Regulators fined financial institutions $3.8 billion globally in 2025 for AML, KYC, sanctions, and customer due diligence failures. Behind many of these cases sits the same structural problem: the data compliance teams rely on to identify who they're really doing business with is incomplete, outdated, or unverifiable. Sanctions screening systems now generate false positive rates of 90–95% industry-wide, according to 2025 benchmarking from Alessa, LexisNexis Risk Solutions, and KPMG — and a significant share of that noise traces back to the underlying entity data being screened, not the matching logic itself.
This is why data enrichment has moved from a marketing function into core compliance infrastructure. But a provider built to append job titles for a CRM is a fundamentally different product from one built to support a defensible KYB or AML decision — and the cost of getting that choice wrong is not a missed email campaign, but a regulatory finding.
Most data enrichment platforms were designed to solve a marketing problem: incomplete contact records slowing down outbound sales. They prioritize speed, volume, and breadth of contact-level attributes — job function, company size, technographic signals. These are useful for a sales team qualifying a lead. They are close to irrelevant for a compliance officer trying to establish who ultimately controls a counterparty, whether that counterparty appears on a sanctions list, or whether its corporate registration is current.
Compliance-grade enrichment instead needs to answer a narrower, higher-stakes set of questions: Is this legal entity real and currently registered? Who are its directors and beneficial owners? Is it, or anyone connected to it, subject to sanctions, adverse media, or PEP status? Has anything material changed since the last time this entity was checked? Providers built primarily for sales and marketing use cases typically cannot answer these questions with the evidentiary rigor a regulator expects, because their underlying data was never collected, verified, or maintained with that purpose in mind.
This distinction matters most in markets where primary-source data is not readily available online. In much of the Middle East and Africa, corporate registries are not uniformly digitized, beneficial ownership disclosure requirements are recent or inconsistently enforced, and public registers vary widely in what they actually return. Transparency International's 2025 assessment of beneficial ownership transparency frameworks across the Middle East and North Africa found that most governments in the region have made limited progress on public sector accountability, with average corruption perception scores essentially unchanged year over year and only a handful of countries showing sustained improvement. A generic global data provider, optimized for jurisdictions with mature open registries, will often have thin or unreliable coverage exactly where compliance teams need it most.
The first and most important question to ask any data enrichment provider is not what data they hold, but where it came from and how it got there. For a compliance use case, an unverifiable data point is close to worthless, regardless of how current it appears.
A provider should be able to explain, for any given data field, whether it was sourced from a primary government registry, a licensed commercial data partner, a proprietary field-verification process, or an aggregation of secondary web sources. This matters because these categories carry very different reliability profiles. A UBO structure pulled directly from a corporate registry filing is verifiable and citable in a suspicious activity report or an audit response. A UBO structure inferred by an algorithm cross-referencing multiple unverified web sources is not — and presenting it as equivalent in an examination is a real regulatory risk.
Ask providers directly: What percentage of your corporate ownership data comes from primary registries versus inference? Can you provide a source citation for any individual data point, down to the record level? How do you handle jurisdictions where no reliable primary source exists at all? A provider unwilling or unable to answer these questions with specificity is signaling that its data lineage is not built for regulated use.
B2B data decays fast. Independent industry benchmarking puts annual decay rates for B2B contact and firmographic data at roughly 22.5%, meaning close to a quarter of a typical dataset becomes inaccurate within a year without active maintenance. For sales use cases, this is a nuisance. For compliance use cases — where a change in beneficial ownership, a new sanctions designation, or a change in corporate status can materially change a risk rating overnight — stale data is a control failure waiting to surface during an audit.
Compliance and risk teams should ask providers how frequently core risk-relevant fields are refreshed, and whether that cadence differs by data category. Sanctions and PEP data generally needs to be updated in near real time given how frequently designation lists change — global sanctions designations grew by roughly 17% year over year through early 2025, according to LSEG data cited in recent screening benchmarking, meaning a list that is even a few weeks stale will materially undercount current exposure. Corporate registry and ownership data moves more slowly but still requires periodic re-verification, since ownership changes, dissolutions, and status changes are not always self-reported by the entity in question.
The more useful providers will also disclose how they detect and flag change — not just how often they re-pull data, but whether they can alert a compliance team the moment a monitored entity's status, ownership, or sanctions exposure changes, rather than waiting for the next scheduled refresh cycle.
