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According to institutional investor engagement research, the aftermath of the 2008 financial crisis has marked the beginning of a new era in the financial markets: active ownership and shareholder engagement has become increasingly widespread among investors who value long-term gains over short-term ones.
Almost 20 years later, active engagement is no longer just about investors taking more control to maximize positive financial outcomes - it’s also increasingly about taking an active role in steering the companies they are invested in towards a more sustainable and equitable future.
Truth is, both investors and their investees can benefit from a more active role of fund managers: it is an invaluable opportunity to create synergies, ultimately allowing both sides to share knowledge more efficiently and to prioritize long-term growth and value generation over short-term gains.
Moreover, by systematically exchanging information with their investors can greatly help companies get a more solid understanding of how they are perceived from the outside, which can serve as an invaluable way to validate internal decisions.
With the growing complexity of sustainability, ESG engagement is one of the most important ways fund managers can take “matters into their own hands” when it comes to the sustainability of their investments. Having a sustainability strategy in place is fast becoming a fundamental prerequisite for building a successful business, and generating future-proof value.
Moreover, investors’ appetite for sustainability, impact investing, responsible investing and ESG is soaring, partly due to a growing body of research which recognizes the financial benefits of preferring to allocate capital to environmentally- and socially- conscious projects. For instance, research by Morningstar found that ESG funds tend to show a better performance in a 10-year period compared to the wider market.
In this evolving landscape, and with the need to match LPs appetite for investments that embody different “flavors” of ESG, investors can no longer afford to simply cherry-pick their investments by applying overly-rigid ESG exclusion criteria. Most companies have a vast sustainability potential, but simply don’t have access to the crucial knowledge and resources to get started.
According to a study conducted by PRI, ESG engagement can create value for both portfolio companies and investment managers through three different venues: learning, communication and politics.
That being said, succeeding in ESG engagement is far from trivial. It involves a constellation of activities and approaches, each of which comes without its peculiar challenges.
Interestingly, Artificial intelligence (AI), and in particular applications of GPT-style LLMs hold a massive potential for helping investors enter a new era of direct ESG engagement.
In this article, we will explore how active engagement can change the game for sustainability- and ESG- oriented investors, the most common hurdles they face, and how AI can serve as a catalyst for change.
Investors can opt for active ESG engagement for multiple reasons.
Here’s some of them:
By actively engaging with their portfolio, investors can identify and address environmental, social, and governance (ESG) risks before they materialize or emerge in reporting, mitigating potential reputational and financial hazards earlier on.
In fact, active engagement around ESG issues enables more efficient knowledge exchange between companies and investors. By sharing insights, challenges, and best practices, both parties can navigate the intricate landscape, deepen their understanding, and collectively work towards sustainable and responsible business practices. Moreover, ESG-savy investors can easily replicate successful models and frameworks for more of their companies, thus creating a positive multiplier effect.
One big topic in the early days of impact investing was that of the (perceived)trade-off between financial and social or environmental gains. When the relationship between investors and businesses is limited to board rooms, it becomes easy to perceive ESG and business-related topics as not related, or even adversarial.
On one hand, companies that are left alone dealing with ESG requests from passive investors are more likely going to perceive such requests as a mere resource-drain, rather than as a way to collect crucial data to help the growth of their business. On the other, investors who fail to understand ESG in the broader context of a company’s business strategy or company’s systems might rely on false assumptions, and ask misguided questions.
By collaborating and working together, investors and companies can achieve better alignment and have a higher chance to find ways to conciliate their business and sustainability objectives.
Finally, one crucial aspect should be kept in mind:
It should be about providing the company with access to the critical resources, network and expertise that can help them make informed decisions about their ESG strategy, and helping them build the internal resources and connections that will help them grow into a more sustainable company in the long term.
ESG engagement can take place both in the investment and pre-investment phase.
The actions associated with it can differ across investors, as shown by this Citywire article - where 13 fund managers provide very different definitions of this expression. Of course, there is a trend towards standardization in the field due to emerging ESG regulations like the EU Taxonomy, which impose disclosure requirements related to ESG engagement.
That being said, some activities recur across the board. Some of these belong to a broader definition of active engagement, which goes beyond ESG alone, while others are more ESG-specific:
In general, we can say that ESG engagement can either be about gathering information, or about taking action. Both are equally important - although some investors do see engagement around ESG issues as more focused around providing advice, or information that can help steer a company in the right direction.
Ultimately, although engagement involves many soft relational components that can’t be assessed quantitatively, getting a rough understanding of the impact of engagement activities is crucial. What can’t be measured, can’t be managed, and this is also true for investor engagement: gaining a better understanding of what could be improved, and what is working and can be doubled down on, is critical.
While, as we saw, active engagement is a noble pursuit and can play a critical role in steering businesses in the right direction when it comes to ESG, it comes with its fair share of challenges.
While there are many hurdles associated with active engagement, we can summarize the main ones as following:
Despite their dedication, sustainability and ESG teams often face limitations in resources and time, making it difficult to devote ample attention to active engagement initiatives. This is even more true for small fund management companies with a small internal ESG team, or where investment managers wear multiple hats, including that of "ESG managers".
Portfolio companies generate vast amounts of unstructured ESG data, which becomes a Herculean task for sustainability teams to analyze, verify, and derive meaningful insights from. There is public information (can exist in public sustainability reports, if the company is large enough), there is private information that needs to be pieced together in the various pre- and post-investment phases. For engagement to be effective (and efficient), a robust data collection and monitoring system should be in place.
