Detect multi-accounting and prevent revenue loss

Multi-accounting is one person operating multiple accounts on the same platform to gain an advantage they couldn't get with a single identity. It usually shows up as:

• Free-trial and freemium cycling: fresh accounts to reset usage limits or trial windows
• Referral and bonus abuse: self-referrals and signup bonuses claimed across many fake accounts
• Ban and self-exclusion evasion: new identities created to get back in after a ban
• Account farms: bulk accounts run at scale to harvest rewards or resell access

Standard detection misses it because the same person rotates IPs, clears cookies, and uses anti-detect browsers to look like a new visitor every time. ShieldLabs links those accounts back to one persistent identity, so repeat sign-ups are detected as one Multi-accounting High-Risk Event instead of separate strangers.

Most platforms still get multi-accounted because the controls they rely on each break in a predictable way. The common gaps:

• IP blocking: residential proxies rotate addresses constantly, and banning a shared egress IP hurts legitimate users on the same network
• Email filters: disposable email services cycle fresh addresses faster than any blocklist can catch them
• Basic fingerprinting: anti-detect browsers spin up isolated profiles built specifically to defeat it
• Session-by-session tools: most fraud tools treat each visit independently, so every fresh sign-up looks like a brand-new user

ShieldLabs closes that gap by building a persistent identifier that survives IP rotation, cleared cookies, and anti-detect browsers, then linking accounts that share it.

ShieldLabs detects multi-accounting by building a persistent identity for each visitor and linking the accounts that share it. It works in three layers:

• Identify: 300+ signals across the device, OS, browser, and network layers resolve to a stable VisitorID and DeviceID, even after IP rotation and cleared cookies
• Link: when a user is known, your client passes a UserHID that ties the technical fingerprint to an actual account in your system
• Detect: when several accounts resolve to the same identity, ShieldLabs detects a Multi-accounting High-Risk Event with Medium or High confidence

ShieldLabs returns the identification and the risk signals with a 0–100 Risk Score on the first visit, and flags multi-accounting across sessions, so your team no longer chases one session at a time.

Yes. ShieldLabs returns a Risk Score and identity match on the first visit, so a repeat sign-up is flagged at the moment of account creation rather than after the abuse lands. At signup it works like this:

• Add the JavaScript snippet to your signup flow
• Pass a UserHID, a hashed identifier that links the technical event to the new account
• If that identity already maps to other accounts, the Multi-accounting event appears immediately with its confidence

ShieldLabs flags the risky sign-up at the point of entry and helps block fraudulent and abusive accounts, so you can choose the action for each case: allow, challenge, or hold.

Integration takes about 5 minutes, and the first Risk Score lands on the very first visit. The setup:

• Add the JavaScript snippet at signup, login, or any sensitive action point
• Set up your domain in the analytics dashboard, no backend changes required to start
• Watch results populate live: High-Risk Events over time, per-visitor Risk Scores, and identity dimensions

ShieldLabs delivers the same data through the analytics dashboard, the API, and Webhooks, so you can start by watching High-Risk Events and later act on the results in your backend.

ShieldLabs stops multi-accounting by flagging risky users and helping block fraudulent and abusive accounts, and you choose the action for each case. How it works:

• ShieldLabs provides: a 0–100 Risk Score, the risk signals, and Multi-accounting High-Risk Events with Medium or High confidence
• Ready out of the box: detection works from the first visit, with no rule setup
• You choose the action: allow, challenge, or block each case in your backend, so legitimate users who share a device or network keep access

ShieldLabs gives your team clear evidence to act with confidence on every case.