Bonus Abuse Prevention
Bonus abuse prevention.
Reward real customers.
Repeat accounts and bots can claim welcome rewards meant for new customers. ShieldLabs detects multi-accounting and automation so repeated claims stop consuming your incentive budget.
Start FreeClaim your welcome bonus
A reward for new customers.
Anti-Detect BrowserProxy
Protect bonus budgets
Keep repeated claims from consuming rewards meant for new customers.
Acquire genuine customers
Keep linked account farms from inflating the growth generated by your offers.
Protect every incentive
Stop the same abuse from spreading across bonuses, trials and referral rewards.
Reward trusted customers
Keep good customers moving through offers without unnecessary checks.
Repeated reward claims
Protect your bonus budget.
Stop repeat claims.
ShieldLabs detects multi-accounting among accounts created with different email addresses. Keep welcome bonuses, deposit offers and introductory credits for eligible customers, with account-count filters to focus your investigation.
Automated claims
Stop automated bonus farming.
Keep offers open to customers.
Bots can submit reward claims at scale. Receive browser automation detections and the identification’s risk assessment to help protect bonus enrollment and redemption.
Expose disguised bonus claims
Detect proxies and anti-detect browsers around bonus requests.
Find abusive campaigns
See the channels, referrers and UTM campaigns bringing risky bonus traffic.
Protect reward access
Detect account takeover around customer sign-in and bonus redemption.
The ShieldLabs platform
More than a redemption.
The users behind the claims.
Combine multi-accounting detection with identification, device and network intelligence, bot detection, risk signals, scoring and traffic analytics.
Enterprise-level functionality. Without enterprise pricing.
Accurate identification
Recognize returning visitors even when they clear cookies, use incognito mode or change their IP address. Detect linked users with different email addresses.
Identification accuracy
High-Risk Event detection
Detect account abuse out of the box by automatically identifying linked users. No fraud model training is required.
Risk signals
Get ready-made detections of automation, masking and spoofing, with named risk signals behind each result.
Bot & AI traffic detection
Detect bot activity from browser automation signals. Recognize useful crawler and AI traffic alongside abuse detections.
Risk scoring
Score every visit from 0 to 100 and classify it as trusted, suspicious or dangerous. See the signals behind each score.
Device fingerprinting
Recognize devices by their fingerprints. Identify the browser, operating system and device type. Detect headless browsers and tampering.
IP & Network Intelligence
Reveal the real IP address and geolocation behind masking. Detect VPNs, proxies and private relays.
203.0.113.42198.51.100.23Traffic quality scoring and risk analytics
Get one score for all your traffic and ready-made quality results by source, channel, referrer and UTM campaign.
Analytics dashboard
Find multi-accounting.
Protect customer rewards.
See detected multi-accounting, associated users and devices, named risk signals and identification risk assessments. Find the channels, referrers and campaigns bringing risky traffic.
How it works
Start protecting your product.
Connect once and start receiving ready-made fraud and abuse detections.
- 01
Add the snippet or SDK
Connect your product and start identifying visitors and users.
- 02
Receive ready-made detections
Get detected fraud and account abuse in the dashboard or through API integrations.
- 03
Prevent fraud and abuse
Protect customer accounts, paid access and signup incentives in your product.
Developers
Integrate in
5 minutes.
A single API to identify, detect and score. Receive risk data through API responses and webhooks. Integrate selected data points into your business logic to prevent fraud and abuse.
Protect your users and product
Make abuse visible.
Keep genuine users moving.
Start Free FAQ
Understand the evidence.
Put it to work.
What is bonus abuse?
Bonus abuse is repeated or automated participation intended to obtain rewards beyond a promotion’s eligibility limits, often through multiple accounts.
How does ShieldLabs help prevent bonus abuse?
ShieldLabs detects multi-accounting, bots, proxies and anti-detect browsers around bonus activity. Help protect welcome rewards and identify the acquisition sources bringing risky traffic.
Can different emails hide repeated claims?
Different account labels can still be linked through identified activity and other evidence. The account names in the illustration are supplied by your product.
Does ShieldLabs read promotion eligibility automatically?
Promotion codes, eligibility and redemption status come from your product. ShieldLabs supplies identity, risk and account abuse evidence for that workflow.
Can I use the same approach for trials and referral rewards?
Yes. Ready-made account abuse detections can support trials, promotions and referral rewards as well as welcome bonuses.
Can this help protect deposit bonuses and reward redemption?
Yes. Multi-accounting and bot detection help protect introductory bonus eligibility. Account takeover detection adds protection around customer access and sensitive reward actions.
Can this help with bonus abuse in gambling products?
Yes. ShieldLabs detects repeated registered accounts and bots around browser-based player signup and bonus claims. Wagering outcomes, deposit eligibility and bonus terms remain in the gambling product.