Identifying innovative strategies and emerging trends can be like searching for a needle in a haystack. Sustainability teams often struggle to keep up with the flood of information, hindering their ability to seize opportunities. This is especially true for ESG reporting, which is becoming increasingly regulated by regulations such as the EU Taxonomy and the SFDR in the EU, with other countries worldwide following suit. These regulatory frameworks and standards are still not carved in stone, and parts of them are still evolving before our eyes.
Moreover, sustainability is intrinsically linked to scientific research in fields like climate science, environmental science, biodiversity science, and several different fields within engineering. Again, although sustainability specialists cannot possibly be experts in all of these fields, effective and well-informed engagement makes it necessary for investors to “stay on top” and up-to-date with the high-level updates in the scientific world: without doing so, the risk is to provide misguided information and advice.
This poses an even bigger challenge for smaller funds, where investment teams - whether pre-investment or post-acquisition -, even though well-positioned to engage with portfolio companies on sustainability, are not the sustainability experts within investment firms.
Engagement can take place asynchronously, online, or via specific meeting with the C-suite or sustainability heads within the company. It can happen at events and conferences. It can be more or less structured, leverage the use of questionnaires, and involve multiple stakeholders. Some investors can count on ESG teams who are able to continuously monitor the progress of their portfolio companies and provide advice and guidance, while others have to deal with more constrained resources.
Recent research shows that over 90% of the data present in organizations is unstructured. AI applications of Large Language Models can now enable sustainability managers to interact with unstructured data and open up new frontiers for sustainability analysis. Previously overlooked or underutilized sustainability information can now be actively managed and treated in a structured manner, akin to financial data. This breakthrough enables analysts to derive meaningful insights and effectively measure and steer sustainability practices.
This is especially relevant for active engagement: as we have seen, many forms of engagement (especially those that focus on gathering information) happen by requesting or giving access to unstructured data. Some of this data pertains to the company’s ESG performance, while others might be related to specific ESG regulations, policies, best practices and so on.
AI tools can help ESG teams at funds and at companies streamline their engagement activities by helping with the collection, summarization and extraction of relevant insights from both public (external) and internal company data.
For example, Briink’s AI Assistant for ESG can ingest documents from companies (in PDF format) and answer questions from fund managers automatically, additionally referencing the relevant passage in the document, so that analysts can check the output directly at its source. The tool can also be used to quickly screen documents for information, which can help fund managers rapidly identify gaps, or perform proactive risk and thematic screening on their portfolio companies, which can greatly help inform future engagements.
Of course, this does not completely eliminate the need for regular check-ins and engagement meetings with portfolio companies, but it can help the stakeholders involved reduce back-and-forth communication considerably, thus addressing Challenge #1 and Challenge #2.
On top of the benefits discussed so far, new AI tools on the market can also help mitigate Challenge #3 and #4. For instance, Briink’s “Taxo Chat” feature (currently in Beta on the Briink platform - you can request early access here) allows ESG managers to open a dialogue directly with ESG regulations like the EU Taxonomy themselves, which can help busy managers develop a better understanding of the latest (updated) version of these regulations themselves, and helps ESG analysts perform external research at scale, which can fuel portfolio company conversations and strategy.
In addition, AI-driven simplification and summarization can be extremely useful for knowledge exchange. Simplified and summarized regulatory text can even be used for other types of stakeholder engagements such as presentations to LPs.
However, investors and companies alike need to be wary of generic marketing AI applications: these usually only “prettify” presentations and make the text sound convincing, but the content might be hallucinated or present misleading information. This is why it is better to use tools that are specifically designed for use cases within the ESG regulatory landscape, and enable the user to check and research references themselves, and use content from real regulations to produce their outputs.
Finally, AI tools can also support engagement activities by providing suggestions in terms of easily actionable next steps to be implemented. In the future, AI-powered ESG assistants will serve as virtual advisors to ESG and sustainability teams, supplementing ESG teams at companies in offering real-time guidance and actionable insights to portfolio companies. Although existing applications trained on LLMs like OpenAI Innovations currently only offer rudimental capabilities in this respect, innovations in this space are happening by the hour, and staying on top of them could prove a very savvy investment in the future.
As we have seen so far, active engagement around ESG is a pivotal strategy for sustainability-oriented investors aiming to drive positive change in their portfolio companies. With AI as a powerful ally, investors can overcome the challenges that hinder effective engagement.
By leveraging AI's capabilities in aiding research and improving access to external information, simplification of information to various levels of ESG-savviness, and even generation of potential action items based on industry best practices, investors can unlock the full potential of active engagement. Embracing AI-driven solutions, sustainability-oriented investors can lead the charge toward a more sustainable and responsible investment landscape, propelling us toward a brighter future for all.
Ultimately, we should not forget that ESG engagement is all about collaboration between portfolio companies and investors. And it’s important to keep in mind that large parts of it rely intrinsically on human factors which do not lend themselves to complete automation. However, investing early in innovations such as AI-powered ESG tools can help investors free up time and resources to take care of the most important aspects of ESG engagement, both in the pre-investment and in the investment phase.
Briink has created the essential AI-powered toolbox for ESG teams. Our solutions help you automatically analyze internal documents and perform screenings against different ESG regulations and frameworks. If you would like to be among the first to try our AI-powered tools for ESG teams, you can register your interest here.
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