Kavra LabPOST /bonus/claimBlockedWelcome bonus claimed by a known ring
- Device linked to 9 accounts
- Fingerprint rotated 6 times
- Mobile proxy, same city as ring
Risk93
Industry
iGaming fraud prevention that stops bonus hunters, not players
iGaming fraud is abuse of online casinos and sportsbooks for money the rules never meant to pay: welcome bonuses claimed by one person many times, colluding accounts, arbitrage bots, stolen accounts and laundered withdrawals. Kavra assesses every signup, login, bonus claim and withdrawal, links accounts run by one actor, and tells your backend what to do.
- Who it hits
- Online casinos, sportsbooks, poker, lotteries
- What it costs
- Bonus budget, margin, chargebacks, license risk
- Tools used
- Antidetect browsers, proxies, bots, emulators
- Where to stop it
- Signup, bonus claim, bet, withdrawal
What iGaming fraud looks like today
Online casinos and sportsbooks hand out value before they know who a player is. A deposit match, free spins, a risk-free first bet or an odds boost is money on the table from the first minute. That makes the industry a prime target for organized abuse, and most of it does not look like classic theft. It looks like many new players who each follow the rules once.
Behind those players is often one operator, or a small team, running dozens of accounts. They use antidetect browsers to give every account its own device, residential and mobile proxies to give it a local home address, and scripts to claim, wager and withdraw on a schedule. Others go after existing players: stolen logins, drained balances and changed payout details. A third group uses the platform to move money or to beat the odds with software.
The threats that hit casinos and sportsbooks
Each threat has its own moment in the player journey, and its own cost.
| Threat | Where it strikes | Business impact |
|---|---|---|
| Bonus abuse and multi-accounting | Registration, first deposit, bonus claim | Acquisition budget paid to the same person many times |
| Gnoming | Registration and bonus claim, often with borrowed identities | Bonuses farmed through accounts in other people's names |
| Chip dumping and collusion | Poker tables, peer-to-peer games, exchanges | Unfair games, laundered funds, player trust lost |
| Arbitrage and matched betting bots | Odds pages, bet placement, promotions | Margin lost to riskless bets placed by software |
| Account takeover and credential stuffing | Login, password reset, payout details change | Drained balances, refunds, support load, complaints |
| Payment fraud and card testing | Deposit, card add, withdrawal | Chargebacks, fees, pressure from payment partners |
| Self-exclusion evasion | Registration and login | Regulatory breach and harm to vulnerable players |
| Odds scraping and API abuse | Odds feeds, live betting endpoints | Pricing copied, infrastructure load, latency for real bettors |
Where to check: the player journey, touchpoint by touchpoint
Fraud in iGaming is a sequence. Checking only at withdrawal is too late; checking only at signup misses accounts that turn bad later.
- 01
Registration
The best place to catch fake accounts and repeat bonus hunters. Look at the device, the network and whether this actor already has accounts, before a bonus is attached.
- 02
Login
Compare every login with the account's own history: known device or new one, usual network or a proxy, a plausible location or impossible travel. This is where takeovers start.
- 03
Deposit and card add
Watch for many cards tried in a row, small test amounts, and cards shared across unrelated accounts.
- 04
Bonus claim and free bets
Re-assess the actor at the moment value is granted. An account that looked clean at signup may now share a device with twenty others.
- 05
Betting and play
Automated bet placement, bets that always hit the best price across books, and players who always sit at the same tables with the same partners.
- 06
Withdrawal and payout change
The last point to stop value leaving. Check for new devices, changed payout details and many accounts paying out to one wallet or card.
Abuse patterns specific to gambling
Some schemes only exist where money is wagered. They need signals across accounts, not a verdict on one session.
Gnoming
Accounts opened in the names of friends, relatives or bought identities, then run by one player. Documents pass KYC because they are real. The device and behavior behind them are shared.
Chip dumping and collusion
One account loses to another on purpose to move funds, or partners share information at a table. Look for the same small group of accounts meeting again and again, often from linked devices.
Arbitrage and matched betting
Arbitrage betting locks in profit by backing every outcome across books. Bots scan odds and place bets in seconds, often through headless browsers or scripted clients.
Self-exclusion evasion
A player who excluded themselves opens a new account with a variation of their details. The device and household they return from often stay the same.
Mobile app farms
Bonus hunters run app accounts on emulators and device farms to look like many phones. Emulated sensors and shared hardware give them away.
Withdrawal abuse
Deposit, wager the minimum on low-risk bets, withdraw. Or deposit with a stolen card and cash out to a clean wallet before the chargeback lands.
Regulation, KYC and the friction problem
Licensed operators carry duties that most online businesses do not. Regulators such as the UK Gambling Commission expect identity and age checks, anti-money-laundering controls, affordability and safer gambling measures, and respect for self-exclusion schemes like GAMSTOP. Failing them can cost fines and licenses, not only money.
