Performing 1:1 Face Match with Didit's JS SDK
Blog post from Didit
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Didit’s 1:1 Face Match service uses its JavaScript SDK to help web applications verify that a live selfie belongs to the holder of an identity document. The process combines passive and active liveness detection to identify spoofing attempts such as photos, videos, and deepfakes, then compares the live image with a portrait extracted from an ID using document-verification tools including OCR, MRZ, and barcode scanning. Verification responses provide a status, a similarity score from 0 to 100, temporary image URLs, and warnings such as low similarity or missing reference images. Businesses can configure thresholds that route uncertain cases to manual review or automatically decline them according to their risk tolerance. Didit presents the service as a modular identity platform that can operate alone or alongside ID verification and AML screening, while recommending that customers retain only statuses and scores to limit biometric-data storage. The company offers clean APIs, a no-code business console, free core KYC, no setup fees, and a pay-per-successful-check model.
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