Knowledge graphs have been around for more than twenty years in various forms, but until comparatively recently, the computational power necessary to make them useful for broad applications has not been there. In the past few years, however, cloud computing has opened up many possibilities for knowledge graphs, and nowhere has this been more apparent than in the Financial Services sector.
Build and Manage Shared Semantics
Knowledge graphs are well suited for creating and managing shared semantic information, from controlled vocabularies to taxonomies to extensive data models. For financial services, this means dealing with the terms used in your business and understanding the concepts that underlie those terms, even when they vary from division to division. Shared semantics means that, whether you have one model or many, you have the means to communicate with one another … which is the whole purpose of having taxonomies in the first place.
Annotate Your Assumptions
What is revenue? This seemingly simple question can turn complex very quickly, as different accounting standards such as Basil III or FASB) not only may have subtly different meanings for such concepts but typically have formal regulations tied into these definitions that play into reporting this information. Knowledge graph annotation systems can tie your language into the appropriate regulatory framework (or multiple such frameworks). They can then use this information to reduce exposure to regulatory faux pas.
Make Your Words Intelligent
Concepts have context, metadata, and often even data, and this information may (and likely will) change over time. A Knowledge graph can not only define the exchange rate symbol for US Dollars but can give you a list of current (and past) exchange rates between dollars and other currencies – today and in the past. It can tell you, for a given job title, not only who the current job holder is but who that person reports to. Knowledge graphs are Internet-aware and have workflow capabilities and can determine what they need to remember. This means that your concepts not only remain current but they can talk to the outside world in both human and machine-readable ways.
Any financial knowledge graph provides deep insights into the connections between the various contracts and revenue movements in a nearly impossible way for a traditional relationship to emulate. This means that knowledge graphs can better monitor complex data shapes (revenue vs. cost from different but interconnected services, for example), identify when and where risks are more likely to occur, and model risk assumptions through extrapolation graphs.
Gain a Customer 360 Advantage
Your customers are not static – their financial behavior can be gleaned from their economic history, and this information can provide a complex portrait that can be used to anticipate their financial needs, warn about potentially risky decisions, and even recommend (and ultimately implement) investment strategies.