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How casinos fight fraudsters - real cases
Modern online casinos are not only games, but also a large anti-fraud circuit: rules, machine learning (ML), KYC/AML, payment gateways, blockchain analytics, logging. The goal is simple: protect players and businesses by complying with license and regulatory requirements. Below - what really happens "under the hood" and what cases are most common.
Typical attack vectors (what attackers are trying to do)
1. Multi-account and bonus abuse. Creating a pack of accounts for the sake of greetings, cashbacks and referral awards.
2. Payment fraud. Stolen cards/wallets, subsequent chargebacks, "triangular" replenishments.
3. Collusion/collusion. In live games/bets - coordinated actions of several players.
4. Affiliate fraud. Traffic cheating, motivated spam, self-referral, cookie-stuffing.
5. KYC fakes. Fake documents, masks, "rented personalities," deepfaces.
6. Crypto risks. Deposits from addresses associated with hacks/mixers/sanctions lists; "overtook" through fast cycles.
7. Technical manipulation. Device spoofing, emulators, proxy farms, auto betting scripts where prohibited.
8. In-game abuse. Exploits feature, prohibited bets under the bonus (max bet, excluded games), "shifting risk" between accounts.
Protection tools (how it is caught)
Device fingerprint. Hardware/software parameters, canvas/fonts, audio context, WebGL → persistent identifier.
Network and geo-signals. ASN, proxy type/VPN/Tor, IP ↔ timezone mismatch ↔ system language.
Behavioral analytics. Speed/rhythm of clicks, betting patterns, reaction times, abnormal balance trajectories.
Linkage graph. Common devices/addresses/cards/wallets, "co-location" of accounts, repeated fingerprints.
Rules and scoring. Velocity limits, lists of banned BIN/addresses, ML models with human-in-the-loop.
KYC/AML/KYT. Dock checks (OCR + face match + liveness), sanctions/PEP screenings, source of funds; for crypto - on-chain rates, clusters, connections with mixers/SEC.
Payment protocols. 3-D Secure/SCA, AVS, test holds, black/gray PSP sheets.
Operational measures. Rate/withdrawal limits, cooldowns, step-by-step verifications, hold until review.
Real impersonal cases
Case 1: "Greetings Garland"
Symptoms. 14 "beginners" in 24 hours from one city, similar devices, instant bonus dep/output.
Signals. General device fingerprint with minimal User-Agent change; the same browser canvas; repeated sequence of clicks in onboarding; ref link of one affiliate.
Solution. Linked accounts are combined into a graph, bonuses are canceled by T & Cs, KYC verification is initiated; part of the accounts was closed, traffic was cut off to the affiliate, net deposits were paid to cardholders.
Inference. A "rule + graph" hybrid catches multipacks better than either alone.
Case 2: Chargeback Carousel
Symptoms. A series of small deposits with cards from different BINs, quick bets on minimum variance, instant withdrawal request, in weeks - a shaft of chargebacks.
Signals. Lack of 3-DS in terms of transactions, mismatch between IP and card country, duplicate mail addresses from the same type of domains.
Solution. Mandatory SCA for risk-BIN, pre-auth instead of direct debit, increase hold before 3-DS confirmation, cooperation with processing, friendly fraud registers.
Inference. Tight payment policy and SCA cut the ROI of such a scheme.
Case 3: Collusion in a live
Symptoms. Several accounts systematically "sit" in narrow side-bet markets, coordinated in time and amount.
Signals. Correlated bets, a single "hand" in behavior (up to the trajectory of the cursor), common device artifacts, activity in night windows.
Solution. Temporary freezing, review of table logs, cancellation of illegally obtained benefits according to the rules, escalation to the live provider and licensing ADR in a dispute.
Inference. Collusion is a combination of behavioral analytics and round history.
Case 4: Fake KYC
Symptoms. Instant download of "perfect" documents, EXIF/geo mismatch, one person on dozens of accounts.
