RepRisk: Go beyond the checklist on ESG

This article is sponsored by RepRisk

Interest in private markets has grown at the same pace as the funds they launch – fast. Private equity firms have a to­tal of $3.4 trillion under management globally, according to a report pub­lished by Institutional Investor in June 2020, and the asset class has more than doubled in size over the past 10 years.

This unprecedented growth means private markets are uniquely poised to further the work of sustainable invest­ment through ESG implementation, and they have the opportunity to in­tegrate ESG in a way that circumnav­igates the growing pains experienced by public markets. True sustainability cannot be achieved by public markets alone, so why have private markets been slow to adapt?

According to a study published by Sustainability in July 2020, ‘ESG Fac­tor Integration into Private Equity’, which surveyed the top 23 private equity players in 2019, private equity firms primarily rely on checklists to as­sess ESG factors, and only a few firms have sought out external advice from industry experts. At RepRisk, we argue that a tailored method based on indus­try, geography and company-specific attributes is preferable to the checklist.

ESG due diligence should illumi­nate any past risks and serve as a reality check for how companies conduct their business. A checklist fails to do this – it may tell you if a company has a codified human rights policy in place, but it is not risk-focused and therefore will not reveal any alleged human rights vio­lations. The static data provided by a one-time questionnaire does not give the full picture of a company’s past and current ESG performance, or how it will likely handle future ESG matters.

Checklists also allow for selective transparency. In a world where com­panies are 100 percent transparent, company self-reporting could be used to create robust ESG due diligence data that accurately reflects business conduct. However, companies are only selectively transparent in their disclo­sures, potentially masking relevant and material ESG risks.

Similarly, the one-size-fits-all na­ture of checklists leads to obsolete and outdated self-reported data that is nei­ther meaningful nor comparable over time or across industries or portfolios.

A tailored approach

Self-reporting checklists are a step in the right direction for investors just dipping their toes into the water of ESG integration, but ultimately fall short as a path to truly sustainable in­vesting. Private equity and private debt investors that have discovered the value of ESG integration and employ granu­lar, timely and multi-dimensional data have seen improvements in the follow­ing processes:

Due diligence and monitoring: It is crucial to identify hidden risks during pre-investment due diligence and while monitoring a portfolio, as ESG risks do not go away once the ink dries. This requires comprehensive, granular and timely data.

ESG research should aggregate outside-in information on a company from a variety of national and interna­tional sources, as well as local sources on the ground, and in multiple lan­guages to get a broader view on current ESG issues affecting a particular sector or peer companies during due diligence – and be better informed on the scope of ESG as a whole. This allows for a more proactive and holistic monitoring approach, enabling managers to stay on top of the ongoing news flow regarding ESG issues linked to their investment universe, for easy flagging of incidents that could lead to major risks down the line.

Engagement: It is critical to have all the necessary research to support in­ternal and external communications and create risk mitigation plans when issues arise. RepRisk provides specially curated risk incident details so no stone is left unturned.

Funds can implement monitoring processes using ESG data to identify incidents that could pose risks, pro­actively contact managers in relation to a specific ESG issue and explore the implications for that business – as well as how the company is manag­ing the issues and engaging with their stakeholders.

Proactive monitoring via machine learning

The key to successfully crisis-proofing a portfolio is proactivity. Crises move quickly – ESG data should too. The most effective methodologies for gen­erating meaningful ESG data for pro­active protection are those that com­bine artificial and human intelligence. RepRisk is the only ESG data science provider to systematically cover ESG risk for private companies since day one – covering more than 100,000 private companies. Its AI and machine learn­ing technology provides the capacity to screen more than 100,000 data sourc­es in 20 languages on 95 ESG factors every day, while more than 90 highly trained analysts curate and analyse the incidents according to a rules-based methodology and relay those results back to the machine, constantly opti­mising the algorithm for more refined results.

This approach allows for the best of both worlds. Relying solely on artificial intelligence – say, a keyword search – produces large amounts of unrefined data very quickly. Relying solely on hu­man intelligence and research produc­es small amounts of refined data very slowly. Leveraging the best parts of artificial and human intelligence, while eradicating their respective short­comings, produces a large and refined dataset.

What is next for ESG in private markets?

Private fund managers are presented with the unique opportunity to learn from the pitfalls faced by managers first integrating ESG into public markets, and to implement an approach based on meaningful data that provides a ho­listic view of their portfolios and ena­bles them to be proactive, see around corners and mitigate risk early.

Fewer than 10 percent of the 8,810 global private equity firms are signato­ries of the Principles for Responsible Investment, according to the Institu­tional Investor study. There is a call for private investors to be pioneers of ESG integration in their field. We invite them to answer by partnering with us and unlocking the potential of the most comprehensive dataset available.