Use case — Fraud
Duplicate and multi-account detection
Catch the same face applying under different names.
The problem
Bonus abuse, ban evasion, and mule networks all rely on one person holding many accounts.
Modules used
Face search
Device and IP analysis
Duplicate and blocklist checks
The flow
What runs, in order
Each step is an independently configurable module with its own result on the decision object.
- 1
Step 1
1:N face search against your own verified population
- 2
Step 2
Device and IP signals correlated across the matched cluster
- 3
Step 3
Blocklist enforcement on confirmed repeat applicants
Outcome
What the team is left holding
A cluster view of linked applications rather than isolated approvals.
Related
More fraud use cases
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