Thomson Reuters has launched an industry-first graph of the relationships between people, organisations and metadata that allows financial services clients to understand over 2 billion connections within the financial ecosystem.
Using big data management techniques and machine learning, Knowledge Graph can be embedded into information systems to support search and discovery of links between individuals, entities and taxonomies.
“The largest big data challenge our customers face today is managing, and making sense of, their unconnected data,” said Geoffrey Horrell, director, product incubation financial and risk, Thomson Reuters.
“By bringing the Knowledge Graph into the wider market, we’ll be providing a hub of precise and valuable connections, and a foundation for our customers to build upon to solve a broad range of business challenges. Our current areas of focus range from investment research and business development to supply chain and risk management, however, there are many more opportunities to be explored.”
Enterprise data is typically built over time from multiple sources across systems and without a common data model and precise identifiers.
Thomson Reuters previously released its PermID as an open data item. The new API-delivered graph applies semantic web principles, the Resource Descriptive Framework and PermID to created structured data and deliver valuable insight.
At launch, the graph contains seven content sets: equity instruments and quotes, organisations, industry classifications, joint ventures and strategic alliances, supply chain, related companies and competitors and a comprehensive range of financial taxonomies and metadata. Additional content will be added as client usage of the graph grows.
Source: Thomson Reuters Press Release
