Sanctions lists

All in one place

Datlab Sanctions screen legal entities and natural persons against sanctions lists from CZ, EU, USA, and 20 other countries. For legal entities, 99% of risks are caused by individuals in the ownership structure, which is why we automatically screen ownership structures as well. We monitor newly emerged risks automatically, so each business partner only needs to be screened once.

Control from Russia

Contracting authorities and suppliers of above-threshold public contracts, as well as EU subsidy recipients, are subject to significantly stricter regulation — specifically Articles 5k and 5l of Regulation 833/2014. They must not make payments to any persons controlled from Russia or by Russians, i.e., persons controlled by the Russian Federation. That’s why Datlab Sanctions flags such control as a risk, including a specification of whom the risk is legally relevant for. For other users, it is a non-binding indication.

Where our global data comes from

Thanks to our cooperation with MOODY’S and CRIF, we have access to ownership structure data for companies from more than 150 countries, including Russia and China. The information is obtained from official registers via local partners — including private and paid databases. This makes it possible to identify long ownership chains spanning 10 or more jurisdictions — for example, companies based in Cyprus are often an intermediary in the EU.

Even so, we cannot guarantee that we have information on every company in the world. Data from providers and source registries may sometimes lag behind reality or be incomplete (typically, for example, in Arab countries or Africa). In such cases, Datlab Sanctions issues a confirmation including a note about the data being incomplete — if more thorough verification is needed, local partners must be asked to supply proof of ownership. In other cases, the findings (even if incomplete) can be considered sufficient, as the certificate confirms the client's reasonable effort to verify the business partner.

Name variants and Cyrillic transliterations

Transcriptions of Russian names into Latin script often appear in various forms in registries — differing based on national conventions, submitted documentation, and other circumstances. For example, the name Дмитрий commonly appears as Dmitri, Dmitrii, Dmitry, Dmitrij, Dmytro, etc. The situation is even more complex with surnames, patronymics (“middle”) names, or names of legal entities.

For each sanctioned person, we therefore work with several different name variations, including approximate matches with 1–2 typos, with or without a patronymic name, etc. The same applies to dates of birth — the exact date is often unknown, or multiple different birth dates may appear for the same person across various sanctions lists.

Thanks to fuzzy matching, the service has a significantly higher likelihood of detecting risks and thus provides better coverage against sanctions violations. However, this also increases the risk of so-called false positives, potentially burdening clients with low-relevance alerts. Our algorithms therefore take into account the risk of false matches for very common names (e.g., Sergei Popov — the Russian equivalent of Jan Novák) and are stricter than they are for rare names.

Batch screening and API integration

Do you need your system to handle sanctions checks automatically? Do you have 1,000 company IDs to verify? We offer several technical integration options and can connect to systems such as SAP, Helios, JASU, and others. Get in touch and we’ll help you choose the right one.