Why Harmonized Data Matters: Semantics and Inference Processing in Finance
published: Nov. 10, 2015, recorded: October 2015, views: 1718
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The credit crisis of 2008 illustrated the data problems associated with unraveling the complex and globally interconnected world of the financial industry. We didn’t know precisely how some of the more esoteric financial instruments worked. We couldn’t link derivatives to their underlying assets. We had a difficult time unraveling ownership and control relationships of legal entities. We didn’t fully understand who was obligated to whom and who would be left holding the obligation when financial processes were unraveling. It was a devastating problem then and it is not much better now.
Conventional approaches aren’t working. There is only one real solution – data harmonization across federated systems, aligned to contractual meaning and expressed in RDF/OWL. In this presentation, we will put the data challenges associated with linked risk analysis into context and explain the pathway moving forward using the Financial Industry Business Ontology (FIBO).
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !