Any trend that can cause changes to share value should be considered impactful to any
publicly traded company—and CVS Health is no exception. According to the article, the
premise behind New Constructs is to “construct a more accurate economic picture of the
firm and to facilitate more meaningful comparisons of performance” (Wang & Thomas,
2021) while using models that include information that is only listed in footnotes and the
management’s discussion sections of financial reports. Information in these sections can be
especially helpful for normalizing adjustments that help compare companies in a more
accurate fashion. Using robo-analysts, or any machine learning platform, could allow for
less information to be missed through human error.
The complexity of companies and their filings have increased over time. The 10-K filing for
CVS Health for 2021 was 184 pages and includes financial information for four segments of
their enterprise. These different segments have very distinct characteristics—a variety of
revenue sources, expense categories, etc.-- that AI could help valuate and to compare
corporate filings as well as the segment reports, providing insights into and scalability of
company comparisons.
The ultimate goal of company valuation is to provide the best information possible with the
data on hand. Human analysts have been expected to provide more detailed information--
about more detailed companies—without missing important information that is hidden in
words instead of numbers. AI can take over the basics of this job to allow a human analyst
the time for higher reasoning and decision-making tasks. An environment that encourages
collaboration between man and machine can provide most accurate information to
companies and investors, all leading to better financial decisions.
Reference
Wang, C., & Thomas, K. (2021, June). New Constructs: Disrupting Fundamental Analysis
with Robo-Analysts. Harvard Business School. Retrieved from
https://www.hbs.edu/faculty/Pages/item.aspx?num=54019
