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Our data collections contain over two million entities from sanctions lists and government watchlists, as well as politically exposed persons (PEPs), entities involved in financial crime, known terrorists, and parties excluded from government contracts.
Some of our data was used to identify billionaires and oligarchs hiding assets and circumventing sanctions via financial firms in Cyprus, and more recently, to corroborate the use of sanctioned oil tankers linked to Russian energy. It was also used in a The New York Times investigation that exposed how an illicit flow of Western technology is shipped to Russia through shell companies in Hong Kong.
The data we gather at OpenSanctions was designed to be built into anti-crime financial products, but also as a “contrast agent” for investigative reporters: a dataset that can be injected and cross-referenced with other data – such as data from leaked documents – to highlight illicit behaviour and uncover corporate corruption.
There are multiple ways you can use OpenSanctions to find leads and strengthen existing investigations. Below, we delve into a few of these methods:
Find people, companies, or vessels
Perhaps a name has cropped up in your investigation, and you want to understand who you’re really dealing with. Who else is this person linked to? What companies do they own or have ties to? Do they appear on a global sanctions list or government watchlist?
Using the OpenSanctions online screening tool, you can search over 300 data sources at the same time. There’s no registration required – we keep our data open to provide a public resource.
How to use our online screening tool:
- Enter search criteria: In the screening tool, input the full name of the entity you want to screen. The drop-down next to “Entity Type” allows you to narrow your search to companies, aircrafts, vessels, people, legal entities, cryptocurrency wallets, and more. Entering additional details such as the date of birth or nationality of the person, or the registration number and jurisdiction for legal entities, will also generate more precise results. Bellingcat also provides an in-depth guide on searching for people, companies or vessels in its Investigation Toolkit.
- Review search results: OpenSanctions will generate a list of matches based on your search criteria. Take the time to review these results carefully. While the screening tool enables you to search inside of specific watchlists, we recommend searching all lists (”OpenSanctions Default”) to begin with, and then discarding irrelevant results.
- Match analysis: For each search match, OpenSanctions provides a profile page with detailed information regarding the match. This includes relevant identifiers, sanctions program details, and associated entities. Where available, profiles link to source websites for each entity, enabling you to conduct further research.
- Save: All result pages on OpenSanctions are designed to be exported as PDFs so you can use your browser’s “Print/Save as PDF” function to create a record for your files.
Combine sanctions data with other open source information
In a recent story, The Washington Post combined OpenSanctions data with open source ship information and private maritime data to confirm that at least 17 sanctioned oil tankers with ties to Russian energy had docked at ports owned by the Indian conglomerate Reliance Industries. Reliance industries happens to be owned by Asia’s richest man, Mukesh Ambani.
The tankers flew under “flags of convenience” from nations including the Comoros, Guinea-Bissau and Sierra Leone, a common tactic used to circumvent Western sanctions. However, each carried an IMO number — a permanent, seven digit number which remains unchanged even if a ship changes hands — allowing The Post to locate the sanctioned vessels in the OpenSanctions database.
Find leads in document stashes
Investigations such as the Pandora Papers or Panama Papers brought financial journalism and follow the money techniques into the mainstream, but they also transformed how media organisations handle large data sets.
The Pandora Papers consisted of almost 12 million files — made up of documents, images, emails and spreadsheets — originating from 14 sources. It was a goldmine of stories, but at 2.94 terabytes, it was also a maze of numbers, names, and largely unstructured data.
The ICIJ relied on a number of tools to extract crucial information from PDF files, combine different data sources, and eliminate duplicates. One of those tools was ICIJ’s own Datashare, based on methodologies tested in the Panama Papers and Luanda Leaks.
Datashare is an open source tool freely available to access. It allows journalists and researchers to index and organise files and images to search for specific names, as well as batch search documents by uploading a list of names and searching more than 10,000 queries at once.
And, when it comes to choosing data sets to contrast against the leaked data, OpenSanctions has hundreds of interesting ones to choose from — from designated terrorist organisations, to politicians, arms dealers or CIA leaders.
You can download these data sets in a "Names-only text file" so that it’s ready to be uploaded to Datashare. These exports contain all the names and aliases of companies and people on sanctions and PEPs lists, often in multiple alphabets and spellings, giving you the best chance of finding a lead.
You can also use OpenRefine to match each entry in a spreadsheet against the OpenSanctions database to find reporting leads. We provide a step-by-step guide on how to do that, here.
Free API key for journalists
While businesses need to purchase a license for access to our API, journalists and non-profits can use our system for free. You can use the API to systematically cross-reference OpenSanctions data with other large datasets.
To request a free key, please sign up (using a work email address, if you have one) and fill out the form provided. For many news organisations (including all GIJN member organisations), NGOs and academic institutions, free API keys will be generated automatically based on your email address.
Using richer data to map connections
We like to think of sanctions data as a web: the more information we draw upon, the deeper and richer we can weave the web of data around a name, providing insight into relationships, affiliations, and ownership.
For this reason, we enrich government and official datasets with data from other sources. This might be Wikidata (used for our PEPs data set), OpenCorporates, or the ICIJ OffshoreLeaks database — the latter of which combines the data from various cross-border investigations by the consortium.
Data enrichment is a process designed to pick out risk-linked entities and their adjacent network from reference data sources to bring more detail to the main database. It also makes it easier for users to then connect data sets with those from sources such as OpenCorporates.com.
Visualising multiple data sets can also help surface relationships that would otherwise be hidden in a spreadsheet or cache of documents. Tools such as OpenScreening, which we developed alongside Open Ownership and Linkurious, allow users to unearth hidden links between sanctions targets and their networks. You can try it for free, here.
Access timely data — and track trends
Perhaps you’ve got your story sketched out, but you’re missing a key piece of data to provide your readers with context.
Sanctions data can be messy for a number of reasons — from bureaucracy-related publication delays to inconsistencies in data quality. OpenSanctions brings together data from several hundred data sources around the globe: that data is carefully cleaned, using a human-in-the-loop process for entity de-duplication across lists, and is then consistently structured, thanks to thousands of hand-crafted data patches. With hundreds of crawlers fetching and parsing data from various sanctions lists and government watchlists, data is updated in some cases on a daily basis.
This high quality data can be used by investigators and journalists, but can also supplement reporting with timely and accurate numbers. In this The New York Times article, journalists investigated how an illicit flow of Western technology was being funnelled to Russia through shell companies in Hong Kong to circumvent US sanctions. The journalists used OpenSanctions data to identify the number of Russian individuals and companies designated for economic restrictions by the Office of Foreign Asset Control (OFAC) since Russia’s full-scale invasion of Ukraine.
Data journalists, trade outlets, and visuals desks may find OpenSanctions particularly helpful for keeping afloat of new sanctions issued during conflicts or geopolitical developments, enabling them to conduct trends analysis across a country or sector.
Our monthly newsletter is handy for keeping up with new datasets added each month (you can also browse data sets here, filtering via “show recent editions first” to see newly added data sets).
And if you need any support in using our data – feel free to reach out. We will also be at the Global Investigative Journalism Conference 2025 held in Kuala Lumpur, as part of a panel exploring how global datasets can be used in cross-border investigations. Details can be found, here.
