Amir Halfon of Marklogic recently discussed the ways that semantic technologies can create value in the financial sector, among other industries. One such way is through data provenance: "Due to the increased focus on data governance and regulatory compliance in recent years, there’s a growing need to capture the provenance and lineage of data as it goes through its various transformation and changes throughout its lifecycle. Semantic triples provide an excellent mechanism for capturing this information right along with the data it describes. A record representing a trade for instance, can be 'decorated' with information about the source of the different elements within it (e.g.: Cash Flow -> wasAttributedTo -> System 123). And this information can be continuously updated as the trade record changes over time, again without the constraints of a schema, which would have made this impossible."
Halfon continues, "Somewhat related to the example above, reference data management can also benefit from semantic technology, by modeling the connections between instruments and legal entities associated with them using triples. Here the richness of semantics as a way to model the real world is key. For instance, modeling the complex relationship between a mortgage backed security and the derivatives built on top of it, or the relationships between legal entities that are affected by M&A activity, can be nightmarish using entity-relational models. Semantic triples represent a much more agile and flexible way to capture facts such as Smith Barney -> acquiredBy -> Morgan Stanley, or CDS_123 -> wasDerivedFrom -> MBS_xyz."
Image: Courtesy Flickr/ Manu_H