Signals. Mismatch of angles/distortions, generation traces, repeating background, "plastic" eyes on liveness.
Solution. Enhanced face-match with active liveliness (micro-motion), repeated verification at a random moment, request for secondary documents, block of accounts.
Inference. Liveness + randomization of the verification stage greatly reduces the success of fakes.
Case 5: Crypto deposit from a "dirty" address
Symptoms. Replenishment from the wallet associated with the mixer/exchange hack; instant output to a new address.
Signals. High online risk rate, short wallet "length," connection with sanctions clusters.
Solution. Auto-hold to officer review, SoF/SoW request, if risk is confirmed - return to the original address/refusal and STR (Suspicious Transaction Report) to the regulator/partners.
Inference. KYT monitoring is mandatory for crypto cash registers.
Case 6: Affiliate fraud "traffic out of thin air"
Symptoms. Sudden spike in single-source registrations, zero LTV, fast bonus drainage.
Signals. High share of proxy/Tor, identical devices, the same type of e-mail patterns, CTR does not beat with conversion.
Solution. Post-attribution by quality (deposits/involvement), holding commissions to a partner, slice; introduction of anti-boot gates, manual application of new affiliates.
Inference. Paying for quality rather than lead is the best prevention.
What helps in practice (combinations of measures)
Rules + ML. Hard velocity filters and explainable ML scoring with manual debriefing of border cases.
Risk segmentation. Beginners, high-rollers, crypto/fiat - different control profiles.
Escalations and SLAs. Fast channel to game providers, PSPs, blockchain risk analysts.
Logging and reproducibility. Unchangeable logs of bets/rounds/payments; tracking by ID.
Communications. Clear T & Cs, pending/processing statuses, explainable failures indicating rule clauses.
Legal hygiene. Regular STR/CTR, license compliance (MGA/UKGC/Curacao, etc.), data storage and access minimization policy.
Antifraud effectiveness metrics
DR (Detection Rate) for confirmed cases.
FPR (False Positive Rate) - false positives (keep low).
Chargeback Ratio и Recovery Rate.
Bonus Abuse Rate (в т.ч. per campaign).
Time-to-Decision (speed of review without compromising quality).
On-chain Risk Exposure (crypto).
Affiliate Quality Score (LTV/deposits/retention).
As a conscientious player not to fall under the "mill" of anti-fraud
Do not use a VPN/proxy. Geo-inconsistencies are a common cause of inspections.
Keep consistency. One device/browser, correct timezone, real data.
Cook KYC in advance. Clear photos of documents, matching addresses, without "editing" images.
Follow the bonus rules. Max bet under the bonus, contribution of games, terms - screen the conditions.
One-way payments. Replenish and withdraw using the same method/wallet, do not use other people's cards.
Keep correspondence in one thread. Capture round/transaction IDs - this speeds up the review.
Frequent questions (mini-FAQ)
Can they refuse to withdraw "for no reason"?
The clause of the rules/license and, if necessary, the risk justification should be indicated. Ask for specifics and ID of checks.
How long does the hold on verification last?
Depends on the amount/risk/payment method. Transparent operators publish SLAs and status trackers.
What happens to stolen funds?
Deposits deemed fraudulent are generally returned to the holder; illegally obtained winnings are canceled by T & Cs.
Is it possible to prove collusion in live?
Yes: by betting logs, timing, video, action correlation and link graph.
The fight against fraud is not a "secret button," but systematic work at the intersection of technologies, procedures and licenses: fingerprint + behavior + graph + payment and KYC/KYT checks. Real cases show: it is the combination of measures that works, and not one miracle rule. For an honest player, the key is simple: transparent data, compliance with conditions, lack of proxy tricks and readiness for verification. For the operator - clear T & Cs, explainable solutions and minimization of false positives. So the industry remains safe and predictable in the process - without romanticizing the "gray schemes."