As 2026 kicks off, I want to take a moment to reflect on the year we’ve just closed. 2025 was an important year for SESAMm, marked by both significant milestones and quieter, foundational progress. We launched new AI-powered reports, welcomed major clients, expanded our coverage, and saw our technology move deeper into real decision-making workflows.

None of this would have been possible without the trust and engagement of our clients, partners, advisors, and team. Your willingness to challenge us, work with us, and build alongside us continues to shape what SESAMm becomes.

Below, I’ve shared a few moments from 2025 that helped move us forward, along with what we’re looking ahead to in 2026.

Growing Through Strong Partnerships

In practice, SESAMm’s data is used in very different ways. It supports large-scale monitoring across thousands of suppliers and assets, while also enabling in-depth analysis of individual companies and local markets.

In 2025, collaborations with organizations such as Sayari, BNP Paribas, Caisse d’Epargne Rhône Alpes, ENGIE, Clarity AI, and Inrate reinforced something we have believed from the beginning: understanding risk today requires data that is both scalable and usable within real decision-making workflows.

More importantly, these partnerships reflect the confidence placed in the quality of SESAMm’s data and its breadth of use. In one case, a financial institution used supplier monitoring to identify early signals of forced labor risk in a supply chain that had previously passed traditional audits. That insight did not replace existing processes, but it changed the questions being asked and the actions that followed.

Welcoming New Advisors

We were also proud to welcome Guy Gresham and Magnus Billing as advisors this year. Their experience, perspective, and intellectual rigor have already challenged us in the best possible way.

As we continue to build SESAMm for the long term, their guidance helps ensure that our technology remains both ambitious and grounded in how risk is actually understood, assessed, and managed in the real world. In a market that is evolving quickly and sometimes unpredictably, that discipline matters.

From AI Promises to AI in Practice

AI dominated conversations again this year. What changed in 2025 was less the technology itself, and more how our clients engage with it.

Initially, the question was whether AI could reliably identify risks. Today, that question has been answered and the conversation has shifted. Clients are asking which risks are most important, which require action, and how to prioritize limited time and resources.

At SESAMm, this translated into concrete product evolution, all with the same objective: supporting both large-scale monitoring and deeper, decision-level analysis. We launched and expanded AI-powered reports, introduced UN Global Compact violation screenings, and significantly increased the number of companies and infrastructure projects we cover globally.

AI is no longer treated as an experimental layer. Our clients are using it as a core component for identifying and tracking risks over time. The question they now face is not whether AI can surface risk, but how to decide which signals deserve attention.

ESG Is Changing, Whether We Like the Term or Not

AI The ESG landscape itself is going through a transformation. Regulatory pressure is uneven. In some regions, expectations are tightening while in others, frameworks are being diluted or politicized. At the same time, the term “ESG” is itself losing ground; it means too much and therefore explains too little.

That has not changed, however, is the nature of the underlying risks. Human rights, forced labor, biodiversity loss, governance failures, and reputational exposure are becoming increasingly visible and material to investors, companies, and regulators alike. The conversation is shifting from broad labels to specific facts, with greater attention paid to the events and the evidence that inform both scores and decisions. This shift from labels to evidence is where SESAMm’s approach is particularly relevant.

Looking Forward

As we move further into 2026, our focus remains clear. We will continue to invest in signal quality over noise, depth over surface-level insight, and tools that help our clients act, not just observe. We will keep expanding coverage where risk is hardest to see, particularly in private markets, and will continue to develop cutting-edge AI agents to support client workflows.

The question for 2026 is not simply how much risk data organizations have, but how effectively they interpret and prioritize it in practice.

Above all, we remain committed to building technology that supports our customers and partners with clear, reliable insight into risk, grounded in reality as it is.

Thank you again to our clients, partners, advisors, and team for your trust and engagement over the past year. We look forward to continuing this journey together!

Wishing you a wonderful and successful year ahead,

Sylvain Forté
CEO, SESAMm

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By Magnus Billing, SESAMm advisor, with insights from Sylvain Forté, CEO of SESAMm

Investors have faced so-called “black swan” events throughout history: unexpected crises with severe consequences, often rationalized only in hindsight. Yet in an era defined by generative AI and vast, real-time data lakes, the question arises: could such events be understood and acted upon before they unfold?

