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Suptech and greenwashing: A desirable paradigm shift

Maryeliza Brasa and Samir Kiuhan-Vasquez co-authors

By Maryeliza Barasa and Samir Kiuhan-Vasquez

Retail and institutional investors increasingly choose to invest in assets that align with biodiversity, climate, and other sustainability goals. This trend has led to a surge in the number of financial products claiming to meet ESG objectives. Notably, ESG-labelled debt securities in the global bond market have grown from €135 billion in 2018 to an estimated € 900 billion in 2023, representing around 14 to 16% of the year’s total issuance.

Financial greenwashing refers to the practice of companies or financial services misrepresenting the extent to which their products, services, or investment strategies are environmentally friendly, sustainable, or ethical. This often involves exaggerated or false claims about a company’s environmental practices or the sustainability of an investment product to attract customers or investors looking to make environmentally responsible choices.

As the demand for ESG-focused products and services surges, so too does the potential for financial services companies to either knowingly or inadvertently amplify their sustainability credentials. The bid to attract and retain customers and investors manifests in myriad forms. Businesses might employ evocative language, make ambitious claims, or use symbols and colours that conjure an eco-friendly image, all to craft a perception that their offerings are more environmentally sound than they truly are. Some financial firms may engage in more deceptive practices, such as fabricating or altering data to suggest more favourable sustainability outcomes, cherry-picking information to disclose only positive environmental impacts while ignoring negatives, or even entirely fabricating sustainability projects that receive funding but never come to fruition. In more egregious ESG greenwashing cases, some firms falsely claim to adhere to international ESG standards or to have certifications that they do not actually possess. These malicious and fraudulent behaviours mislead stakeholders and undermine the credibility of genuine ESG efforts within the sector.

In this context, the potential of suptech to ensure the robustness and reliability of “green” products is significant, inspiring confidence in their credibility and future relevance.

Determining whether claims regarding green advantages or compatibility with climate-related goals are valid is very complex, and accusations of greenwashing are common. For instance, an investor advisor company was charged USD 1.5 million in 2022 by the US Securities and Exchange Commission (SEC) for misstatements and omissions on ESG considerations in making investment decisions for certain mutual funds that it managed. The Australian Securities and Investments Commission (ASIC) brought a case against Mercer Superannuation (a public offer retail fund), alleging that they falsely claimed their Sustainable Plus investment options excluded investments in fossil fuels, alcohol, and gambling, when in fact, they included investments in companies involved in those industries – the company was ordered to pay a USD$8 million fine. In a separate case, several energy companies, including Tlou Energy Ltd and Black Mountain Energy Limited, faced penalties from ASIC for making unfounded claims about carbon neutrality, low emissions, and focussing on clean energy without substantial progress, funding, or detailed plans​.

ESG Greenwashing doesn’t always stem from deliberate deception; it can also arise from inadvertent errors in the complex process of assessing and comparing the environmental impacts embedded within the portfolios of financial entities. The intricate nature of these evaluations is further complicated by the ESG landscape’s continuous development. Taxonomies defining what constitutes ‘green’ are still in a state of flux and harmonisation, and standardised disclosures and reporting frameworks are still being developed.

This state of flux creates a gap often filled by voluntary disclosures, which, lacking standardisation, can be unreliable and lead to confusion. Consider the dilemma of deeming funding for a project as “green” when the funds come from an issuer deeply engaged in carbon-intensive operations. Should their broader environmental impact negate the project’s sustainable label?

Moreover, discrepancies in sustainability ratings provided by different agencies for the same asset only add to the confusion. Without a universal standard, two rating providers might evaluate the same asset and arrive at wildly different conclusions about its sustainability credentials.

Questions and challenges like these are central to the broader issues confronting the financial sector today.

Regulations and the risks of greenwashing

Widespread greenwashing risks undermine efforts to promote and mobilise sustainable finance. Bill Coen, former Secretary General of the Basel Committee on Banking Supervision, argues that “[greenwashing] erodes investor confidence in the market for sustainable relatable products, deprives developing countries of blended financing investments for sustainable infrastructure and poses a threat to a fair and efficient financial system.” The BIS identifies the following ways in which financial authorities can thwart greenwashing claims by enhancing market transparency:

  1. Developing taxonomies for the transition to a greener economy and matching them with high-level objectives such as The Paris Agreement.
  2. Setting up and enforcing consistent and standard practices that will help investors understand the environmental advantages of “green” assets.
  3. Creating verification procedures and certifications attest to achieving the stated environmental advantages.

Many central banks and financial supervisors have committed to addressing climate-related financial risks and supporting climate-related financial disclosure reporting. This is evidenced by collaborative networks of financial authorities like the Central Banks and Financial Supervisors Network for Greening the Financial System (NGFS), the Sustainable Banking Network (SBN), and climate-related financial disclosure reporting like the Task Force on Climate-related Financial Disclosures (TCFD), Global Reporting Initiative (GRI), IOSCO’s Sustainable Finance Taskforce (STF) and International Sustainability Standards Board (ISSB).

