Detecting duplicate accounts and self-exclusion with facial recognition on AWS
A single bettor creating multiple accounts to get around deposit limits, dodge welcome bonuses, or bypass a self-exclusion block is a problem that Brazilian betting regulation treats seriously. Detecting this behavior requires more than checking a tax ID or email; it requires identifying the person behind the registration.
Why aren’t tax ID and email enough?
A bettor determined to break the rules can create multiple accounts using family members’ documents, disposable emails, and slightly altered data. Verification systems that rely only on textual registration data have difficulty identifying that two or more seemingly distinct accounts belong to the same physical person.
How does facial recognition solve this problem?
Amazon Rekognition makes it possible to compare the facial image captured during a new registration with the image database of accounts already existing on the platform, identifying matches even when the textual data provided is different. This makes it possible to detect attempts to create duplicate accounts with false identities, something that traditional verification based only on documents cannot capture on its own.
The critical role in self-exclusion compliance
Self-exclusion is a regulatory mechanism that allows a bettor to voluntarily block themselves from betting, an important protection for responsible gaming. If a self-excluded bettor manages to create a new account with slightly different data, the platform fails a serious regulatory commitment. Facial recognition adds a verification layer that identifies the person physically, regardless of the data provided in the new registration, reinforcing the real effectiveness of the block.
How does this connect with risk management?
Beyond blocking duplicate and self-excluded accounts, this same recognition mechanism feeds risk management systems, flagging suspicious behavior patterns among related accounts for deeper analysis. This strengthens the operator’s ability to identify organized fraud, not just isolated attempts.
Implementation with data governance
Working with biometric data requires extra attention to the LGPD. Well-designed architectures store and process this information with encryption, strict access control, and within the AWS São Paulo Region, meeting the data residency requirements of Brazilian regulation.
CloudDog implements facial recognition architectures with Amazon Rekognition for iGaming operators, strengthening self-exclusion compliance and duplicate account detection with security and compliance. Get to know our complete Cloud for iGaming solution and reinforce the integrity of your bettor base.
