New SEC Reg-SK Requirements
Hi everyone, in this blog, we will show you how to have complete and total transparency into developing company narratives around Human Capital reporting that meets the new SEC requirements. Today we are reviewing an ESG Scorecard based on Human Capital disclosures that seek to comply with the SEC's new Reg-SK guidance. We will also explore the technology underneath and how it's different from the traditional data aggregators.
Structuring ESG Data via a "Scorecard"
For this HCM (Human Capital Management) Scorecard project, we have looked at a selected set of early filers complied with the REG-SK reporting requirements so far in 2021.
We screened for the human capital section of the business overview and looked for normative language around ten key policies and programs. The results have formed a simple-to-follow scorecard. In our analysis so far, Visa has received the top score.
When you get a scorecard like this from a provider, how do you know the data is correct? How many opinions were used in the creation of that score? Here, we narrowed the scope to tagging language that meets precise criteria. It's powered by natural language processing, the same we use to extract and structure other non-financial information from the 15 million SEC filings in our database.
Insight Requires Transparency
Just seeing the scorecard has been somewhat a technology equivalent of view an Excel file, I have no idea what any of these scores actually mean from just looking at it. I don't want to make investment decisions without transparency. The main difference with what we do at idaciti is designed to increase your research confidence, save you time, and reveal the numerous data buried in unstructured documents.
Here's what we do differently.
Instead of copying data from documents to a proprietary database, we attach metadata to the source documents to maintain the connection, traceability, and auditability.
Extending XBRL to Structure Quantitative and Qualitative ESG Data
Digital reporting is the new norm, and more and more financial and ESG data are available in a "structured" format - i.e., XBRL. However, there are still numerous data buried in unstructured documents and disclosures globally. We have extended the XBRL structure to non-financial data. The idaciti tagging application is the simplest solution to XBRLize static documents into interactive data.
Instead of copying data from documents and then into excel or searching for hours through data catalogs, we attach metadata to the source documents - almost like overlaying search-enabled hyperlinks to the text. When you research through idaciti you maintain a connection to the source because it's traceable and in sync with the SEC Database 24/7.
New Requirements Require an Integrated View
These new SEC Requirements are principle-based, for now anyway. They are determined based on the filers' analysis of business materiality. So it follows what a filer chooses to disclose and how they disclose it; these are relevant features in analyzing qualitative ESG factors.
If we take a vertical view, we can look at several different ways companies discuss a single topic. For instance, hiring programs to increase diversity. The vertical view provides a method of comparing how deeply committed a company is to any particular ESG concern. The vertical view allows us to look at the difference in language between multiple companies on any single topic.
We can also research the topic horizontally. Take a company like Visa. Their score is high. The score alone does not tell you that they are meeting ESG thematic investing targets. You have to decide that for yourself. We make it very easy to do so. Our scorecard reveals the developing norms, but how are you going to integrate this into your investment process?
Reduce Noise - Boost Signal
If you run NLP-based machine learning yourself, there is a way to reduce the noise. We can structure the specific documents for you as "machine-readable disclosures" as clean inputs - you decide what the disclosures reveal. Call it in real-time via API, anytime, 24/7. How much more can you do with your python models, for instance, if new data can be sourced in real-time, directly from the issuers themselves?
A Better Future Demands Better Data
We need to go further to meet the needs of modern ESG stakeholders. What can you do with better research tools to further a more sustainable future? Below, we've used the power of idaciti to leverage structured data and bring together qualitative and quantitative information. In modern portfolio construction, you need to quickly perform integrated analysis —balancing the financial and non-financial picture. Let's see what that looks like in real-time with idaciti.
Here we are doing simple visualizations to demonstrate that you see the breakdown of ethnicity in their workforce.
If you are researching any of these companies, what kind of story does it tell you to see that a workforce is diverse, but leadership is not? Or that a company states a commitment to diversity but does not give out metrics to measure their success? It's all a part of the story, going beyond, to find out more about what matters to you.
We Make it Easier
And we can integrate this information with normalized financial data such as EPS or Cost of Revenue. You know what you are looking for as an investor. It's your mandate, your insight, your curiosity, your values that drive you to research. We simply make it easier to cover all the ground. Remove the middle person and get the data directly to you.
Thanks for reading! Follow us on LinkedIn to stay engaged with developing topics in disclosure research, ESG matters, SEC regulations, and more. Contact us here if you'd like to see more or get free access to selected idaciti applications and reports.