The 2023 U.S. regional banking crisis offers a striking case study. The rapid collapses of Silicon Valley Bank and Signature Bank revealed how quickly stress can spread and how difficult it remains to connect early warning signs across sources.

While traditional financial analysis focuses on fundamentals such as capital ratios, liquidity positions, governance, and earnings, a new class of tools is expanding the lens. AI-driven controversy data aggregates and analyzes millions of public sources, from regulatory statements to media and industry discussions, to detect emerging issues as they surface. It does not replace quantitative and fundamental analysis; it complements it by tracking the visibility of risk as it enters public conversation.

This combination of approaches may offer investors a fuller picture: the structural risks visible in balance sheets, and the narrative risks revealed through public dialogue. To test this idea, we revisited the 2023 crisis through both perspectives, starting with what traditional analysis could have shown and what it missed.

Traditional Analysis and Its Blind Spots

In hindsight, the vulnerabilities of regional banks such as Silicon Valley Bank and Signature Bank were visible before the start of 2023. Unrealized losses on long-term securities, heavy reliance on uninsured deposits, and exposure to interest-rate risk pointed to potential liquidity stress. Yet these indicators were neither fully recognized nor connected in the market.

Traditional analysis has a tendency to evaluate banks based on their specific niches: Silicon Valley Bank focused on technology and venture financing, while Signature Bank served commercial real estate and digital asset clients. However, this approach risks overlooking the common and shared structural factors: concentrated depositor bases, high sensitivity to interest rate changes, rapid growth, and weaknesses in governance. Few, if any, observers recognized how rapidly these vulnerabilities could interact and escalate in a modern, digitalized banking environment.

While financial reports contained the data, there was little discussion connecting these risks in the public domain. But what about controversy data? Would it have caught the impending crisis? To find out, I asked Sylvain Forté, CEO of SESAMm, to provide an AI perspective.

What the Data Showed: Signature Bank

Signature Bank displayed a gradual pattern of emerging risk visible through public discussion. From mid-2022 onward, controversy data showed a rise in coverage related to governance practices, management oversight, and deposit concentration risks, often in the context of its ties to the digital-asset industry.

Importantly, it was not the crypto exposure itself that led to the bank’s collapse. The bank even announced in December 2022 that it would reduce its crypto-related business. Instead, the FDIC’s Supervision of Signature Bank report concluded that, “the root cause of SBNY’s failure was poor management. SBNY’s board of directors and management pursued rapid, unrestrained growth without developing and maintaining adequate risk management practices and controls.”

From a controversy perspective, those signals were publicly visible but fragmented. As shown in the chart above, AI-powered monitoring could have aggregated them into a clear view of a sustained drift in governance-related discussions, offering an early indication that oversight and internal controls were under pressure and risk was increasing.

What the Data Missed: Silicon Valley Bank

In contrast, Silicon Valley Bank presented a markedly different pattern. While controversy data registered some activity in late 2022,  including investor reactions to financial forecasts and coverage of routine business operations, these signals were fundamentally different in character from Signature Bank's governance-related warnings.

The September 2022 increase reflected market disappointment with financial guidance rather than operational or governance concerns. The subsequent activity captured normal business news, such as arranging syndicated loans. Critically, there was minimal public discussion of the bank's balance-sheet structure, unrealized losses, or depositor concentration risk until the crisis was already unfolding in March 2023.

This example underscores a key distinction: AI controversy monitoring excels at capturing reputational, governance, and operational risks as they enter public dialogue, but may not surface structural financial risks that remain confined to regulatory filings and analyst reports.

Lessons from Both Cases

The contrast between these two banks illustrates the complementary roles of quantitative and fundamental financial analysis vs AI-driven controversy monitoring.

In Signature Bank’s case, controversy data captured a steady accumulation of governance-related warnings, a slow build-up of risk visible through public discussion.

In Silicon Valley Bank’s case, the risks were structural but not yet discussed, leaving little for AI-powered controversy data to detect.

