Watch CEO Sylvain Forté discuss SESAMm’s solutions for corporations focused on supply chain and client reputational risk monitoring during an interview with FF News at FinovateEurope last March.
Watch the full recording:
Watch CEO Sylvain Forté discuss SESAMm’s solutions for corporations focused on supply chain and client reputational risk monitoring during an interview with FF News at FinovateEurope last March.
Watch the full recording:
In theory, a portfolio with no ESG controversies signals low risk. In practice, experienced analysts treat it as a warning sign. The absence of alerts often reflects not resilience, but limited coverage, fragmented data, or incomplete aggregation. What looks like reassurance may instead point to a gap in visibility.
This dynamic came up repeatedly during our recent webinar, Private Markets in 2026: Macro Trends, ESG Shifts, AI Innovation and What It Means for Deal-Flow. The discussion highlighted how gaps in coverage and aggregation can shape investor perception, particularly when portfolios appear “quiet,” not because risks are absent, but because relevant information is not being captured.
This dynamic matters more than ever as private market due diligence intensifies. With fewer deals, longer holding periods, and higher selectivity, investors are spending more time scrutinizing assets before acquisition and monitoring them for longer after entry. Yet the informational foundation behind many ESG assessments has not caught up with these expectations.
Private assets operate under persistent disclosure constraints. Unlike public companies, most private firms do not produce standardized, recurring ESG disclosures, nor do they benefit from consistent analyst coverage. These gaps are structural and unlikely to disappear in the near term.
In this context, silence is ambiguous. A clean ESG screen may indicate the absence of material issues, but it may just as easily signal that no relevant information was captured. Language limitations, fragmented sources, and uneven coverage across geographies and asset types all contribute to this uncertainty.
This dynamic is particularly visible in secondary transactions. Deal teams often need to assess large portfolios under tight time pressure, with limited access to management and incomplete identifiers. In such cases, relying on the absence of signals can create false confidence rather than reduce risk.
Even when information exists, it is not always immediately actionable. Adverse media has become a valuable substitute where structured ESG data is limited, offering outside-in visibility into private assets. However, it is not without challenges. Without robust aggregation and cross-language consolidation, the same issue can appear repeatedly across multiple articles, jurisdictions, and languages, creating duplication rather than clarity. At the same time, gaps in coverage or weak filtering can allow other material risks to go undetected.
At the same time, some portfolios appear unusually quiet simply because the underlying assets fall outside the scope of traditional datasets. ESG and reputational expectations in private markets remain fragmented, with bespoke workflows driven by LP-specific requirements. This lack of convergence makes it difficult to distinguish between genuinely low exposure and analytical gaps.
More data does not automatically resolve this problem. Without traceability, source quality, and a way to assess financial, legal, or operational materiality, increased volume can add noise without improving decisions. In that environment, silence can be just as misleading as signal overload.
A core takeaway from the webinar was that point-in-time ESG assessments are no longer fit for purpose in private markets. A single diligence exercise conducted at entry cannot capture emerging governance failures, litigation, reputational issues, or supply chain risks over multi-year holding periods.
Instead, meaningful ESG visibility combines three elements:
This approach reframes ESG from a compliance exercise into a source of informational advantage. Rather than concluding that no alerts mean no risk, investors use ESG signals to guide follow-up questions, prioritize deeper diligence, and identify issues that were not visible at entry.
Private markets will continue to operate with imperfect information. Disclosure gaps, opaque supply chains, and bespoke reporting demands are inherent to the asset class.
Treating “no issues detected” as a conclusion creates false comfort. Treating it as a hypothesis, contingent on coverage quality and monitoring depth, aligns ESG analysis with how risk actually emerges in private assets.
Discover unparalleled insights into ESG controversies, risks, and opportunities across industries. Learn more about how SESAMm can help you analyze millions of private and public companies using AI-powered text analysis tools.
Over the past decade, many organizations have improved their carbon footprints, from recyclable and biodegradable packaging and single-use plastic to planting trees and reducing their greenhouse gas emissions. However, some businesses and companies looking to boost their eco-friendly image without committing to serious changes and addressing environmental issues have been associated with false green marketing. We call this "Greenwashing."
