Investors weighing companies’ ESG exposures often feel frustrated by the challenges of either sourcing data from third-party providers or attempting to do their own research. But their frustrations may be about to ease, thanks to a new approach to ESG research.
A Murky—and Challenging—Data Landscape
There are several inherent difficulties with using third-party ESG scorers. Not all cater to the needs of investors; those that do, tend to overly focus on risks that are relevant to equity, not fixed-income, investors. Data providers are notoriously tight-lipped about how they arrive at their scores. And investors often find that there’s little similarity between different providers’ assessments of the same company; it’s hard to say whose score is more accurate.
The in-house research solution has also presented challenges. Without clear frameworks and processes for sorting and managing data (or lack thereof), ESG analyses tend to be both highly subjective and vague.
Thankfully, there’s been a proliferation of ESG data in recent years: since 2015, roughly 75% more companies in the major credit universe1 now report at least some ESG metrics. This heralds a sea change in how credit investors can conduct ESG analysis. How can investors capture, analyze and effectively evaluate so much additional information?
The answer, in our view, lies in rethinking the approach to ESG analysis. It’s been deeply rooted in fundamental credit research for a long time, but that must evolve if investors are to harvest the ESG data opportunity without falling victim to the same shortcomings as before. Making sense of the vast volume of data requires a scalable and consistent approach.
PRISM Shines a Brighter Light
This can be achieved by incorporating quantitative research into the process, as we do with PRISM, our proprietary credit research tool, which includes ESG in its broader credit assessments and provides an ESG score for nearly every issuer. PRISM takes advantage of the fact that the increase in ESG data has created the critical mass necessary for data to be inputted quantitatively.
There are, in our view, a number of benefits to this approach:
• It performs transparent, scalable and consistent processing of large volumes of ESG data that would be beyond the capacity of most fundamental credit research teams.
• Combined with big data capabilities, it covers 95% to 99%2 of the universe of investment-grade, high-yield and emerging-market corporate bonds, including small and unlisted companies—more than is typically available through third-party providers.
• It provides meaningful comparisons between issuers’ ESG risks, even when the issuers are from different industries.
• It creates insights specifically tailored to credit investors.
• By enabling nuanced comparisons between companies and industries, and by freeing analysts from data-gathering to do more valuable work, it adds to the power of active investment strategies.
To understand these benefits, it helps to know a little about how PRISM works.