Visualising conflicts of interests

Header image: Photo by David Cook on flickr under a CC BY-NC 2.0 licence

mySociety and SpendNetwork have been working on a project for the UK Government Digital Service (GDS) Global Digital Marketplace Programme and the Prosperity Fund Global Anti-Corruption programme, led by the Foreign & Commonwealth Office (FCO), around beneficial ownership in public procurement. This is one of a series of posts about that work

As part of our research into beneficial ownership in procurement, we found several potential uses of better ownership data in the procurement process:

  • The identification of bidding cartels through revealing common beneficial ownership of tenderers to procurement processes.
  • The identification of high risk or fraudulent suppliers through non-existent or suspicious beneficial owners, such as professional intermediaries, or the presence of sanctioned individuals and companies in the ownership chains.
  • There is also an appetite from both government and civil society to use beneficial ownership in the identification of conflicts of interest in conjunction with information on procurement officers and politically exposed people.

To explore this area we built a prototype, ‘Bluetail’, to explore options for a visual interface for use by procurement officers. This demonstrates the ways in which beneficial ownership data could be used to address some of the key procurement use cases we had found as part of our research.

Diagram showing how contract data, ownership and pep data are combined to a single datastore and interface

Our demo sites and and source materials are available in public:

This prototype is a demonstration of processing data in three relevant standards: BODS, OCDS, and Popolo.

Bluetail integrates this data by identifier matching. We reviewed options for the alternative approach of attribute-based matching, and identified relevant open source tools with which to achieve this. However, the goal would be to avoid this kind of matching wherever possible as it is a time and resource intensive process, with many possible inaccuracies and difficulties in scaling. That being the case, we also explored different methods for releasing ID information that can improve the effectiveness of this process.

More information on the process and running locally can be found in the repository readme file.

See all posts in this series.