Correlation between influencer reputation laundering and betting data contamination

When information sources within a platform re-emerge under pseudonyms after engaging in past misconduct, recurring patterns show that previously tainted data channels become reactivated. This goes beyond a simple ethical issue, as unverified and misleading information originating from unreliable sources can distort both market confidence in betting odds and the integrity of data flows, creating a structural risk across the system.

From an operational perspective, there is a need for an architecture that proactively filters abnormal data linkage by cross-verifying account histories of information emitters against their past promotional and behavioral patterns. This helps identify whether suspicious continuity exists between new identities and previously flagged entities.

In your platform, what primary identification logic do you prioritize to block the re-entry of such disguised sources within the Oncastudy platform?