Until relatively recently, sanctions were blunt instruments intended to isolate countries or individuals to condemn or alter their behavior—think of the decades-long U.S. sanctions on Cuba. In recent years, sanctions have become more common but, importantly, have also become more targeted. For example, rather than targeting an entire country, many recent sanctions target specific segments of a market and/or specific entities.
These sanctions often require knowledge of corporate structures and ownership to avoid even partial exposure to a sanctioned entity. A good illustration of this would be the U.S. executive order against specific Chinese military entities last year preventing U.S. investors from holding certain securities within their portfolios. FactSet Insight previously explored this topic in 2017.
Given the current situation in Ukraine and the growing list of sanctions issued against Russian institutions and individuals, we thought that it would be useful to consider a current, relevant example that illustrates what data and business logic is necessary to identify impacted securities.
The first step is to identify those entities that are explicitly identified by a relevant regime or government body. In the case of the U.S., government sanctions are recorded and made available via the Office of Foreign Assets Control (OFAC) of the U.S. Department of the Treasury. We can relatively quickly find the primary entities that the U.S has sanctioned from these lists.
One such recent addition from Directive 2 under Executive Order 14024, specifies the public joint stock company Sberbank Russia PJSC. To comply with this sanction, all U.S. investors must avoid holding investments in Sberbank. However, examining Sberbank’s entity structure illustrates that avoiding this company and the securities it has issued, along with its many subsidiaries and their issued securities, is not as simple as one might think.
To exclude the appropriate securities, we need to map out the corporate structure of an entity to identify all relevant subsidiaries. It is important to bear in mind that to flag the correct subsidiaries, we sometimes need to apply business logic based on percent of ownership. In other words, if 50% or more of an entity is owned by the explicitly sanctioned entity then that subsidiary should also be considered a sanctioned entity.
As an example, shown below we used FactSet data to map Sberbank Russia PJSC to its underlying subsidiaries as well as all securities issued by these entities. This now gives us a comprehensive list of securities, including common stock, corporate bonds, loans, and more to avoid.
There is still one more element that financial market participants need to consider: the risk of indirect exposure to sanctioned securities. In other words, investors must avoid any funds or ETFs that hold sanctioned securities. Accomplishing this requires mapping a sanctioned securities list, such as the one above, to a database of ETFs and funds along with their underlying constituents. While none of the above is trivial, the main challenge is having all the necessary data and, importantly, a means by which to link these disparate datasets together.
Unfortunately, the ongoing situation in Ukraine is a powerful reminder of the growing relevance and importance of sanctions as tools for change. Moreover, the increase in the volume, specificity, and frequency of change related to sanctions makes complying with them more of a challenge, and companies must do their best to manage and mitigate risks such as these since many other risks associated with war and acts of aggression are hard to predict with certainty.
Jeremy Katz and Eric Weitzman also contributed to this article.
FactSet’s Data Management Solutions (DMS) provides access to FactSet’s security- and entity-level symbology and comprehensive entity reference data, delivering all the necessary relationships and connections you need to link disparate sources of information to a master identifier.
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