Database Validation vs. Document OCR: Which to Use?
Blog post from Didit
Integrating database validation and Document Optical Character Recognition (OCR) offers a comprehensive approach to identity verification, combining the strengths of both methods to enhance security and compliance. Database validation excels in cross-referencing user-provided data with authoritative sources like government registries, ensuring the legitimacy of personal details without needing physical documents. Conversely, Document OCR focuses on verifying the authenticity of identity documents by extracting and analyzing data directly from them, detecting any alterations or inconsistencies. Didit leverages both these methods in its AI-native platform, allowing businesses to create tailored verification workflows that include additional features like Passive & Active Liveness detection and 1:1 Face Match. This layered approach not only strengthens fraud prevention efforts but also offers flexibility for different use cases, such as high-assurance KYC/AML compliance and international verification. By combining these methods, businesses can ensure a more robust defense against identity fraud while maintaining a smooth user experience.
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