Synthetic Scores

SentiLink's models are trained on fraud insights, not performance.
As a result, our synthetic scores are renowned for precision and best-in-class
false positive rates.



Detect synthetic identities with
unparalleled accuracy

Start with multiple data sources

There are over 300M consumers in the U.S. Data on when they applied for credit, what credentials they used when applying, married with a large collection of data elements associated with those consumers is the foundation. This, combined with the unique consortium data shared across our partners is the starting point for evaluating identities. 

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Fuse the data with human intelligence

SentiLink brings intelligence, people and data together to empower one another. Intelligence comes from our Risk Operations team who applies deep knowledge of known synthetic identities. Nuances and edge cases are identified that technology can’t catch.

Define model targets based on fraud insights

The clean, consistent, and clearly defined fraud labels applied by our Risk Operations team to subtle differences in synthetic identities differentiates our solutions. These insights based on what fraud looks like is what trains our model to catch significantly more synthetic fraud with a much lower false positive rate.

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Three Synthetic Scores

Composite Synthetic
Composite synthetic fraud score that indicates whether an identity is likely synthetic.
First Party Synthetic
Detects applicants using their true name and date of birth, but an SSN that doesn’t belong to them. They are manipulating their true identity.
Third Party Synthetic
Identifies applicants using a name, date of birth and SSN combination that is completely fabricated.

Synthetic Score Delivery

Real-Time API

Integrate easily to our single endpoint API and get scores in milliseconds.

Batch Upload

Batch can occur with an SSH File Transfer Protocol (SFTP) or upload data manually to the SentiLink dashboard.

Dashboard

Intelligent UI that surfaces the most important attributes for investigation.


Let’s work together to stop synthetic fraud