Platform/Fraud
Rules-first.
Explainable by design.
A centralized, rule-driven fraud engine that evaluates payment events in real time using predefined rules, enriched context, and deterministic outcomes — then orchestrates prevention actions across gateway and switch flows.
Outcomes
CNP and CP decisions driven from the same versioned ruleset.
Reason codes and traces for disputes and regulatory questions.
Maker-checker and staged rollout for anything customer-impacting.
How it works
Authorization, auth advice, or gateway session signals.
Velocity, lists, BIN/MCC, geo, device, and custom attributes.
Deterministic rules with explicit outcomes.
Step-up, decline, or allow with downstream hooks.
Analyst queues with full trace to rule versions.
Security & operations
- Segregation of duties for rule authors vs approvers
- Immutable audit for promotions and overrides
- Data minimization hooks for sensitive attributes
Product preview
Integrations
Integration snippet
Example request shape for sales and solution engineering — replace endpoints and credentials with your environment.
curl -sS https://api.flagship.example/v1/fraud/evaluate \
-H "Authorization: Bearer $FLAGSHIP_TOKEN" \
-d '{"transaction_id":"txn_1","signals":["velocity","device"]}'Where this product sits
Four layers — from people-facing surfaces down to durable records.
Compliance & attestations
- Rules and lists are versioned with maker-checker before activation.
- Model scores and thresholds are auditable for regulator and partner review.
- PII minimisation is applied to fraud payloads shared with third-party scoring.
FAQ
No. The product direction is explainable, rule-first decisions with traceability.
Yes. Shadow mode is part of the rollout vocabulary.
It focuses on decisioning and evidence export; CM tools can sit beside it.
Next step
Map Fraud Engine to your stack in a working session — no slide-only promises.