Bruno Bertocci, the head of sustainable equities at UBS Wealth Management, argues that the quest for standardized ESG data may be misguided. He likens ESG data to traditional financial metrics that institutions have evaluated for years, where complete agreement or uniformity is not the norm.
Bertocci suggests that just as two analysts can interpret the same financial data in different ways, a wide range of conclusions can emerge from ESG assessments as well. The focus, he believes, should be on providing functional data that enables asset and wealth managers to make informed, independent decisions.
During the recent webinar titled “ESG Standards: The Best Path Forward,” hosted by Reuters, Bertocci discussed the transition of ESG from theory to practice. The session aimed to explore how investors, companies, and policymakers could collaborate more effectively.
Some advocate for the standardization of ESG data through organizations like SASB and ISO to ensure transparency regarding corporate operations and risk exposure across sectors. However, as Bertocci points out, achieving uniformity in ESG performance analysis seems unlikely. He states, “If you’re looking for consistency, you’re not going to find it. This has never been the case, and I don’t think it’s a realistic expectation.”
Instead, he proposes treating ESG data similarly to traditional financial metrics, where diverse opinions and assessments are accepted. Asset managers should leverage various analytical tools from different providers, choosing those that best align with their proven methodologies. Some may prefer Moody’s ratings, while others might favor Bloomberg analyses.
Bertocci elaborates, comparing ESG ratings to Wall Street analysts’ recommendations on stocks, where opinions can vary widely—some analysts will advocate a “buy,” while others may suggest “hold” or “sell.” “This divergence is perfectly normal; the market thrives on diverse opinions and outcomes,” he states.
He raises a pertinent question: why does the investment community seek standardization in ESG when they readily accept varying conclusions regarding financial performance? This may stem from the nascent stage of ESG evaluation, as financial services navigate new datasets. Alternatively, it could reflect a broader uncertainty among asset managers about interpreting ESG data, given its complexity.
For example, consider an investment evaluation for an agricultural firm that provides affordable food products to impoverished regions. While such a company might meet many sustainability criteria, concerns about its carbon footprint could create a dilemma for investors. Should the potential benefits of reducing hunger and enhancing education override environmental concerns? The complexity of these trade-offs may lead financial professionals to seek standardized data for reassurance in their decisions.
Bertocci notes that asset managers often desire a comprehensive overview of companies’ ESG performance presented clearly, but he cautions that such clarity is unlikely due to inherent complexities. It may not even be essential for end investors, who primarily want assurance that their advisors are making well-considered decisions on their behalf.