The Financial Stability Board (FSB) has led the effort to develop internationally consistent standards for ESG disclosures with the Task Force on Climate-related Financial Disclosures (TCFD) initiative. The TCFD Framework, released in 2017 and focuses on climate-related financial disclosures, is one of the most widely endorsed frameworks. In 2023, the ISSB published its first two IFRS Sustainability Disclosure Standards, IFRS S1 General Requirements for Disclosure of Sustainability-related Financial Information and IFRS S2 Climate-related Disclosures. These standards are built on TCFD (Progress Report on Climate-Related Disclosures (fsb.org)). The FSB, which oversees the TCFD, acknowledged that the ISSB standards mark the culmination of the TCFD’s work since its establishment in 2017. The FSB has now requested the IFRS Foundation to monitor companies’ progress in disclosing climate-related information, a previously held responsibility by the TCFD.

Some jurisdictions have introduced specific frameworks to regulate financial institutions’ claims concerning ESG or sustainability factors of their products and services. The SEC, for instance, set up a Climate and ESG Task Force in 2021, which, among other things, examines compliance and disclosure issues with ESG strategies of investment advisers and funds and detects serious omissions or misstatements in public issuers’ disclosures of climate risk. Similarly, the UK’s Competition and Markets Authority (CMA) published a green claims code in the same year to protect consumers from misleading environmental claims. The European Central Bank also published a new set of statistical indicators in 2023 to support climate-related risk analysis in the financial market and to monitor green transition. Just recently, in February 2024, the Council and European Parliament reached a provisional agreement to regulate ESG rating activities, particularly concerning their methodology and sources of information. Additionally, the EU’s Internal Market and Environment committees set out new regulations in the same month, which require companies to undergo a verification process for their environmental assertions before publicising them.

As the regulatory rules relating to ESG greenwashing take shape, supervisory authorities in various jurisdictions are also taking steps to advance the inclusion of sustainability claims within their existing framework. However, supervisors have generally made less progress in integrating climate‑related and environmental risks more broadly into binding supervisory tools. Challenges remain in development. They are also hampered by a lack of common definitions, classifications, taxonomies, and evidence of risk differentials between ’green’ and ’non‑green’ assets.

Can suptech enhance/establish the supervisors’ capacity to tackle ESG greenwashing?

Financial authorities need to adapt their supervisory approaches to include technologies that can analyse ESG data. Artificial intelligence (AI) and machine learning (ML) techniques, big-data analytics, and distributed ledger technology (DLT) solutions can assist supervisory authorities in evaluating corporate emissions and identifying those overstating their commitment to sustainability. These suptech solutions enable the processing of large quantities of data. They can lower costs, shorten the time and effort needed to obtain and analyse a firm’s ESG track record and contribute to enhanced data quality, reliability, and transparency.

Financial institutions and supervisors are better able to reduce the dangers of greenwashing with greater assurance over the source of the data and advanced techniques. DLT is considered a way of maintaining the data’s provenance and traceability. Additionally, harnessing satellite imagery, remote sensing technologies, and other geospatial technologies has helped collect large datasets on material environmental risks, vital in checking financial institutions’ exposures. Technological solutions connecting directly existing systems, such as waste management systems via APIs to retrieve relevant climate and consumption data more effectively, are also being utilised.

Technology can help financial authorities verify that ESG-related product claims to consumers are accurate and complete via streamlining sustainability reporting. For instance, in September 2022, under Project Greenprint, the Monetary Authority of Singapore and Singapore Exchange (SGX) jointly introduced ESGenome, a digital disclosure portal for financial institutions to submit ESG data efficiently and for investors to access such information in a consistent and comparable format. Later in November 2023, the MAS unveiled Gprnt, a culmination of MAS’ Project Greenprint, an integrated digital platform harnessing technology to simplify how the financial sector and real economy collect, access and act upon ESG data to support their sustainability initiatives.

AI takes automation a step further since natural language processing (NLP) can be leveraged to scrape data from the web. ML can match and merge disparate datasets, thus driving certain aspects of data analysis and management to inform supervisors’ actions. NLP platforms convert unstructured data collected into structured data, which is then transformed into insights and narratives.

