* Uses various sophisticated heuristics to detect real vs fake IDs.
* Matches the ID to the human face.
* Detects whether the human face is live or not.
* Dynamically requests more or less information depending on the confidence level.
It also gets better over time based on the attacks and fraud attempts that Stripe itself sees.
We’re exploring different options for scanning IDs like Anyline and BlinkID right now, but this looks incredibly well suited for what we’re building and would save us a tremendous amount of time if it works.
• Document detection
• Blur and glare detection
• Tool-tips during the user flow
Those are 4 great bullets btw. They helped me understand the service a lot more than the landing page for identity. Might want to consider a view like this.
This means it will fail for a few individuals and you will be stuck trying to reach support who are going to be pointless and useless.
Mostly this will be an issue with people of non-white ethnic origins and people with older laptops/phones with poorer cameras.
This is obviously a useful product, but it is one the world would be much better of if it didn't exist at all.
> Document checks verify the authenticity of government-issued identity documents. Stripe uses a combination of machine learning models, automated heuristic analysis and manual reviewers to verify the authenticity of hundreds of different document types.
> Selfie checks look for distinguishing biological traits, such as face geometry, from a photo ID and a picture of your user’s face. Stripe then uses advanced machine learning algorithms to ensure the face pictures belong to the same person.
> ID Number checks provide a way to verify a user’s name, date of birth, and national ID number. Stripe uses a combination of third-party data sources such as credit agencies or bureaus, utility or government-issued databases and others to verify the provided ID number.
> Match the ID photo with selfies of the document holder
> Validate SSN and addresses against global databases
Seems fairly clear.