MobeeShield evaluates transactions in real time using rules, machine-learning anomaly detection and behavioural signals — then accepts, blocks or sends them for step-up verification before the money settles.
MobeeShield is positioned across the wider Mobee stack so risk teams are not operating a different fraud tool for every rail.
The product is built around a pre-settlement risk decision, with investigation only where the transaction needs human review.
Every transaction across connected switches is streamed into MobeeShield in real time.
Rules, anomaly models and behavioural context calculate transaction risk in milliseconds.
The risk engine returns an immediate action before transaction settlement.
Flagged events land in the case console for analyst investigation and resolution.
MobeeShield combines deterministic rules with machine-learning anomaly detection and behavioural monitoring so the risk decision is not dependent on one signal type.
Flagged transactions do not disappear into logs. Analysts can investigate, annotate and resolve cases in the same operating environment.
Risk teams also need policy control, case evidence and structured reporting for management, audit and regulatory review.
Configure and deploy real-time risk logic without relying on long engineering release cycles.
Use model-driven anomaly detection alongside deterministic rules.
Track changes in device, location and transaction behaviour.
Detect rapid activity and multi-device misuse before the transaction clears.
Investigate, annotate and resolve flagged transactions in one console.
Produce structured reports for RBI and internal audit requirements.
Talk to Mobee about rules, ML risk scoring, behavioural signals, case operations, reporting and rollout across your payment channels.