As Sylvain explains, “AI controversy monitoring helps investors understand how and when risks start to emerge in public dialogue. It does not replace fundamental analysis. It complements it by showing when the conversation begins to shift.”

Conclusion

Black swan events are often rationalized only in hindsight, but the 2023 regional banking crisis suggests a more nuanced reality. Some signals existed. What remained difficult was connecting them across sources before stress became contagion.

AI-driven controversy monitoring proved effective at surfacing governance and operational risks as they entered public dialogue, as Signature Bank demonstrated. Yet structural financial vulnerabilities like those at Silicon Valley Bank may not generate discussion until crisis forces the conversation, underscoring that no single lens captures all risk.

The advantage lies not in prediction, but in preparation: combining the structural risks visible in balance sheets with the narrative risks revealed through public discourse. In an era of real-time data and generative AI, the question is no longer whether information exists, but whether investors can connect it before it becomes consensus.

Reach out to SESAMm

TextReveal’s web data analysis of over five million public and private companies is essential for keeping tabs on ESG investment risks. To learn more about how you can analyze web data or to request a demo, reach out to one of our representatives.

Sustainability trends have become ubiquitous in the business world, mainly due to the attention ESG is receiving. To state the obvious, this is a positive trend as it helps push companies to consider their impact on the environment, employees, and customers and ensure their governance practices are sound. However, it also incentivizes actors in the business world to try to game the system through marketing campaigns to improve their reputation.

Through the use of artificial intelligence and other technologies, we embarked on a mission to analyze the sentiment on the web and uncover to what extent companies are incurring reputational laundering techniques to deceive investors, customers, and other stakeholders but also to identify the ones that are actually performing actions to have a positive impact around them.

This analysis dives into the concept of greenwashing and reputational laundering. It reveals the nuanced interplay between genuine sustainability efforts and deceptive practices, offering a new lens to distinguish genuine from false corporate sustainability claims.

Beyond Greenwashing: Reputational Laundering

Let’s start with some definitions. Reputational laundering is deliberately hiding unethical behavior with highly visible positive actions. Greenwashing is just one component of reputational laundering. Another component is the social aspect of it, and it includes various forms of color washing such as purplewashing, pinkwashing, purpose washing, etc. So far, in 2023, greenwashing accounted for 55% of all the volume of reputational laundering mentions on the web. So, the remaining 45% represents color-washing.

TerraChoice defines greenwashing as “the act of misleading consumers regarding the environmental practices of a company or the environmental performance and positive communication about environmental performance."

Colorwashing, on the other hand, refers to a strategy used by organizations to create a positive public image by associating themselves with specific causes, ethics, or moral standpoints.

Beyond the conventional understanding of deliberate greenwashing, there’s a more nuanced concept and less discussed: unintentional greenwashing, where companies inadvertently convey misleading environmental claims. This can occur due to a lack of understanding of the true impact of their products or services, unverified claims, overlooking hidden consequences, unintentional confusion in marketing materials, or insufficient transparency. While these companies may not have malicious intent, their actions can inadvertently misrepresent their environmental efforts and mislead consumers about their commitment to sustainability.

Reputational laundering at a glance

Over the past eight years, reputational laundering mentions have increased steadily. However, from 2021 onwards, they’ve grown a staggering 3.3x. The mentions of reputational laundering are coming from different topics, from false advertising, and misleading practices to lawsuits regarding greenwashing. Furthermore, we have observed a growing number of references regarding the declining trust of the public in corporate pledges, such as those related to 'net-zero' climate goals.

This increase can be attributed to two main reasons: the actual increase in reputational laundering and, more interestingly, the growing awareness from stakeholders (i.e., Investors and eco-conscious consumer base).

According to a report published by the UN Environment Programme (UNEP), climate change lawsuits have continuously surged over the past five years.
Consequently, we analyze mentions of lawsuits related to environmental breaches and detect a significant increase in 2021 – which continues to the present day.

Lawsuit mentions have increased by more than 3x since 2020. These litigations span a spectrum of environmental issues, extending well beyond planned obsolescence practices by major consumer goods manufacturers. We also observe the rise of youth-led climate change lawsuits, instances of oil spills, wildfires, pollution-related legal actions, and the pervasive issue of PFAS contamination.

