Fraud Detection · Documentation
Business Problem & Solution
The problem Fraud Detection solves in the hospitality ecosystem and how this downscaled demo proves it.
← Fraud DetectionCatch risky bookings before they cost
Booking and payment fraud is a chargeback and trust problem: a high-value first booking from a new account, a card whose BIN country does not match the guest IP, a burst of bookings from one device, a watchlisted email domain, a billing-versus-stay-city mismatch, a rapid cancel-rebook. Fraud Detection scores bookings against this signal set, surfaces the high-risk ones, and lets an owner hold, clear, or escalate a signal into a refund/dispute case to limit exposure.
What this proves — and what it simplifies
It proves a transparent risk score with named reasons, an auto-hold threshold, and a clean escalation loop into the refund/dispute app (#21). The deterministic signal rules are authoritative; the metered model rides on top. It simplifies by scoring synthetic bookings with a recorded OSS model at $0 by default; no real cards, no real guests, no PII.