First Consideration: Competitive Advantage or Disadvantage?
Turning back to our earlier example and considering a trading system based on proprietary algorithms, it is easy to accept that this might be better built in-house: it is a genuine point of difference for the bank that builds it. Perhaps the algorithms are so good that it becomes a tangible competitive advantage.
For a new version of Bloomberg, however, it is impossible to contemplate an in-house solution: the competitive landscape means that it is a disadvantage NOT to have the third-party solution, rather than an advantage to have your own. It is a system that relies on, in addition to many other things, access to vast amounts of data from a market-place much bigger than any one bank’s product and client coverage.
So how does this apply to a taxonomy-based financial tagging system?
Like a new Bloomberg, building your own would clearly put you at a competitive disadvantage.
Imagine a portfolio manager client who is excited to have signed up to receive a thematic selection of research reports from their five favourite banks. If four of the five all use the same gold standard thematic taxonomy, the client knows they can rely on receiving content about “5G” without being deluged with every single Telecom Sector and Single Stock report.
If the fifth bank has designed its own thematic taxonomy, however, it might not be able to expose “5G” as its own theme. Perhaps it has decided that “Future of Communication” or “Mobile Technology” is the more important theme and has buried 5G in one of those instead. This would mean that the same client would then have to accept either receiving no content on 5G or having that 5G content heavily diluted with other “Future of Communication” topics. In that scenario, you can imagine that the client stops relying on the fifth provider for that subject matter.
To be clear, though, the issue is not whether “5G”, “Mobile Technology”, or “Future of Communication” is the correct name or grouping for the thematic content. That is clearly subjective and likely to change over time and in different conditions. The real issue is that the publisher should always aim to provide its content to its clients according to the clients’ wishes.
The third party taxonomy can manage this easily as it constantly updates for the latest best practice it sees across the entire market. It can also be mapped seamlessly to any existing taxonomies already created, and adapt to changes over time. Furthermore, it is likely to be much larger. Therefore, the bank could decide to keep its “Future of Communication” tag as a parent category for general purposes but could still serve the client specific “5G” content as a child category.
In other words, an ‘ontology isn’t just for Christmas’. It is easy to underestimate the maintenance burden. Maintenance of an ontology and taxonomy requires a team of domain experts to update the breadth, depth, relationships and synonyms to accommodate a constantly evolving financial language and landscape.
Some examples are: new companies, sector classifications, asset classes (e.g. Digital Assets) and technologies (DLT, NFT, automation, ChatGPT); geopolitical changes (heads of state / central banks / elections); financial risk events (‘credit crunch’, or Covid-19 with all the variants to Omicron and beyond); and emergent themes (ESG, or ‘Lower-for-longer’).
There is a belief that some of these issues can be avoided by pulling in feeds of reference data and combining them together. However, that simply shifts the problem to the equally challenging tasks of interminable data cleaning, finding and filling gaps, and linking together disparate datasets all evolving at different times and in different ways.
So far, therefore, we have covered the cost advantage to buying an expert tagging solution (particularly the ongoing maintenance and development costs). We have also explained why it is a competitive disadvantage not to use the gold standard. But a final point remains: