Facial Recognition
Powered by in-house-developed technology, our facial recognition solution delivers unmatched accuracy, speed, and fairness, proven in real-world environments.
Powered by in-house-developed technology, our facial recognition solution delivers unmatched accuracy, speed, and fairness, proven in real-world environments.
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Our facial recognition technology uses advanced machine learning (ML) models to compare images with ID photos or previously captured pictures. This ensures accurate verification and fortifies fraud prevention, maintaining a seamless user experience.
Identifies, isolates, and analyzes unique facial features from an image or video for subsequent analysis, often within milliseconds.
Analyzes and identifies unique features, facial patterns, and characteristics, ensuring accurate recognition, no matter the expression or lighting.
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Converts extracted features into a numeric representation of the facial biometrics. This becomes a unique “facial signature.”
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Securely encrypts the vector into a format that can only be opened and interpreted with the correct decryption key.
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Compares face templates extracted from a selfie or an ID image against another template (1:1) or against a database of templates (1:N).
Our pioneering technology is powered by globally inclusive and diverse training data, resulting in high recognition accuracy regardless of ethnicities, age, gender, or environmental conditions.
Achieve fast and frictionless verification with outstanding accuracy.
Incode’s facial recognition models are NIST-certified and top ranked in FRTE benchmarks for 1:1 verification and 1:N identification, tested on millions of images for accuracy and fraud detection.
success rate in spotting and blocking fraudulent selfies
Verifications processed in 20 milliseconds
ISO (30107-3)
Certified against biometric spoofing and presentation attacks
success rate in identifying and passinggenuine selfies
Recognized as a top remote identity validation provider by the Department of Homeland Security
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1:1 verification
What it is: A selfie is compared to a single reference photo (e.g., from a government-issued ID) to confirm that both belong to the same person.
How it might be used: When a user opens a new bank account online, Incode compares their selfie to the photo on their government-issued ID. This proves ownership of the ID by the user, preventing impersonation and meeting compliance requirements.
1:N identification
What it is: A single face image is compared against a database of many enrolled profiles to find a match or confirm that no match exists.
How it might be used: A financial institution checks a new customer’s selfie against its database of existing clients to ensure the person is not already enrolled under another identity. This prevents duplicate accounts, fraud, and compliance violations.
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Personalize and simplify your services with accurate facial recognition, built on Incode’s advanced ML models.
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