Identity Scoring

A confidence score is maintained to allow for a risk-based approach to identification. In the event of significant changes the score will drop and require an additional authentication factor from the account holder.

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Identity Based Confidence Risk

An Identity-based Confidence risk model, as opposed to a traditional credit-based approach, integrates seamlessly into existing risk engines to provide more accurate outcomes by focusing on the user's verified identity. This innovative method helps our clients make better-informed decisions, reduce fraud, and enhance overall security while maintaining a smooth customer experience.

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Reduces False Declines

Digid's Identity Scoring virtually eliminates false declines because our solution focuses on identifying the customer as opposed to creating a set of rules that are meant to establish whether a transaction is fraudulent or not.

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Most Inclusive

Not racist or classist etc. because we only care that the user is the user...Credit scores measure credit risk and so fraud risk systems often create a false decline and this traditionally affects minority and lower income communities.

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Stronger Over Time

Digid's Identity Scoring gets cumulatively stronger with every customer transaction across ANY client that uses Digid, for example, different banks, whether it is payment transactions, wire transfers, or simple logins.

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Real-Time Multi Signal Data Monitoring

Gathering data from multiple signals such as the connected network, fuzzy geolocation, device platform attributes, user biometrics, and verifiable credentials validated at initial onboarding builds a robust profile without invading PII. Data signals are monitored continuously during ongoing user authentications and identity verifications keeping the profile up to date as the user transacts online.

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Step-Up Authentication

If the confidence score decreases to a YELLOW or cautious range because an anomaly has been detected (e.g. location changed, first time device, change in address etc.) additional factor(s) can be requested to confirm identity of the user and bring the score back into normal range. Rules are configurable by the client institution.

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Tunable for Use for Your Specific Needs

Digid's Identity Scoring system is customizable and tunable for the specific needs of our clients so it takes into account more of what they consider key. Variables such as geolocation, device data, transaction times, transaction amounts and so on can be configured to impact the confidence score based on the service provider's own rules.


A demo is worth a 1,000 words...

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