Connecting the corrupt: data sources to study networks of serious financial crime in the United Kingdom - Diviák, Tomáš (The crime data handbook, 2024)
Social network analysis (SNA) is an approach concerned with analysing networks of relations and interactions among a defined set of actors. In recent years, SNA has become known as a useful tool for analysing a wide range of criminal networks, including networks of serious financial crime. However, using SNA in the study of crime is hindered by the aim of actors involved in these to conceal their interactions, making data collection complicated. These complications stem from issues with data availability, validity and reliability. To tackle these issues, we first introduce a framework for thinking about six aspects of network data collection: nodes, ties, attributes, levels, dynamics and context. In the light of this framework, we subsequently review three types of data sources usable for analysing financial crime networks in the context of the United Kingdom. These data sources are documents accompanying Deferred Prosecution Agreements, enforcement case files and commercial transaction data. We illustrate the contents of each of these data sources together with their potential for extracting network data and the types of conclusions that can be drawn through analysing them. These data sources share common problems in being of a secondary non-scientific nature and being prone to contain missing information. In conclusion, we illustrate further uses of SNA and possible extensions of the introduced data sources to other types of criminal networks and jurisdictions beyond the United Kingdom.