Investing
How Green is Green? Empowering ESG Investment Managers with Standard Methodology
Published by Jessica Weisman-Pitts
Posted on February 6, 2024
7 min readLast updated: January 31, 2026
Global Banking & Finance Review®
Company
Published by Jessica Weisman-Pitts
Posted on February 6, 2024
7 min readLast updated: January 31, 2026
Aligned Green, Social, Sustainability, Sustainability-Linked and Transition (ESG bonds or GSS+) finance volumes passed the $4trillion mark in H1 2023, according to the
Aligned Green, Social, Sustainability, Sustainability-Linked and Transition (ESG bonds or GSS+) finance volumes passed the $4trillion mark in H1 2023, according to the Climate Bonds Initiative (CBI). But how green is green? And how confident are fund and asset managers about the quality and integrity of the data required to support Environmental, Social and Governance (ESG) fund management decisions?
Maria Vigliotti
There is widespread consensus that climate change is impacting the profitability of financial institutions, hence it is imperative to not only deploy the appropriate risk model, but also to gather and maintain accurate data to ensure that transition and physical risks can be effectively monitored. The respective roles of Risk and Compliance officers are therefore evolving, as they’re tasked with ensuring data availability, quality, and governance to fulfil disclosure obligations, while also monitoring and assessing risk within portfolios. The current regulatory landscape necessitates the management of both compliance and ESG-risk exposures, with increasing scrutiny in the face of greenwashing allegations. The nuances of data have never been so key.
Under the European Union’s Sustainable Finance Disclosure Regulation (SFDR), which imposes mandatory ESG disclosure obligations for financial markets participants, fund and asset managers are required to provide more detailed disclosures to justify the categorisation of their light green Article 8 (environmental and/or social characteristics) and dark green Article 9 (environmental and/or social objectives) funds. Yet a lack of confidence in data, combined with the use of multiple different standards, raises fears about non-compliance, leading some to rebrand dark green funds as light green simply to mitigate the risk of punishment. While article 8 and 9 funds are making waves in the ESG investment sphere, the risks associated with regulatory non-compliance threaten to ultimately undermine sustainable investment.
Akber Datoo
With a better approach now vital, Maria Vigliotti, CEO at Fidata and D2 Legal Technology’s Akber Datoo and Elliot Curtis discuss the power – indeed, necessity – of technologies which enable financial market participants to have a common ESG understanding and support greener investment decisions. Is this the moment for AI?
ESG Imperative
Analysis from McKinsey estimates that the investment in new infrastructure and systems needed to meet international climate goals could be $9.2 trillion a year annually through 2050 – a figure estimated to be at least $3.5 trillion more a year than the current level of investment in both low-carbon and fossil-fuel infrastructure and changes in land use.
The EU is leading the world in its commitment to achieving change and the financial services market is recognised as a vital element in driving the fight against climate change. The SFDR is key to achieving the level of investment required to support innovation and compel companies to evolve towards more sustainable operations. It is fast-becoming the pre-eminent financial regulation in respect to combatting greenwashing, building on the work already done at the retail/product level to hold companies to account for all their activities.
Elliot Curtis
However, the lack of trusted data and inaccurate risk modelling remains a massive concern that is without a doubt constraining the pace of ESG-led change. Compliance and Risk officers are the custodians of regulatory compliance, yet this is a transition which cannot be achieved without the correct technology enablers. If the investment industry is not confident in the quality of data or, critically, able to make valid comparisons between business ESG performance, global opportunities to deliver on environmental strategies will be lost.
Inconsistent Data and Multiple Standards
A lack of consistent data is somewhat inevitable given the immaturity of the ESG market. However, adding to the problem is the arrival of multiple, incompatible standards and frameworks that are making it incredibly difficult to confidently compare the performance of ESG bonds. Are companies measuring their performance based on the Climate Bond Initiative’s (CBI) Climate Bonds Taxonomy, the EU’s taxonomy for sustainable activities or the International Capital Market Association’s (ICMA) Green Bond Principles?
Each of these – and there are many others evolving across the world – sets out a framework for disclosing and reporting on ESG bonds, but each has a different set of requirements which make it very difficult, time-consuming, and expensive to truly understand comparative performance and climate risk.
