Big open data analytics in finance services
While the financial services industry was bearing the brunt of the 2008 global crisis, big data analytics was making its mark in the development of numerous industries. The financial industry has also come to realize that big data and its insights and value would lend the sector a helping hand in both improving internal procedures and fine-tuning offers to customers.
In order to fight fraud, the sector is using analytics to compare data on location, shopping patterns and previous transactions to flag inconsistencies and take immediate actions. To comply with rapidly-changing regulations, the industry is launching initiatives to prevent as early as possible actions which may cost it billions of dollars in losses or regulatory fines.
Semantic technology allows text to be analyzed using big knowledge graphs and get linked to them. This allows more comprehensive discovery of suspicious patterns, using information from multiple data sources and combining them with facts extracted from text. Using this technology financial services industry can be more efficient in fighting fraud. Such applications can benefit from data sources and resources like:
- Linked Open Data – There are thousands datasets publicly available: DBPedia (all the facts from Wikipedia), Geonames (geographical database of all locations on Earth), statistical and other government data. All together these include billions of facts that can be used as source of evidence on broad range of relationships. In the English version of DBPedia alone we have identified more than 30 thousand direct child-parent organization relationships. For instance, there are 94 children organizations of Alphabet Inc., 106 children of JP Morgan Chase, 63 of General Motors and 48 of Gazprom.
- Global Legal Entity Identifier data – “Legal Entity Identifier (LEI) is a 20-character, alpha-numeric code, to uniquely identify legally distinct entities that engage in financial transactions.” LEI data can be downloaded from the GMEI Utility portal – a recent dump contains about 2.8 million facts about 211 thousand organizations. There are more than 10 thousand statements for ultimate parents – The Goldman Sachs Group Inc. is the champion being the ultimate parent of 1851 organizations!
- Financial Industry Business Ontology (FIBO) is a conceptual schema that allows for unified description of the structure and contractual obligations of financial instruments, legal entities and financial processes. This can be used to layer the proper semantics on top of the data coming from different sources. In other words it gives you the right lens to look at it.
The exponential rise of big data and analytics may turn into a huge leverage for the increasingly digitalized financial services industry and assist it in saving costs and raising profit margins. Challenges are many but hope is that a smart and insightful use of big data would change the financial industry for the better.
Read my newest blog post “Putting Big Data analytics into finance practice” for deeper insights.
I’m talking on this subject at FIBO Conference, collocated with Enterprise Data World 2016 in San Diego. Join my talk “Using FIBO and Open Data to Discover Relationships” on April 20 2016, 08:30 AM – 10:15 AM