Breakdown by type of washing

While greenwashing often dominates the conversation around reputational risks, it's crucial not to overlook the social dimension, which tends to receive less attention from the public. Since 2020, we've observed a significant uptick in mentions of greenwashing and its less-discussed counterpart, colorwashing.

Historically, up until 2020, the distribution of mentions leaned toward one-third greenwashing compared to two-thirds colorwashing. However, post-2021, this pattern has shifted. We've witnessed a rise in the frequency of greenwashing mentions, surpassing those of colorwashing and signaling an evolution in the focus of reputational laundering concerns.

During the COP27 conference at the end of 2022, a call was made to verify carbon and other environmental claims and show zero greenwashing tolerance. As a result, there has been a rise in scrutiny, and data now shows an increase in the number of allegations related to greenwashing. Here are a few examples:

June 2022: Head of Deutsche Bank’s DWS stepping after ‘greenwashing’ raids,
October 2023: Suncor accused of greenwashing
September 2023: Greenwashing cases against airlines in Europe, the US,

In analyzing advertisements, we found instances of reputational laundering through various means. Some companies engaged in social washing, while others used sportwashing to bolster their reputation. The mining and energy industries were particularly guilty of this practice. Meanwhile, the communication industry, including companies such as Netflix and Disney, was associated with black and whitewashing.

Inspecting the Regulatory Landscape

To analyze the regulatory environment of reputational laundering, we studied the effects of different legal frameworks and government organizations on greenwashing and other forms of reputational laundering. We measured the influence of legal frameworks and regulatory bodies on greenwashing by analyzing the quarterly growth of greenwashing mentions over the study period.

In this analysis, we define the concept of legal frameworks by capturing references related to the 'Green Claims' directive, Sustainable Finance Disclosure Regulation, EU Taxonomy, Green Product Certification, Fair Labeling and Advertising Act, Non-Financial Reporting Directive, FTC Act, FTC Green Guides, etc.

Concepts of Regulation bodies are defined by references to governments and Supranational entities (i.e.,  US government, FTC, SEC, Chinese government, Japanese government, etc.) or regulatory agencies established to safeguard the environment (United Nations Environment Programme (UNEP), Environmental Protection Agency (EPA), European Environment Agency (EAA), Intergovernmental Panel on Climate Change (IPCC), etc.)

Over the past three years, mentions of frameworks and laws have grown substantially, with increasing ESG scrutiny, new green claims guidelines, and a focus on sustainability and ESG reporting.

There has been a slight increase in the mentions of regulatory bodies over the years, mainly due to the growing interest in greenwashing, which has peaked during events like COP26 and COP27. Legal frameworks and regulatory bodies have played a significant role in the fight against greenwashing. Although there is no decrease in the mentions of this topic, the growth rate has reduced significantly. In fact, the quarter-on-quarter growth for greenwashing web mentions has been decreasing lately.

The trends reveal an interesting fact that there is a negative correlation between the growth in mentions of frameworks, laws, and regulatory bodies and the growth in mentions of greenwashing. Though the mentions of greenwashing are still increasing, the growth rate has significantly decreased from a 75% quarterly growth rate to 10% in the last year (except for spikes related to controversial events such as Greta Thunberg labeling COP26 as a “greenwash festival,” and not attending COP27).

Conclusion

As we navigate the landscape of corporate sustainability, it becomes evident that distinguishing genuine efforts from greenwashing is not just a matter of skepticism but a necessity. This exploration underscores the importance of vigilant analysis and the role of AI in unmasking deceptive practices. It calls for a collective commitment to transparency and accountability, empowering stakeholders to make informed decisions and advocating for a future where corporate responsibility aligns authentically with sustainable development.

At SESAMm, we used AI to study billions of articles and analyze greenwashing trends. Download this comprehensive ebook for an in-depth understanding of the evolving landscape of reputational laundering, notably greenwashing, and dive into its trends in the corporate world.

SESAMm’s AI Technology Reveals ESG Insights

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.