Incompatible Comparative Performance
This problem affects every part of the hugely complex and diverse ESG-led investment concept. Take the area of buildings renovation to reduce carbon emissions, for example. The CBI requirements will demand different approaches depending on whether the building is new or old, commercial or residential, and where it is located across the world. This requires a significant amount of work to assess different impacts in France, for example, compared to Australia.
An alternative approach could be to adhere to the ICMA model, which simply considers the site and the carbon reduction level. Meanwhile, the EU taxonomy demands adherence to the relevant national standard legislation. In some cases, this will allow the creation of an Environmental Performance Certificate (EPC) without the need to measure carbon reduction. While each approach is legitimate, they are significantly different. So how are fund and asset managers to confidently make comparisons between bonds?
In theory, the problem could be resolved if a fund’s risk model required reporting to all three standards, but the cost would be prohibitive given both the lack of skilled resources in this nascent area and difficulties in securing relevant, consistent data. Essentially, while the thinking behind each taxonomy and model is laudable, the existence of multiple standards is creating significant barriers to progress in a vital area of investment.
Engagement, Methodology and Technology
Consistency is essential if the ESG bond market is to fulfil its potential. Risk and Compliance officers need to establish rigorous data governance frameworks and structured methodologies to enable the effective comparison of performance and risk. Using the right taxonomy, it is possible to overcome the fragmentation and provide valid information that not only supports fund management decisions, but also compliance with regulations such as the SFDR.
Today, fund and asset managers are rightly nervous. They are concerned about the reputational risk and the real prospect of fines for SFDR non-compliance and, as a result, there are increasing reports of billion-dollar downgrades, where dark green (Article 9) funds are being downgraded to light green (Article 8) as part of a risk mitigation exercise. This is ultimately undermining the value of ESG activity, and clearly illustrates the current issues being faced in the realm of compliance risk.
It is time for Compliance and Risk officers to find better ways to measure and compare performance, while accurately assessing climate risk to portfolios. This is the time for systems which will be able to algorithmically traverse across these differing standards and frameworks, assessing, cleansing, standardising, and only then utilising the data to make the right decisions. Doing this at scale necessitates complex algorithms combined with a deep understanding of this area of ESG. A number of AI approaches, including Natural Language Processing (NLP) and ESG machine learning classifiers for accurate prediction of risk, are being developed. In relation to the Task Force on Climate-Related Financial Disclosures (TCFD) for example, ClimateBERT, a deep neural language model, has analysed the disclosures of TCFD-supporting firms and was able to conclude that firms have tended to cherry-pick to report primarily non-material climate risk information. While ClimateBERT has helped to highlight trends in climate-related disclosures, AI technologies will be of limited use in the absence of accurate and more broadly, appropriate data governance.
Conclusion
The EU is at the vanguard of sustainable investment and, as such, the world is watching. Greater international consensus is clearly required to accelerate investment in innovative ESG activity and that will only be achieved when fund and asset managers globally have the data, methodology and systems required to confidently discharge their responsibilities.
Now must be the time to implement the right methodologies and systems, or the threat of fines will become a reality as regulators continue to adopt a hard-line approach to greenwashing. But now is not the time for investment funds and asset managers to dial back. It is essential to move the dial on sustainability-driven activity and the market opportunity is enormous. Fund and asset managers that proactively embrace a methodology that brings together different standards and data sources will not only safeguard SFDR compliance, but also achieve new levels of investment clarity.
ESG stands for Environmental, Social, and Governance. It refers to the three central factors used to measure the sustainability and societal impact of an investment.
The Sustainable Finance Disclosure Regulation (SFDR) is a European Union regulation that requires financial market participants to disclose information on sustainability risks and impacts.
Greenwashing is the practice of companies misleading consumers about the environmental benefits of a product or service, often to appear more environmentally friendly than they are.
ESG bonds are fixed-income securities that are issued to fund projects with positive environmental or social impacts, aligning with ESG criteria.
Data governance refers to the management of data availability, usability, integrity, and security in an organization, ensuring that data is accurate and used responsibly.
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