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The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

ESG, Textual and Movement Data Lead Alternative Data Interest During COVID Pandemic

By Warren Breakstone, Managing Director and Chief Product Officer of Data Management Solutions, S&P Global Market Intelligence.

As market participants work to understand their risk, uncover new opportunities, and try to make sense of the current state in the midst of COVID-19, there appears to be a heavier reliance on new sources of insight where traditional data alone does not provide sufficient perspective.

Based on an analysis of the usage of our S&P Global Marketplace platform and hundreds of client conversations, here is what we are seeing in terms of data that is garnering the most interest from the market.

Movement Data: tracking foot traffic and physical goods

We all know what happened to Toys R Us stores when it filed for Chapter 7 but how about the stores next door? How will I know when we begin to recover from the effects of COVID-19?  Movement data can play a role answering these questions.

Movement data takes a number of forms — people, goods, and money flow just to name a few. On people movement, also referred to as foot traffic, the data is most valuable when used in combination of a physical asset (e.g., retail or commercial properties). Real estate investors may use foot traffic data to assess their REIT properties— is that property getting more visitors or fewer? The return of people to stores may be an indication of the return of economic flow as society returns to patterns of normalcy.

On physical goods, trade or supply chain data can help market strategists understand changes in the value and quantity of goods being shipped between suppliers and companies, as well as between countries looking to understand the health and vibrancy of companies and economies.

Changes in goods flow can indicate strategy shifts or anticipate demand.  Pharmaceutical supply chain data can help anticipate FDA approvals based on movements of supplies ahead of decisions. Hospitals and government bodies have relied on these insights from Panjiva to understand the flow of PPE and ventilators, especially early on in the pandemic.  Separately, when applying telematics and weather condition data, decision makers are able to understand risks associated with supply chain disruption.


Being one of the hottest areas of investor interest, ESG data is a terrific example of how alternative data is becoming mainstream. As attention to ESG continues to rise, companies are increasingly considering the effects of sustainability and the risks it poses on future growth. They are looking to assess the financial impact and physical risk associated with climate changes, along with the impact of transitioning to a carbon-neutral economy driven by potential regulatory and market demand. By linking alternative datasets such as Trucost’s climate change physical risk dataset with property asset level insights, investors can leverage the resulting analysis to help them weigh their exposure risk from physical impacts. Additionally there is growing interest in transitioning to a low-carbon economy as businesses see the value in reducing expenses related to air travel and daily commuting.

Investors, regulatory bodies and employees alike have showed increased interest in whether a company is being a good community stakeholder and considering social and environmental impact of decisions. In return, companies are increasingly publishing sustainability reports and sharing their goals, progress and initiatives related to climate change policies and their own carbon and water footprint.  Similarly, social scores are used to understand gender and ethnic diversity, ethical supply chain sourcing, social justice issues, and employee training and compensation.

Textual Data: Uncovering new insights with AI

Fundamental investors are increasingly turning to textual data (written content such as filings and earnings transcripts) to provide context and commentary, particularly when used in its natural form as a digital document or on paper. Until recently, analysts consumed this content one-at-a-time. With the introduction of Natural Language Processing (NLP) and the application of machine learning, rich quantitative data is increasingly being extracted from qualitative content en masse, and becoming an important input into the decision-making processes. Instead of reading an individual earnings call transcript, machines are used to consume hundreds in real-time to generate insights. How are companies reacting to COVID? What risks do they see?

Technological advances in artificial intelligence have made tremendous strides over the last few years. This is especially relevant more recently as businesses have more urgency to leverage technology in the midst of a virtual workforce, capitalizing on the new volume and variety of textual data at scale to turn unstructured content into structured knowledge.

New problems and unusual situations often require new solutions. We see this in the actions and behaviors of our most sophisticated clients in the midst of the global pandemic, as they seek new insights and information from new sources. Clients are also looking to ensure they incorporate learnings from the current crisis to increase preparedness for the next.

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