A flag isn't a block. Your traveler in Lisbon keeps earning while your team checks the case.
Each risk score comes with the reason behind it: unusual velocity, a registration cluster, or a redemption that’s out of character for that member.
Every transaction is checked against normal patterns, so abuse surfaces before it drains your points.
Before a promotion goes live, AI Loyalty Guard checks it against everything already running and flags combinations that hand out points nobody meant to give.
Each reviewer decision feeds back into the model, so over time, flags fit your members, partners, and rules more closely.
Follow one unusual redemption through AI Loyalty Guard and see where the system steps in, where your team takes over, and why no genuine member gets locked out along the way.
Each member gets their own baseline alongside your program’s, so a redemption that’s routine for a frequent flyer still stands out on a casual member’s account.
When something breaks the pattern, it gets a risk score and a plain-language reason, so your reviewers know exactly what to check first.
Flagged cases land in your review queue. Nothing is blocked or held automatically, so genuine members keep earning while your team takes a look.
A reviewer marks each case as genuine, probably genuine, monitored, or suspected. Every decision goes back into the model and sharpens future detection.
Pick the example closest to your business and see what the reviewer sees, what they check, and how they make the call.
An airline sees one account redeem in Toronto, then in Lisbon a few hours later. AI Loyalty Guard flags the jump and shows the distance and time between the two redemptions. The reviewer finds an overnight flight in the booking and marks it genuine.
A grocery chain gets dozens of sign-ups in one afternoon, all with near-identical details and all claiming the welcome bonus. AI Loyalty Guard flags the cluster, and a reviewer marks it as suspected and pauses the bonuses.
A fuel retailer sees one card earn eight times in an hour at the same station. AI Loyalty Guard flags the spike, and the reviewer marks it monitored while checking for a fleet account.
Results depend on your program, so rather than promise a number, we show each decision-maker what changes and which metrics will prove it.
Fake transactions, promotion abuse, and staff card scanning add liability with no sale behind it, and catching them early keeps it off your books. Track points liability from flagged activity against your pre-launch baseline, and margin lost to unearned rewards.
Genuine members keep earning while cases are reviewed, so your fraud controls don’t become the reason someone loses faith. Track how many flagged cases turn out to be genuine, and complaints about blocked accounts.
Every case comes with a reason and a recorded outcome, and the queue gets easier to work as detection learns your program. Track time to a decision, and how often flags are confirmed.
AI Loyalty Guard works with data already in your platform, under the privacy, access, and hosting rules you set.
Use Left and Right arrow keys to choose a card. Use Home or End to go to the first or last card.
Your AI comes with people who know your members, your partners, and your rules. Let us show you how AI Loyalty Guard spots the pattern and hands the decision to them.
AI Loyalty Guard is the AI fraud detection capability in Comarch Loyalty. It monitors enrollments, transactions, redemptions, and points activity, scores anything unusual, explains why it was flagged, and sends the case to your review team. A person always makes the final decision, and every decision helps the model learn your program.
Got something we didn't cover?
Ask away
