> For the complete documentation index, see [llms.txt](https://docs.1kosmos.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.1kosmos.com/identity-verification/database-validation/overview.md). # Overview *** Database verification cross-checks the data captured during identity proofing against **authoritative and third-party record sources** - issuing authorities, government registries, and identity-data providers. Instead of judging a document by its appearance alone, the platform asks the systems of record whether the identity actually exists and whether the submitted details match. It is a passive, back-end check: in most cases the user does nothing beyond the capture they have already completed. The result is a strong corroboration signal that complements document authentication and biometric matching. ### Why It Matters Document scanning and liveness confirm that a *real, unaltered document* is being presented by a *live person*. Database verification answers a different question: **does this identity exist in an authoritative source, and does the submitted data match the record on file?** A document can be genuine in appearance yet not correspond to any valid record - or it can be a real document tied to a different person. Checking against the source of record closes that gap and raises overall assurance. ### Methods Covered | Method | Question it answers | User friction | | ------------------------------ | ----------------------------------------------------------------------------------------------------- | ------------------- | | **AAMVA Verification** | Do US driver's licenses and state IDs match the issuing state's DMV record? | None (passive) | | **Aadhaar Verification** | Does the Aadhaar number correspond to a valid record, and do the holder's details match? | Low (consent / OTP) | | **Person Search Verification** | Do aggregated identity records corroborate the name, address, and other attributes the user provided? | None (passive) | {% hint style="info" %} Database checks are configured per verification flow. Coverage varies by document type, country, and source availability — confirm which sources are enabled for your tenant before relying on a given check. {% endhint %} ### Combining Database Checks Database verification is most powerful in combination. A document scan with face match establishes that a real person holds a real document; layering AAMVA, Aadhaar, or person search on top confirms that the underlying identity is recognized by authoritative and independent sources. Higher-assurance flows generally enable one or more database checks as required steps, while lower-risk flows may run them as advisory signals or omit them entirely. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.1kosmos.com/identity-verification/database-validation/overview.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.