More on data onboarding this week – ‘part two’ of my answer to the question “What data is it?”
Last week, in ‘part one’, I wrote about the datasets needed for a functioning security master program. This week, I want to tackle what is needed to establish a foundational entity master program.
Many of the same principles used in establishing a security master apply to an entity master. That said, you obviously do not have to have instruments for an entity master. (Just like recording issuers is not an absolute necessity for a security master.)
However, in case you do, they can be of great help in facilitating and ultimately improving your issuer matching.
With that, there are four key considerations in establishing an entity master.
The first is to look at all the entity or issuer identifiers that are coming into play now, or that may come into play later. These are key to achieving the necessary quality for an entity master. They are also key to saving money down the road because the biggest challenge with entity masters is duplicates, and preventing those duplicates helps drive better operations later on.
Next, there are classifications, such as industry sectors and subsectors. These are needed usually for certain internal requirements and external regulatory reporting.
Third, just as there are for a security master, there are standards. There are several seed data sets, with the most well-known being currencies, countries and regions. These then allow you to standardize crucial entity information such as country of domicile, country of risk, and which regulatory regimes are applicable to the entity.
And fourth, there are hierarchy considerations which are largely dependent on the core identifiers you choose. However, it may also be necessary to also employ other ID schemes to meet certain compliance criteria functions.
Each of the above are a necessity at the very outset of establishing an entity master. Once decisions have been made and implemented, the entity master then can be augmented further with other datasets such as issuer ratings, emissions data, physical risk, or company fundamentals to create a robust, workable, dynamic entity master.
Next week, I plan to talk about “Which datasets are foundational?” That is, the data that need to be onboarded next to service the foundation.