All modules

    Uniqueness Identification

    One customer. One golden record. Across everything.

    Fuse deterministic and fuzzy matching with biometric, device and behavioural signals to maintain a single golden record per real-world person or business — across products, brands, entities and jurisdictions.

    Identity match · live
    JAS
    John A. Smith
    DOB 14-03-1986
    JS-3142
    JS
    J. Smyth
    DOB 14-03-1986
    JS-9987
    Match · 97%
    Name
    92%
    DOB
    100%
    Face
    96%
    Device
    100%
    Address
    88%
    Phone
    94%
    Self-excludedAction: BLOCK

    Signals

    Four layers of evidence. One probabilistic verdict.

    Identity attributes

    Name, DOB, government ID, tax ID, address, email, phone.

    Biometrics

    Face-match against historical KYC photos to catch resurrected accounts.

    Device & network

    Device fingerprint, browser entropy, IP, geolocation, behavioural cadence.

    Relationships

    Shared payment instruments, beneficial owners, agents — fed by ComplyLink.

    Use cases

    Where Uniqueness pays for itself in week one.

    Self-exclusion enforcement

    Block re-registration of self-excluded customers across brands and jurisdictions in real time.

    Multi-accounting & bonus abuse

    Detect customers running multiple accounts to game promotions, free bets or referral programmes.

    Synthetic identities

    Score combinations of real and fabricated attributes that look human but don't belong to any real person.

    Sanctions evasion

    Catch sanctioned individuals re-onboarding under spelling variants, transliterations or partial-data submissions.

    Fraud rings

    Surface clusters of accounts sharing devices, payment cards, or behavioural patterns — even when names differ.

    Group-wide AML

    Maintain a single customer view across subsidiaries, brands and product lines for consolidated risk.

    <100ms

    Real-time onboarding lookup latency

    11×

    Average increase in self-exclusion catch rate

    98.4%

    Precision on benchmark synthetic-identity dataset

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