KYC answers one question: is this document real and does it belong to the person holding it? It does not answer whether the same person is already behind ten other accounts, whether the session is a script, or whether the login is really the account owner. It is also expensive and adds friction, so running it on every visitor early in the funnel hurts conversion.
Device and behavior intelligence fills that gap. Kavra does not replace KYC or AML screening. It tells you which registrations and withdrawals deserve a closer look, surfaces links between accounts that documents cannot show, and lets clean players move through without extra steps.
KYC and device intelligence answer different questions
| Question | KYC and document checks | Kavra |
|---|---|---|
| Is this a real, adult person? | Yes, from the document | No, that stays with KYC |
| Is one actor behind several accounts? | Only if the same name is reused | Yes, from shared device, network and behavior |
| Is the session a bot or a spoofed device? | No | Yes, on every visit |
| Is this login the usual owner? | No | Compared with the account's trusted devices and history |
| Should this player be stepped up now? | Usually runs once, at a fixed point | Assessed at each touchpoint, invisibly |
What good iGaming fraud protection looks like
Casinos and sportsbooks compete hard for players, so protection that blocks too much costs as much as fraud. The aim is to keep the honest majority moving and to put friction, delays or reviews only where evidence points.
- Every registration assessed before a bonus is attached, including app installs.
- Accounts linked by the real device and network behind them, even when fingerprints rotate and VPNs or Tor hide the address.
- Logins compared with each player's own trusted devices, with step-up only on real anomalies.
- A fresh check at bonus claim and withdrawal, not only at signup.
- Self-excluded players recognized when they return on the same device or household.
- Clusters reviewed as a whole, so a ring is closed at once instead of account by account.
- Clear reasons on every decision, so risk, payments and compliance teams can act and explain.
Sources
- UK Gambling Commission: Identity verification requirements for remote operators
- UK Gambling Commission LCCP 3.5.5: Remote multi-operator self-exclusion
- UK Gambling Commission: Online operators required to participate in GAMSTOP from March 2020
- GAMSTOP: Online self-exclusion scheme
- OWASP Automated Threats: OAT-019 Account Creation
- OWASP Automated Threats: OAT-008 Credential Stuffing
How Kavra helps
How Kavra protects casinos and sportsbooks
Kavra analyzes 3,000+ data points on every visit and returns an explained verdict at each step of the player journey. Your backend decides what happens next.
One actor, many accounts
Returning devices are recognized across registrations, so gnomes, bonus rings and self-excluded players returning on the same device surface as linked accounts.
Spoofed devices exposed
Antidetect profiles, emulators, virtual machines and device farms are caught by contradictions between what they claim and how they behave.
Proxy intelligence
Kavra measures real exit IPs of commercial residential and mobile proxy networks, so a local-looking address is seen for what it is.
Betting bots detected
Automation frameworks, headless browsers and scripted clients placing bets or scraping odds are flagged on the web and in the native apps.
Login and payout protection
Each login and payout change is compared with the player's trusted devices and history. Step up only when something is off.
Complements your KYC
Kavra adds device and behavior evidence to your KYC and AML checks. Start in observe-only mode and tune before you enforce.
FAQ
Frequently asked questions
Something else? Talk to our team.
What is the most common type of fraud in online casinos?
Bonus abuse through multiple accounts is the most widespread, because welcome offers pay out before a player's value is known. It often overlaps with gnoming, where accounts are opened in other people's names. Account takeover, payment fraud and collusion follow. The common thread is one actor hiding behind many accounts or someone else's identity.
How do sportsbooks detect arbitrage and matched betting bots?
They look at how bets are placed, not only which bets. Bots hit odds pages at machine speed, place stakes within seconds of a price change and run through automation frameworks or scripted clients. Kavra flags that automation and links the accounts it controls, while betting patterns stay with your trading team.
Does device intelligence replace KYC for gambling operators?
No. KYC confirms that a document is real and belongs to an adult, and licensed operators must run it. Device intelligence answers different questions: whether one actor runs several accounts, whether a session is automated and whether a login is the real owner. Used together, they catch gnoming and ring activity that documents alone miss.
Can a self-excluded player be stopped from opening a new account?
Operators check self-exclusion registers against the details a player enters, but determined players change those details. Recognizing the device and household they return from gives a second signal. Kavra can flag a new registration linked to an excluded account so your team can refuse it or review it.
How do you detect chip dumping in online poker?
Look for the same small group of accounts meeting repeatedly, one side losing large pots with weak play, and funds moving toward one account. Device and network links between those accounts make the case much stronger. Kavra supplies the links, and your game integrity team reviews the hands.
Will fraud checks slow down registration for real players?
They should not. Kavra runs invisibly in the page and the apps, with no CAPTCHA puzzles or visible challenges. Most players get an allow and never notice it. Only sessions with mixed evidence get an invisible challenge or a step-up, and you can delay the bonus instead of blocking the signup.
See who is really on your site.
Run Kavra on your own traffic in observe-only mode. No risk to your customers, and a clear report of the fraud it finds.