Tim Baker

Tim is the Head of Applied Innovation for Refinitiv, PKA Finance and Risk Division of Thomson Reuters. He leads a team of talented data scientists, research scientists, design and u/x experts, and software engineers who collectively apply new technology and innovative approaches to solve business and customer challenges. Their primary labs are in San Francisco, New York, London & Singapore.


Tim has been and continues to be a major sponsor of Refinitiv’s open platform strategy and was an early proponent of the firms Open PermID initiative (see PermID.org), as well as the launch of the firms associated big data solutions, also known a Big Open Linked Data Solutions.


Prior to Thomson Reuters, Tim was a Managing Director at UBS joining the firm as an equity research analyst based in Mexico, after which he became Head of Latin Research, Deputy Head of US Research and CTO for Global Research. Latterly he led the firms investments in independent research firms, and assumed a number of board positions in portfolio companies.


Tim originally trained as an electronics engineer at Rolls-Royce, having graduated with a BSc in Electronic Engineering, and an MBA both from Bath University. Tim is a CFA Charter Holder.

Practical Use Cases and Challenges to Implement Graphs in Financial Services: Combating Financial Crime

Building a knowledge graph feed at scale for financial services use cases is challenges, but the use cases powerful. I will review the current state of play of knowledge graphs in financial services, what are the emerging use cases and what does the future look like. How did Refinitiv build its Knowledge Graph feed, and how can it be implemented by customers.


We will then do a deeper dive into a current Refinitiv Labs project that looks at how exposure to financial crime can be assessed by applying network analysis and centrality to a specialized version of the knowledge graph that includes data on sanctioned companies and people. We will show the concept, an overview of the analytics and a specific use case.