Streamlined 1:1 Face Match with Didit WebView Integration

Effortless IntegrationImplement Didit's 1:1 Face Match into your mobile applications using WebView, providing a smooth and secure identity verification flow for users.

Robust SecurityLeverage Didit's advanced biometric verification, including powerful 1:1 Face Match and Passive & Active Liveness, to prevent identity fraud and deepfake attacks effectively.

Configurable WorkflowsCustomize verification thresholds and warning handling for face match scores, allowing you to define review and decline conditions tailored to your specific risk appetite.

Didit's AdvantageBenefit from Didit's AI-native platform, modular architecture, and Free Core KYC, making high-security identity verification accessible and developer-friendly without setup fees.

Understanding 1:1 Face Match in Identity Verification

1:1 Face Match is a cornerstone of modern identity verification, ensuring that the person presenting an identity document is indeed its legitimate owner. This process involves comparing a live image or video of a user with the portrait extracted from their ID document. The goal is to establish a high level of confidence that the individual is who they claim to be, thereby preventing various forms of identity fraud. In an increasingly digital world, where remote verification is common, the accuracy and reliability of 1:1 Face Match are paramount.

A successful 1:1 Face Match confirms the authenticity of the user's identity, providing a critical layer of security for onboarding, access control, and transaction authorization. It works in tandem with other verification steps, such as document authenticity checks and liveness detection, to create a comprehensive security posture. The advanced algorithms used in these systems analyze facial features, ensuring consistency between the presented face and the reference image, even accounting for natural aging or minor appearance changes.

The Power of Didit's 1:1 Face Match Technology

Didit's 1:1 Face Match technology is built on advanced AI, offering highly accurate and reliable comparisons. Our system not only generates a similarity score between the live image and the document photo but also integrates seamlessly with Passive & Active Liveness detection to ensure the user is a real, present individual and not a deepfake or spoof. This multi-layered approach to biometric verification is essential for combating sophisticated fraud attempts.

The Face Match process involves several critical steps: first, extracting a high-quality portrait from the identity document using Didit's ID Verification capabilities (including OCR and MRZ scanning). Second, capturing a live image or video of the user, often guided by our Liveness detection. Finally, comparing these two images to produce a detailed report. This report includes a similarity score (ranging from 0-100) and any relevant warnings, such as LOW_FACE_MATCH_SIMILARITY if the match score falls below predefined thresholds. Didit's modular architecture allows developers to easily integrate this powerful feature into their existing workflows.

Integrating Didit's Face Match via WebView

For applications where native SDKs might not be the primary integration path, Didit offers flexible integration options, including WebView. While native SDKs (for iOS, Android, React Native, and Flutter) provide the best user experience, NFC capabilities, and optimized camera access, WebView remains a viable option for certain platforms like Xamarin or Cordova, or when a quick, cross-platform deployment is prioritized. Integrating Didit's 1:1 Face Match through WebView is a straightforward process, designed to minimize development effort while maximizing security.

The architecture for WebView integration typically follows these steps: Your backend initiates a verification session via Didit's API, receiving a unique verification_url. Your mobile application then opens this URL within a WebView. The user completes the verification steps, including the 1:1 Face Match and liveness checks, all within the WebView interface. Upon completion, the WebView navigates to a predefined callback URL, which your app intercepts to signal the end of the verification flow. Concurrently, your backend receives comprehensive results via webhooks, allowing for robust processing and decision-making. Didit ensures that even with WebView, the user experience is intuitive and secure, guiding them through the necessary biometric captures.

Handling Face Match Results and Warnings

Didit provides a detailed Face Match report, allowing you to parse critical information such as the verification status (Approved, Rejected, In Review), the similarity score, and temporary URLs for the source and target images. Critically, the report also includes a warnings array, which flags potential issues. For instance, a LOW_FACE_MATCH_SIMILARITY warning indicates that the facial features do not closely match, suggesting a potential identity mismatch. Another common warning is NO_REFERENCE_IMAGE, which automatically declines the verification if a comparison image is missing.

A key advantage of Didit's platform is the configurability of verification settings. You can define custom thresholds for face match scores: a 'review threshold' might flag sessions for manual inspection if scores fall below a certain point, while a 'decline threshold' can automatically reject sessions with unacceptably low scores. This granular control allows businesses to tailor their risk management strategies precisely. It's also important to note the security best practice: the image URLs provided in the report are temporary and expire after 60 minutes, encouraging applications to store only verification statuses and scores, minimizing biometric data retention. This focus on data security and configurable workflows positions Didit as an industry leader in biometric verification.

How Didit Helps

Didit is revolutionizing identity verification with its AI-native, developer-first platform. For 1:1 Face Match and WebView integration, Didit stands out by offering an open, modular identity layer that businesses can easily plug into their existing systems. Our 1:1 Face Match & Face Search capabilities provide highly accurate biometric comparisons, complemented by Passive & Active Liveness detection to guard against sophisticated fraud, including deepfakes. This ensures that the person you're verifying is not only the document holder but also physically present and real.

Didit's advantages extend beyond just technology. We offer Free Core KYC, enabling businesses to get started with essential identity checks without upfront costs. Our modular architecture means you can compose verification workflows with ease, integrating only the identity primitives you need. With clean APIs, an instant sandbox, and comprehensive public documentation, developers can quickly integrate and deploy robust identity solutions. Furthermore, Didit’s orchestrated workflows and no-code Business Console automate trust, reducing the need for manual reviews and streamlining operations. Whether you're integrating via WebView or our native SDKs, Didit provides a secure, scalable, and cost-effective solution for all your identity verification needs.

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