What it means to be the authoritative data layer

Identity verification has always had a data problem. It’s not a shortage of tools, as many companies have built comprehensive tech stacks that span orchestration platforms, document verification, biometrics, and fraud prevention. The problem is what sits beneath those tools: the identity data that flows through every layer in the verification workflow.

The verification industry has spent years improving the software that sits on top of data without meaningfully improving the data itself. But when that data is poorly vetted, out of date, or missing coverage across entire regions, even the most sophisticated stack will produce results that are inconsistent, hard to audit, and difficult to defend. Legitimate customers get declined, while fraudulent identities slip through. And every time a regulator, auditor, or compliance team asks how a decision was reached, they’re met with head-scratching and hand-wringing.

This is where a data layer comes in, and it’s something businesses can’t overlook when building their verification process.

Data Zoo is the authoritative data layer for global identity verification. It doesn’t replace your orchestration platform, your document verification solution, or your fraud tools. Rather, Data Zoo sits within your verification workflow and gives every part of your stack better material to work with. We connect you to 150+ authoritative sources across 40+ countries, drawing reliable data from government databases, credit bureaus, telecoms, and other primary registries. And it’s all available through a single identity verification API.

We believe accurate, defensible data should be there for you wherever you do business, and you should never have to second-guess it. To us, data isn’t a feature or a nice-to-have. It’s mission-critical to your business, and it’s our entire focus as your trusted data layer.

At the core of what Data Zoo solves is a matching problem: Does the identity data presented at the point of onboarding correspond to an authoritative record? Most verification approaches collapse this into a single outcome (a single score, a pass, or a fail) that doesn’t show how the result was reached.

Data Zoo works differently, verifying at the attribute level whenever possible. Each identity element (such as name, date of birth, address, and ID number) is checked independently, and each result is returned as a true/false value alongside a service-level status that distinguishes a genuine non-match from a source error, partial result, or unreachable record. That means you can tune your decision logic to handle inconclusive results differently from confirmed mismatches, reducing false declines and mitigating the risk of acting on incomplete data.

Data Zoo ensures that the sequence is always configurable. Clients can define which sources are invoked, in what order, and under what conditions, fine-tuning for match rate, cost, response time, or any combination of the three. This is what makes it possible for organizations to improve their pass rates in new markets without rebuilding their stack and for platforms to offer their clients consistent verification quality across regions that vary enormously in data availability.

Clients set the decision logic, and Data Zoo returns a complete, structured record of every verification, from the overall match outcome and safe harbour status down to the result of each individual identity element and the source category it was checked against. There’s no black box determining outcomes, which means every identity decision is fully auditable, explainable, and defensible.

Not all identity data is created equal. The verification industry has grown up around a model in which data flows from primary sources (like government agencies, credit bureaus, and national registries) and through intermediaries and aggregators before reaching the organizations that need it. Each step in that chain introduces latency, potential quality degradation, and distance from the original system of record.

Data Zoo connects you to government databases, credit bureaus, telecoms, and other registries and subjects every source to rigorous due diligence for independence, freshness, and compliance with applicable data privacy and regulatory requirements before adding it to our network. Data Zoo does the work behind the scenes so your data is reliable enough to stake a business decision on.

In markets where data quality is highest, this means fast, confident verifications against authoritative records, with the option to verify across multiple independent sources for the highest level of confidence. In emerging markets and regions with lower data availability, it means a broader network of vetted alternatives that can still produce a defensible result. In both cases, you get a clear, attribute-level record that shows exactly what was checked, what matched, and from where.

The data layer is the foundation on which everything else in a verification stack depends. Database checks and document verification work together to create a layered defense, strengthening the confidence of every identity decision. Fraud detection is more precise when the underlying identity signals come from sources you can trust. And compliance is more defensible when every decision comes with a documented record of sources, attributes, and outcomes your team can point to when a regulator or auditor asks.

Identity data tells you whether a person is who they claim to be. Fraud and risk signals tell you whether the account, device, or contact information attached to that identity can be trusted. The two are complementary, and both are necessary.

More often than not, sophisticated fraud involves real credentials like stolen identity data, compromised contact details, synthetic identities built from fragments of legitimate records, presented in ways that look legitimate. A name-and-address check against a government database won’t catch a SIM swap, and a document scan won’t flag a phone number that was ported yesterday.

Data Zoo’s fraud and risk signals operate at the pre-verification layer, providing a set of discrete, configurable data points that organizations can use to pre-screen users before committing to a full onboarding check, set risk thresholds for different customer populations, and trigger periodic reviews for existing accounts. Unlike most risk scores, each signal is returned as a standalone data point, so your fraud and compliance teams can clearly see what was checked, what was returned, and from which source, instead of working backwards from an opaque score.

Data Zoo gives you configurable signals that are transparent, independently verifiable, and ready to integrate into your existing risk logic:

• Global watchlist screening: Sanctions lists, PEP checks, adverse media presence, and high-risk user flags, all from one integration.
• Configurable risk scoring: Custom risk rules using signals from multiple Data Zoo capabilities and authoritative sources.
• Mobile number intelligence: Carrier history, ownership history, connection type, and porting checks to distinguish genuine users from fraudulent ones.
• Deceased identity checks: Cross-referencing against official government death records to prevent use of deceased identities.
• Email & IP intelligence: Risk signals during pre-transaction screening, before high-risk actions are initiated.
• Name & phone match: Cross-referencing supplied names against phone numbers to confirm association and flag mismatches.
• SIM swap detection: Identifying recently ported or swapped SIM cards in real time to catch account takeover attempts before they succeed.

The case for an authoritative data layer isn’t just about completing more verifications. It’s about what becomes possible when your identity decisions are built on a solid foundation you can trust.

• At onboarding, higher-quality data means more legitimate customers are verified, reducing manual reviews and escalations that slow down approvals and erode the customer experience. For organizations operating across multiple markets, Data Zoo allows them to navigate different data sources, safe harbour requirements, and data availability while maintaining a consistent request and response structure.
• As organizations scale, the data layer removes a structural bottleneck. Entering a new market no longer requires sourcing local data vendors, negotiating new contracts, or spinning up new engineering projects. A single API integration grants access to the entire Data Zoo source network, with hands-on support through region-specific compliance and coverage requirements.
• For compliance and risk teams, attribute-level results and full source transparency mean every identity decision comes with a documented record. They always know which sources were used, which attributes matched, and how the result was reached. When a regulator asks, the answer is clear. When an auditor reviews, the trail is there.
• For fraud teams, the combination of authoritative identity data and pre-verification risk signals creates a layered defense that addresses the full range of modern fraud patterns, including identity impersonation, account takeover, synthetic identity fraud, and the use of compromised contact details to bypass verification controls.

The data layer is the infrastructure that makes all of this work. It sits beneath your existing verification tools to make them more accurate, more defensible, and more capable of performing in the markets that matter to your business, from account openings and cross-border payments to customer due diligence.