Stop bonus abuse before it clears your promo budget
Welcome offers, referral bonuses and coin promotions are magnets for abuse. Kixo9 flags the patterns behind them in real time.
Why manual review can't keep up
A fraud analyst reviewing signups one at a time is working with a fraction of the picture.
Reviewed in isolation, an abusive signup and a genuine one look almost identical — a name, an email, a device, a small claim. The tell isn't in any single account; it's in how that account relates to hundreds of others the analyst isn't looking at in the same moment. By the time a pattern gets noticed manually, it's usually because someone in finance flagged an unusual month of bonus payouts, which means the abuse already ran its course before anyone caught it.
Kixo9 solves the visibility problem, not just the detection problem: every new signup or claim gets checked against the full account graph automatically, so the pattern that would take an analyst hours to find manually — if they ever found it — surfaces in the time it takes the page to load.
What bonus abuse looks like
It rarely looks like one bad actor — it looks like ordinary-seeming signups, one after another.
Coin/credit farming
Repeated low-effort signups designed purely to harvest free-play currency or sign-up credit.
Referral loops
Self-referral chains where the same person invites accounts they also control.
Offer stacking
Claiming the same "new player" welcome offer repeatedly across accounts that share an identity.
Signals Kixo9 detects
Claim velocity
Unusual speed or frequency of bonus claims relative to normal player behavior. Genuine players tend to explore a platform for a while before claiming and redeeming a bonus; farmed accounts often do both within minutes.
Shared payout details
Multiple "new" accounts routing bonus payouts to the same card, wallet or bank account — the single strongest signal that separate-looking accounts share a controller.
Referral graph anomalies
Referral chains that loop back to a small cluster of controlling identities, rather than spreading out the way an organic referral network naturally does.
Promo stacking across offers
The same underlying identity claiming several different promotions in sequence — a welcome bonus, then a deposit match, then a re-engagement offer — each time under a "new" account.
Why volume-based rules alone don't work
The obvious first fix — cap claims per IP, or per device — catches the laziest abuse and misses almost everything else.
A single IP cap breaks the moment a fraudster routes through a residential proxy or a mobile network, and it produces false positives for anyone on a shared connection — students on a campus network, coworkers behind the same office router, family members at home. A device cap runs into the same problem in reverse: browser fingerprints can be randomized, emulators can spoof hardware signatures, and a determined operator will happily buy a stack of cheap phones if a hard device limit is the only thing standing between them and a promo budget.
Kixo9 doesn't rely on any single rule. A claim gets scored on the combination of signals around it — device history, payout destination, referral chain position, claim timing relative to signup, and how the account's early behavior compares to your platform's own baseline for genuine new players. That combination is much harder to fake consistently than any one signal on its own, which is why pattern-based scoring catches abuse that a flat rule would either miss entirely or over-block into oblivion.
What this looks like once it's running
Clean claims clear instantly
A first-time player with no overlap in the account graph gets approved in milliseconds — no added friction to your onboarding funnel.
Grey-area claims queue up
Claims with a few overlapping signals but nothing conclusive land in a review queue for your team, with the specific signals attached.
High-confidence abuse gets held
Claims matching a known farming or stacking pattern can be auto-blocked before the bonus ever clears, based on the thresholds you set.
Frequently asked
Does this slow down legitimate signups?
No — scoring happens in milliseconds and clean signups pass through without added friction. Only flagged claims are held for review.
Can we set our own risk thresholds?
Yes. You control what counts as auto-block, review, or auto-approve for your platform.
Does it work with our existing bonus engine?
Kixo9 integrates via API or webhook alongside your current promo/bonus system — no replacement required.
What happens to accounts that get wrongly flagged?
Any account routed to review rather than auto-blocked can be manually cleared by your team, and that outcome feeds back into the model so similar future cases score more accurately.
Find out how much bonus abuse is costing you
We'll review a sample of your claim data and show you what's slipping through today.