Elevating Legacy Systems: Face Search via Didit's WebView

Bridging the GapLegacy systems often lack advanced biometric capabilities, creating security vulnerabilities and hindering user experience. WebView integration provides a practical solution to incorporate modern features like Face Search without extensive re-engineering.

Unlocking Advanced Fraud PreventionFace Search (1:N) is crucial for identifying duplicate accounts and preventing sophisticated fraud, enabling businesses to cross-reference new verifications against a database of existing or blocklisted users.

Seamless Integration with Didit's WebViewDidit's WebView integration method allows mobile applications, even those built on older frameworks, to easily embed a secure and compliant identity verification flow, including biometric checks.

Didit's AI-Native AdvantageDidit provides an AI-native, modular identity platform that simplifies the addition of powerful features like Face Search, offering a free core KYC and flexible, pay-per-successful-check pricing.

The Challenge of Modern Identity Verification in Legacy Environments

In today's digital landscape, robust identity verification is no longer a luxury but a necessity. Businesses face an escalating threat of fraud, account takeovers, and compliance breaches. Modern identity verification solutions, particularly those leveraging biometrics like face recognition, offer powerful defenses. However, integrating these cutting-edge technologies into existing legacy systems or mobile applications built on older frameworks can be a significant hurdle. Full-scale overhauls are costly, time-consuming, and often impractical.

Many organizations operate with infrastructure that, while stable, wasn't designed for the dynamic demands of real-time identity checks and advanced fraud detection. This creates a dilemma: how to enhance security and user experience with state-of-the-art tools like Face Search (1:N) without disrupting core operations or embarking on a complete technological migration. This is where strategic integration methods become invaluable, allowing businesses to layer new capabilities onto their existing stack efficiently.

Understanding Face Search (1:N) and Its Importance

Face Search (1:N) is a powerful biometric capability that compares a newly captured face against a database of many previously verified or blocklisted faces. Unlike 1:1 Face Match, which verifies if a person matches a specific known identity, 1:N Face Search aims to identify if the person is already known within a larger dataset. This capability is absolutely critical for:

• Duplicate Account Prevention: Identifying users attempting to create multiple accounts using different credentials but the same biometric identity. This is vital for fair play in gaming, preventing bonus abuse, and maintaining data integrity.
• Fraud Detection: Catching individuals who have previously been blocklisted or identified as fraudsters trying to re-enter a system. Didit's Face Search can automatically check against your face blocklist, flagging suspicious activity instantly.
• Enhanced Security: Adding an extra layer of biometric security to account access or high-value transactions, ensuring that the person interacting with your service is indeed the registered user and not an imposter.
• Compliance: Meeting regulatory requirements that demand robust identity assurance and fraud prevention measures.

Didit's Face Search provides detailed reports, including similarity percentages, session IDs of matched verifications, and user details, enabling thorough fraud investigation. Configurable settings like similarity thresholds and handling of multiple faces allow businesses to fine-tune the detection to their specific risk appetite.

Integrating Advanced Biometrics via WebView

For mobile applications, especially those built on frameworks that might not natively support the latest SDKs or those needing a quicker integration path, WebView offers a pragmatic solution. Didit's WebView integration allows businesses to embed the entire identity verification flow, including ID Verification, Passive & Active Liveness, and 1:1 Face Match, directly into their existing mobile apps. This means that users can complete their verification journey within the app's native environment, experiencing a seamless flow without being redirected to an external browser.

The process is straightforward: your backend initiates a Didit session, which returns a unique verification_url. Your mobile app then opens this URL within a WebView. The user completes the necessary steps, such as document scanning and liveness checks. Once verification is complete, the WebView navigates to a predefined callback URL, which your app intercepts, signaling the completion of the process. Your backend then receives the full verification results via webhook, including the data needed for Face Search (1:N).

While Didit offers native SDKs for iOS, Android, React Native, and Flutter for optimal performance and features like NFC Verification, WebView integration serves as an excellent alternative for specific scenarios, ensuring that even legacy applications can benefit from Didit's powerful identity capabilities.

How Didit Helps

Didit is the AI-native, developer-first identity platform designed to make advanced identity verification accessible and flexible. Our modular architecture allows businesses to plug and play identity checks, including the critical Face Search (1:N) feature, into any environment, even legacy systems via WebView integration. We understand the challenges of modernizing existing infrastructure, and our platform is built to provide powerful solutions without requiring a complete overhaul.

With Didit, you gain access to a comprehensive suite of identity primitives, including ID Verification (OCR, MRZ, barcodes), Passive & Active Liveness, 1:1 Face Match & Face Search, AML Screening & Monitoring, and Proof of Address. Our AI-native approach ensures high accuracy and continuous improvement in fraud detection and identity assurance. We offer Free Core KYC, allowing you to start verifying identities without upfront costs, and our pay-per-successful-check model means you only pay for what you use, with no setup fees. The developer-first approach provides an instant sandbox, public documentation, and clean APIs, making integration as smooth as possible. By leveraging Didit's Face Search, businesses can proactively combat fraud, maintain high data integrity, and ensure a secure user base, all while integrating seamlessly into their current operational framework.

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