In December, we sat down with ESG regulatory compliance and assurance specialist, Lily Turnbull, to discuss her recent research into investor-grade ESG data.
Can you tell me a bit more about what you’re researching at the moment?
My research looks at the intersection of ESG regulatory compliance, governance, controls and ESG assurance. I’ve recently been researching best practices for enabling investor-grade ESG data, which we define as data that are accurate, auditable, automated and timely. Investor-grade data will be key to meeting the requirements of regulations such as the EU’s CSRD and the US SEC climate disclosure rule – but our research shows that over a third of firms don’t feel confident that they can provide investor-grade ESG data.
In 20 words or less, can you tell me why investor-grade ESG data are important for organizations?
Investor-grade ESG data is about ensuring that investors have reliable information for decision-making and that firms avoid greenwashing accusations.
What impact will this have across global business practices?
The growing emphasis on investor-grade ESG data will have a big impact on corporate transparency and accountability. It will mean that businesses have nowhere to hide, and they’ll be forced to be more transparent about their sustainability performance, risks and opportunities. Some industries may be more impacted by this than others. For example, retail and financial services have historically received more scrutiny over their green claims and will now face pressure to back up sustainable product claims with traceable data. As a result of this wave of radical transparency, we can hopefully expect decision-makers to be more incentivized to drive ESG and sustainability performance improvements within their organization.
What’s the one thing you would suggest organizations do to tackle investor-grade ESG data?
The overarching piece of advice would be to invest in software to manage your ESG disclosures and reporting. We frequently hear from organizations about how they are still using spreadsheets to manage quite complex ESG use cases. This presents a whole host of problems, such as version control issues, data inaccuracies due to human error, and data inconsistencies due to unstandardized data collection, calculation and tagging methodologies. Using software can provide a single point of control for ESG information and help to alleviate some of these challenges.
What is one recent innovation in the sustainability technology space that’s caught your eye?
We are beginning to see a lot more use of AI in ESG reporting and data management software, particularly in order to enhance data quality. For example, some firms are using AI to analyse large unstructured data sets and identify anomalies or estimate quantitative metrics in cases where actual data are unavailable. We are also beginning to see software vendors develop generative AI tools that can be used by firms as part of their ESG disclosure strategy to query regulations. Using these types of new, innovative technologies can help with advanced analysis as well as enabling investor-grade ESG data, although we recognize that some AI technologies are nascent and as such may still require a high degree of human oversight.
What’s next on your research agenda?
I am currently working on a benchmarking report, focused on ESG reporting and data management software for investors. An important part of our assessment criteria is whether the software has in-built functionality for data quality enhancement and auditability of records, which is key to enabling investor-grade ESG data. Ensuring data quality is a particular challenge for investment managers that may hold funds with tens or hundreds of portfolio companies.