Coverage claims are where generic data enrichment providers most often overstate their fit for compliance use cases. A vendor advertising "global coverage" typically means comprehensive data across North America, the UK, and the EU, with meaningfully thinner records once a search moves into the Middle East, Africa, or other markets with less digitized public infrastructure.
For a compliance team operating cross-border — particularly one dealing with counterparties, suppliers, or customers based in or connected to MEA jurisdictions — this gap is not a minor limitation. It is the exact scenario in which enriched data is most needed and least reliably available from providers built around markets with mature open registries. The African Development Bank and partner organizations have highlighted that opaque corporate ownership structures remain a persistent channel for illicit financial flows across the continent, with UN estimates placing annual losses in the range of $50 to $88.6 billion — a gap that regional data infrastructure has not yet closed.
When evaluating coverage, ask providers to demonstrate depth, not just breadth: request sample records for specific jurisdictions relevant to your risk footprint, ask how records are sourced and maintained in markets without centralized public registries, and ask how gaps are disclosed rather than silently backfilled with lower-confidence inference. A provider with genuine regional expertise will be direct about where its data is thin and how it compensates — through local partnerships, direct registry relationships, or manual verification — rather than presenting uniform confidence across every market.
Poor entity matching is one of the largest hidden costs in compliance operations. Industry benchmarking places sanctions screening false positive rates at 90–95% across most organizations, meaning fewer than one in ten alerts a typical screening system generates represents a genuine match. A meaningful share of this noise originates in data quality: inconsistent name formatting, missing dates of birth or national identifiers, and transliteration inconsistencies across scripts and languages — all of which are amplified in markets with less standardized entity data.
A well-built data enrichment provider directly addresses this by supplying structured, standardized entity identifiers — consistent name formats, transliteration handling, unique entity identifiers, and complete secondary identifiers such as registration numbers — rather than leaving normalization entirely to the screening engine downstream. Ask providers what unique identifiers they attach to each entity record, how they handle name variants and multiple-script names common across the Middle East and Africa, and whether they can demonstrate measurable false positive reduction for clients with comparable risk profiles.
Every compliance decision that touches enriched data needs to be defensible after the fact — to an internal auditor, an external examiner, or a regulator. This means the data itself, not just the compliance team's internal process, needs to hold up under scrutiny.
Ask whether the provider can produce a documented audit trail for any given data point: source, retrieval date, and any subsequent changes. Ask whether their data handling practices align with the jurisdictions in which your organization operates, and whether they can support your record-retention obligations — a consideration that has become more prominent as regulators extend documentation requirements; OFAC, for example, extended sanctions-related record-keeping requirements from five to ten years in 2025. A provider that cannot produce this kind of audit trail is transferring risk back onto the compliance team, regardless of how comprehensive its data otherwise appears.
Bringing these criteria together, compliance and risk teams evaluating a data enrichment provider should structure the assessment around five questions: Where does the data come from, and can any individual record be traced to its source? How often is risk-relevant data refreshed, and does that cadence match the volatility of the underlying risk? How deep, not just how broad, is coverage in the specific jurisdictions the organization actually operates in? What measurable impact does the provider have on matching accuracy and false positive rates? And can the provider support the organization's documentation and audit obligations, not just its initial screening decision?
Providers that can answer all five with specificity and evidence — rather than marketing language — are the ones built for regulated use. Providers that cannot are likely better suited to sales and marketing workflows, where the cost of an inaccurate or outdated record is a wasted outreach email rather than a regulatory finding.
Data enrichment has become a functional necessity for compliance and risk teams, but the market is not built primarily for regulated use cases — most providers originate from sales and marketing tooling, where speed and volume matter more than provenance and defensibility. Choosing a provider fit for compliance work means looking past coverage claims and evaluating data lineage, refresh cadence, jurisdictional depth, matching accuracy, and audit-readiness directly. This distinction matters most in markets like the Middle East and Africa, where primary-source data is less standardized and the gap between generic global coverage and genuinely reliable regional data is widest. Teams that build vendor evaluation around these five criteria — rather than around breadth of data fields — are better positioned to make defensible compliance decisions and withstand regulatory scrutiny when it comes.