Greenwashing is a practice used by businesses to represent themselves as more sustainable than they truly are. Greenpeace and the Environmental Protection Agency define greenwashing as making false and misleading claims about a product's environmental benefits or practices, services, technology, or company practices. Greenwashing typically involves companies spending more money on advertising and marketing than on implementing sustainable business practices that minimize environmental impact. These false green claims can deceive consumers into believing that a product or company is more environmentally friendly than it is, leading to increased sales and profits. As a result, false advertising, misleading initiatives, and groundless claims have increased green investors' exposure to risks emerging from potential lawsuits from activist groups, image deterioration, and heavy losses in assets invested.
In recent years, new concepts have emerged alongside greenwashing:
When talking about greenwashing, the usual suspects are the oil and gas industry, the food and beverage sector, and other environmentally impactful industries. However, the financial industry has also been embroiled in its own greenwashing controversies.
DWS Group has been at the center of repeated greenwashing allegations. In April 2025, the firm was fined €25 million by German prosecutors for misleading ESG claims, building on years of scrutiny. It all started in 2021 with whistleblower claims that DWS overstated its ESG credentials, triggering investigations by both U.S. and German authorities. A police raid in June 2022 led to the CEO’s resignation, and in 2023, the SEC fined DWS $25 million for ESG misstatements. Lawsuits in Germany also allege false advertising around ESG. Greenpeace condemned DWS’s ESG bonus scheme as cosmetic rather than meaningful. Despite public commitments to sustainability, these controversies underscore a pattern of overstated ESG practices designed to attract investors.
BNY Mellon faced similar regulatory action. In May 2022, the SEC fined BNY Mellon Investment Adviser, Inc. $1.5 million for misleading statements about ESG integration in mutual funds. Although the funds were marketed as ESG-focused, the SEC found that BNY Mellon failed to apply ESG quality review as consistently as claimed, raising concerns about greenwashing in the financial sector.
It’s challenging to produce an accurate assessment of environmental, social, and governance (ESG) factors, which creates opportunities for companies to hide ineffective and fake green initiatives. According to Regtank, the main challenges to detecting greenwashing include:
These gaps lead to inaccurate ESG data and scores, allowing greenwashers to avoid accountability. Ultimately, detecting greenwashing requires careful scrutiny of company claims and a deep understanding of their supply chains and operations.
As greenwashing practices become more common, activist investors, journalists, and the general public are using social media, news outlets, and blogs to highlight false claims. Artificial intelligence (AI) has become an invaluable tool in the early detection of greenwashing by analyzing vast amounts of public data.
At SESAMm, we use generative AI and LLMs to identify greenwashing risks across billions of web-based articles. Our data lake covers over 25 billion articles in more than 100 languages from four million news sources, blogs, social media platforms, and forums, analyzing data on five million public and private companies. Through our AI platform, we generate reliable, timely, and comprehensive insights to detect greenwashing, monitor ESG controversies, and identify related risks.
The rise of greenwashing is not going unnoticed by regulators, as frameworks like the Corporate Sustainability Reporting Directive (CSRD) and the Corporate Sustainability Due Diligence Directive (CSDDD) directly target misleading sustainability claims and hollow marketing.
Looking ahead, greenwashing will continue to face intense scrutiny from regulators, investors, and the public. With evolving regulatory frameworks like CSRD and CSDDD, the pressure is on for companies to ensure genuine environmental responsibility—not just green advertising. At SESAMm, we believe that the combination of regulatory rigor and advanced AI technologies will play a critical role in uncovering false green claims and supporting investors in navigating ESG risks with greater transparency and accountability.
Discover unparalleled insights into ESG controversies, risks, and opportunities across industries. Learn more about how SESAMm can help you analyze millions of private and public companies using AI-powered text analysis tools.
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Discussions around nuclear weapons and defense have recently highlighted how differently investors interpret weapons exclusions. In particular, Russia’s invasion of Ukraine has brought security considerations back into focus across Europe and prompted some investors to revisit long-standing exclusion policies.
