Abstract: 

Gartner states that “graph analysis is possibly the single most effective competitive differentiator for organisations pursuing data-driven operations and decisions.” Graphs are becoming an increasingly popular and useful tool in the information world – but they are by no means new.

In the world of financial data, Thomson Reuters considerable data assets are contributing to the formation of a Thomson Reuters Knowledge Graph. This will help our customers to identify both inferred and factual relationships previously unknown. For example, Thomson Reuters has been tracking movements of officers and directors of companies for over 30 years.

Our Deals database spans a similar period. By mapping organisations and people in both data sets to common permanent identifiers (PermIDs), a graph representation is formed exploring which executives are associated with which deals through time. Graphs like this can also be easily connected to other graphs as long as the graph databases share some common standards – typically around how entities (like people or companies) and relationships are represented. Graph use cases range from relationship management and business development to alpha and idea generation. Risk is perhaps the biggest category as graph databases can help identify hidden or complex relationships, which go to the core of fraud detection, supply chain risk analysis and exposure to sanctioned entities. The documents leaked in the Panama Papers case is one such example that helped identify hidden connections and the importance of connecting the dots as part of the research process to expose political corruption and offshore financial secrecy.

Bio: 

Tomasz A Adamusiak MD PhD has a unique blend of business acumen and technology expertise spanning multiple industries from finance to healthcare. He leads an organization developing Thomson Reuters Big
Data solutions for top financial, pharma, and research institutions - Data Fusion and Graph Feed. Dr. Adamusiak has a wealth of experience in the linked data and data science space backed up by the leadership and advisory roles within the American Medical Informatics Association (AMIA), and the SNOMED International.