Examples of NLP-related techniques that can be used for ESG-related analyses to detect potential greenwashing include text analysis, text summarisation, sentiment analysis, information classification, knowledge graph, named entity recognition, question answering, topic modelling/clustering, patent and enterprise search, knowledge graphs, synonym search, network analysis etc. Let’s break down some of these methods as explained by Beerman, Prenio and Zamil in their 2021 paper on suptech tools for prudential supervision:

  • Text analysis involves compiling, analysing, and extracting specific information from large volumes of unstructured documents using NLP and ML techniques. It covers a range of use cases, including topic modelling text mining, among others. It can be applied to assess companies’ disclosures and deliver qualitative results on their ESG credentials. For instance, the SEC Climate and ESG Task Force proactively search for greenwashing cases via data mining. Banco de España applied text mining techniques (specifically named entity recognition) to assess the Task Force on Climate-Related Financial Disclosures (TFCD) recommendations on climate-related disclosures of 12 significant Spanish financial companies using publicly available corporate reports from 2014 to 2019.
  • Text summarisation, closely related to text analysis, summarises critical points from large documents for quicker supervisory consumption. With AI, news and articles can be summarised and analysed automatically to monitor hundreds of entities claiming to offer green products in real time. One of the vital use cases is NLP Extraction, which began in 2020. It was used for text summarisation and analysis to monitor discussions regarding climate change in board packages.
  • Information classification seeks to reveal patterns from vast amounts of unstructured information through classification and organisation. Supervisory agencies organise and classify various texts, including news articles, regulatory submissions, and other documents. In early 2019, Banco de España piloted a project to use NLP to extract and classify relevant information in relation to ESG disclosure in Spain.
  • Sentiment analysis involves identifying and categorising opinions (harmful, positive or neutral) expressed in texts. The European Central Bank (ECB) explores market sentiment analysis using NLP and ML techniques to assess how the public perceives financial institutions. The intended solution should be able to present, in the form of a dashboard, an overview of market sentiment, allow for drilling down into risk trends, analyse market sentiment over time, and group detected issues into risk categories.

Notwithstanding the tangible benefits of suptech tools and applications, implementation challenges remain, holding back their wider adoption and acceptance. Some include lagging data science skills, governance complexities, data quality, and integration issues. Developing a strategy/ roadmap for incremental, comprehensive transformation is necessary to address these challenges. Suptech modernisation is a journey, not an event (Cambridge SupTech lab, State of SupTech report, 2022 and 2023).


Investors are increasingly looking at a firm’s ESG activities to make informed decisions on where to invest and where to use their influence to improve firms’ sustainability practices. Available ESG ratings and green labels are often not sufficiently clear on the promised environmental advantages and offer little assurance of the benefits accruing. Financial authorities aim to protect investors and promote a fair and reliable portfolio of sustainable financial products, helping achieve climate policy goals.

In protecting against ESG greenwashing, it is vital to ensure that consumers have access to ‘green’ or sustainable financial products and services that meet their needs and preferences. Therefore, several jurisdictions are developing supporting tools like standard audit practices, a taxonomy of activities, and financial accounting standards, as well as ensuring that these tools are robust and as straightforward as possible. In the meantime, based on existing frameworks, they are exploring technologies to help them detect ESG misconduct faster and more efficiently.

Artificial intelligence and other tools offer a promising way forward for collecting and analysing financial firms’ “green” claims. NLP and ML techniques can quickly and accurately collect and process vast amounts of information on a firm’s ESG impacts from diverse sources to complement current ESG ratings and corporate disclosures.

To translate these principles into actionable steps, financial regulators can collaborate with industry stakeholders to develop comprehensive guidelines for evaluating and disclosing ESG practices. This collaboration should emphasise transparency, accountability, and alignment with global sustainability standards. Additionally, fostering innovation in data analytics and machine learning can empower investors to make more informed decisions by providing them with reliable insights into a firm’s environmental, social, and governance performance. By implementing these measures, regulators and supervisors can strengthen the integrity of sustainable finance markets and support the transition to a more environmentally and socially responsible economy.

The Cambridge SupTech Lab can play a pivotal role in advancing these actionable steps by leveraging its expertise in suptech and collaborating with regulatory bodies, financial institutions, and technology providers. The Lab can facilitate the development of advanced data analytics tools tailored specifically for evaluating ESG practices in the financial industry. Through partnerships with financial authorities, the Lab can contribute to the establishment of standardised frameworks and guidelines for assessing and disclosing ESG-related information. Moreover, by conducting research and experimentation, the Lab can help identify innovative approaches to detecting and preventing greenwashing, thereby enhancing market transparency and investor confidence. Therefore, by actively engaging with stakeholders and fostering innovation, the Cambridge SupTech Lab can drive meaningful progress towards building a more sustainable and resilient financial ecosystem.



Cambridge SupTech Lab

Cambridge SupTech Lab


Jose Miguel Mestanza Hirakata

Cambridge SupTech Lab


Juliet Ongwae

Cambridge SupTech Lab


Kalliopi Letsiou

Cambridge SupTech Lab


Maryeliza Brasa and Samir Kiuhan-Vasquez

Cambridge SupTech Lab


Matt Grasser

Cambridge SupTech Lab


Matt Grasser and Kalliopi Letsiou

Cambridge SupTech Lab


Simone di Castri

Cambridge SupTech Lab

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