At the same time, regulatory frameworks such as the Sustainable Finance Disclosure Regulation (SFDR) encourage investors to screen portfolios for controversial activities and disclose how those risks are managed. However, these frameworks do not impose a single global definition of weapons exposure. As a result, policies can vary widely between institutions.
In responsible investment policies, the term “controversial weapons” has a relatively clear meaning. It refers to weapons that are prohibited or heavily restricted under international conventions because of their indiscriminate or humanitarian impacts.
Typical examples include:
Because these weapons are banned or widely condemned under international treaties, investors usually apply strict zero-tolerance exclusions. Any company involved in producing these weapons, or supplying critical components for them, is typically excluded from ESG-focused portfolios.
The broader category of weapons exposure is more complex and is where investor interpretations often begin to diverge. Recent discussions across Europe’s sustainable finance community have focused on whether defense companies should remain excluded from ESG portfolios, particularly in light of renewed security concerns following Russia’s invasion of Ukraine.
Many exclusion frameworks distinguish between controversial weapons and other forms of military-related activity. Companies may be involved in conventional weapons manufacturing, such as firearms, missiles, bombs, or military electronics. Others produce defense systems and equipment, including radar, communications technology, or aircraft components. Civilian firearms are also frequently treated as a separate category within exclusion policies.
In these cases, investors often rely on revenue thresholds rather than absolute bans. A company may be excluded if more than five to ten percent of its revenue comes from weapons manufacturing, while smaller or indirect exposure may still be permitted depending on the investor’s mandate.
A key challenge in these screenings is that a company’s weapons exposure is not always obvious from its core business description. A firm may supply components, software, or materials used in weapons systems or operate as part of a broader defense supply chain. This is particularly difficult to identify in private markets, where companies are not required to disclose detailed segment revenues or defense-related contracts.
As a result, defining and detecting weapons exposure requires clear policy definitions and structured screening logic. What counts as weapons involvement, and where the exclusion threshold lies, ultimately depends on each investor’s mandate and risk tolerance.
These questions are no longer abstract. Since Russia's invasion of Ukraine, major asset managers have visibly shifted their positions. Allianz Global Investors, for instance, updated its Article 8 fund policies in 2025 to allow defense companies. Global Trading UBS and Franklin Templeton made similar moves, each removing revenue-based weapons thresholds that had been standard practice for years. At the regulatory level, Hortense Bioy, Head of Sustainable Investing Research at Morningstar Sustainalytics, noted that "since the start of the war in Ukraine in 2022, it has become increasingly clear that geopolitics plays a more significant role in shaping the boundaries of sustainable investing than ethics." What these shifts share is a common thread: the thresholds and definitions that once felt settled are now being redrawn, which is precisely why screening frameworks need to be flexible enough to reflect each investor's current policy, whatever that may be.
Because exclusion policies are defined at different levels, it’s rarely as simple as establishing a generic exclusion list. Limited partners often impose their own restrictions or revenue thresholds, which general partners must apply alongside the fund’s internal ESG policy and regulatory restraints. In some cases, LP requirements may further restrict or override the fund’s baseline approach.
As a result, acceptable levels of exposure to activities such as conventional weapons can vary significantly across portfolios.
Screening frameworks, therefore, need to adapt to the investor’s policy rather than forcing the policy to adapt to the tool.
In this case, SESAMm’s AI-generated exclusion screening report can be customized to match each investor’s requirements. Threshold-based classifications help identify different levels of involvement, allowing investors to distinguish between companies with no exposure, limited exposure, or significant involvement in controversial activities. Each classification is supported by underlying evidence and source documentation, allowing analysts to verify the reasoning behind the flag.
This approach makes it possible to apply a consistent methodology across both public and private companies while remaining aligned with the investor’s specific exclusion framework.
Discussions around defense and responsible investment will continue to evolve as geopolitical and regulatory contexts shift. Recent debates around nuclear deterrence and defense participation illustrate how differently investors can interpret weapons exclusions, even when they operate under the same regulatory frameworks.
For investors, the challenge is therefore not only defining exclusion policies but ensuring that those policies can be applied consistently and transparently across portfolios. As definitions of weapons exposure vary, and as supply chains and private market structures add further complexity, screening frameworks must be capable of translating policy into clear, operational rules.
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