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Fraud solutions for a multi-dimensional view of identity risk.

Sigma Identity Fraud machine learning models are purpose-built for specific industries, trained with feedback data from a consortium of clients to tackle targeted fraud patterns and produce real-time actionable risk scores and reason codes.

Socure's approach to data science allows for flexible, advanced iteration boosted by network consortium and feedback data.

95% or higher fraud capture rate for the riskiest 10% of users, on average.

Industry-specific models for credit card, lending, DDA, telco, money transfers, and more.

Additional Fraud Products

Email Risk

Socure ID+ email risk models predict the risk of an email and its correlation to an identity considering hundreds of data elements. Predictive factors include deliverability, age of the email, domain type, and alternative emails linked to an identity.

Phone Risk

Socure ID+ phone risk models predict the risk of a phone number utilizing various risk intelligence and phone number attributes. Predictive factors include how often the phone number has been ported, length of subscriber tenure, and if the number is a VoIP.

Address Risk

Socure ID+ address risk models predict the risk of an address utilizing various risk intelligence and residency attributes. Predictors factors include deliverability, length of time at an address, property type, as well as links between an identity and alternative addresses.

Alert List

Socure’s consortium database of known first- and third-party perpetrators and fraud outcomes, tagged by industry vertical or segment, is an additional source of data in the decisioning process to accept, reject, or review consumer applicants.

Ready to see the power of Socure?

Request a demonstration or simply contact our sales team to learn more about Socure.

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