The Data Connecting Politicians, Criminals and a Rogue Industry that hides their cash

Panama Papers: Secrets of the Global Elite

About this data

The ICIJ Offshore Leaks database, which you are working with in Neo4j, contains information on almost 350,000 offshore entities that are part of the Paradise and Panama Papers and the Offshore Leaks investigations. The data covers a long time of activities – and links to people and companies in more than 200 countries and territories.

The real value of the database is that it strips away the secrecy that cloaks companies and trusts incorporated in tax havens and exposes the people behind them. This includes, when available, the names of the real owners of those opaque structures. In all, it reveals more than 430,000 names of people and companies behind secret offshore structures. They come from leaked records and not a standardized corporate registry, so there may be duplicates. We suggest you confirm the identities of any individuals or entities located in the database based on addresses or other identifiable information.

There are legitimate uses for offshore companies and trusts. We do not intend to suggest or imply that any persons, companies or other entities included in the database have broken the law or otherwise acted improperly. If you find an error in the database please get in touch with ICIJ.

The Shape of the Data

data model

The Offshore Leaks Database was imported into Neo4j to be used by journalists and researchers to take advantage of the connections in the data. To the left is the basic "property graph" data model. Each data record is called a "node" representing an entity, intermediary, officer or address. They're connected to form a "graph" that reveals a complex web of relationships. To the left you can see a simplified diagram how the nodes connect to each other.

These are the types of nodes that you will encounter in the data:

  • Entity - The offshore legal entity. This could be a company, trust, foundation, or other legal entity created in a low-tax jurisdiction.

  • Officer - A person or company who plays a role in an offshore entity, such as beneficiary, director, or shareholder. The relationships shown in the diagram are just a sample of all the existing ones.

  • Intermediary - A go-between for someone seeking an offshore corporation and an offshore service provider — usually a law-firm or a middleman that asks an offshore service provider to create an offshore firm.

  • Address - The registered address as it appears in the original databases obtained by ICIJ.

  • Other - Other entities found in the data.

How Graphs Helped our Investigation

The Offshore Leaks data exposes a set of connections between people and offshore entities. Graph databases are the best way to explore the relationships between these people and entities — it’s much more intuitive to use for this purpose than a SQL database or other types of NoSQL databases.

For example, let's say we want to discover the shortest paths between two entity officers through a set of Entity or Address nodes. This is quite easy with Cypher, Neo4j's graph query language.

MATCH (a:Officer),(b:Officer)
WHERE a.name CONTAINS 'Smith' 
  AND b.name CONTAINS 'Grant'
MATCH p=allShortestPaths((a)-[:OFFICER_OF|INTERMEDIARY_OF|REGISTERED_ADDRESS*..10]-(b))
RETURN p
LIMIT 50

To execute this query, please click on the statement above to put the query in the query editor above.
Hit the triangular button or press Ctrl+Enter to run it and see the resulting visualization.

The resulting graph allows us to explore how these people are connected:

How to ask questions using a query language

Graph Patterns

Neo4j’s query language, Cypher, is centered around graph patterns which represents entities with parentheses, for example, (e:Entity) and connections with arrows, for example -[:INTERMEDIARY_OF]->. :Entity and :INTERMEDIARY_OF are the types of the entity and the connection, respectively.

Here is an example pattern: (:Intermediary)-[:INTERMEDIARY_OF]->(:Entity). These patterns may be found with the MATCH clause.

Other Clauses

The following clauses may follow a MATCH clause. They work with the properties stored at the nodes and relationships found in the graph matching that pattern.

filter

WHERE intermediary.name CONTAINS 'MOSSACK'

aggregate

WITH e.jurisdiction AS country, COUNT(*) AS frequency

return

RETURN country, frequency

order

ORDER BY frequency DESC

limit

LIMIT 20;
Jurisdiction distribution of intermediaries in the ICIJ offshore leaks DB
MATCH (intermediary:Intermediary)-[:INTERMEDIARY_OF]->(e:Entity)
WHERE intermediary.name CONTAINS 'MOSSFON'
RETURN e.jurisdiction AS country, COUNT(*) AS frequency
ORDER BY frequency DESC LIMIT 20;

Click on the block to put the query in the topmost window on the query editor. Hit the triangular button or press Ctrl+Enter to run it and see the resulting visualization.

Explore the Panama and Paradise Papers Yourself



Investigative Queries

Explore the data yourself.

  • Cypher query language intro
  • Finding companies and individuals
  • Path finding

Shape of the Data

Understand the data model.

  • What are the nodes?
  • What are the relationships?
  • What are the properties?

Send ICIJ a tip

Help us investigate.

  • Interesting connections
  • Entities that matter to you