In cooperation with Linkurious, we worked to develop a network graph view of the OpenSanctions data and demo how it can be used in anti-corruption and money laundering investigations.
The demonstration showed a network combining OpenSanctions data with the ICIJ OffshoreLeaks database, which includes offshore company details published as part of the Panama Papers, Paradise and Pandora Papers investigations. Using only name-based matching, the graph allows us to draw the lines between sanctioned individuals, PEPs and potentially shady offshores. We also demonstrated how stored queries and alert-driven case management can be used to scale up this investigative process.
Linkurious also documented using graph analytics for PEP screening in a case study blog post.
The underlying mechanism for this demo combines the OpenSanctions and OffshoreLeaks data into a CYPHER script that will import the data into the Neo4J graph database. From there, it can be analysed or imported into the Linkurious analysis tool.
The data, as well as the script used to generate it, is available from our GitHub repository and can be used to replicate and expand the demonstrated functions:
As always, we're keen to hear any feedback, suggestions and ideas on this! And, of course, get in touch with Linkurious if you're interested in trying out their power tool for investigations.
This article is part of OpenSanctions, the open database of sanctions targets and persons of interest.