depending on your current infrastructure. The first 2-3 weeks involve API setup and historical data analysis—we need to understand your transaction patterns before the models start learning. After that, it's usually deployment and tuning.

False positives are real and we don't hide it. The system learns your baseline patterns—what's normal for your processors, card-present vs. card-not-present, seasonal spikes. We work with you to calibrate the sensitivity. You might catch 92% of fraud at a 3% false positive rate, or 78% with 1%—it's your call based on your tolerance.

No. The API sits between your existing payment flow and your fraud checks. We handle the heavy lifting—feature engineering, anomaly scoring, alert routing—and you integrate via REST endpoints or webhook callbacks. Existing systems stay intact.

The system adapts to your mix. Card-present transactions (in-store, terminals) have different risk signals than card-not-present (online, phone). We train separate models for each channel and aggregate them into a single risk score. Cross-channel patterns also matter—if someone's swiping cards in three cities simultaneously, that's a signal regardless of channel.

The models retrain continuously on incoming data. Fraudsters adapt, so we adapt. You'll see alerts shift as new patterns emerge—maybe a new card testing ring starts hitting your merchants, or seasonal behavior changes. We monitor model performance and flag drift so you're never flying blind.

Pricing scales with your transaction volume and complexity. You get API access, model training, alert dashboards, and 90 days of integration support. There's no per-transaction fee or hidden licensing. We can walk through a rough estimate once we understand your volumes and transaction mix.