On 5 December in New York, SESAMm was selected to take part in The BIG Alternative Data Showcase Event, one of the major events focused on alternative data applied to the asset management industry. Organised by our partner Eagle Alpha, this very first step in the US market for SESAMm represented a unique opportunity: to bring our expertise and solutions to the biggest asset managers globally.

Since September, SESAMm’s business has been growing steadily. In addition to the ongoing discussions we have with several significant asset managers, two major groups have signed a contract with us: one of the top 5 asset managers in Japan that has more than $100 billion of assets under management; and one of the top 10 asset managers in France with more than $50 billion under management.

In addition to this great news, we recently signed partnerships with two major data providers in the USA, one of them with Eagle Alpha. Shortly after our agreement, from a list of 450 data vendors, Eagle Alpha selected 12 of them to be part of the BIG Alternative Data Showcase Event, SESAMm being the only French company chosen. This event in New York City represents the biggest one globally on alternative data applied to asset management. That was an opportunity for our company to present for the very first time L’Humeur des Marchés and our expertise in the United States.

Sponsored by Deloitte, Lowenstein Sandler, S&P Global Market Intelligence and CRUX, Eagle Alpha’s event showed us how unique and exceptional the US market is in terms of business opportunities for SESAMm. Gathering renown international hedge funds, investment banks but also major companies from other sectors with needs in Artificial Intelligence and Data Analysis, this event proved to be one of the most interesting and exciting we have attended so far.

Following this event, with the multiple contacts and leads for both partnerships and business contracts that have been gathered, our journey home only strengthens our intention to plan future business trips in the United States and our entry on this market.

In private equity, as in most industries, decision-making counts on accessing accurate and valuable information. However, these firms often encounter significant challenges when sourcing reliable data, especially when dealing with small, private companies. This article dives into the complexities of identifying high-quality information on smaller companies and underscores its value in investment decisions, operational efficiency, and risk management. It also explores how advanced artificial intelligence (AI) technologies are revolutionizing the identification of these risks, leading to higher rewards and more secure investments, thus providing a competitive edge.

The challenge of identifying valuable information for Smaller Firms

Lack of valuable data

Sturgeon's Law, which states that "Ninety percent of everything is crap (or noise)," becomes particularly relevant in the context of data sourcing. For private equity and investment firms focused on small companies, finding the golden nuggets of information amid the overwhelming amount of digital noise can be daunting. The data available on these companies is often sparse, fragmented, and difficult to uncover using conventional methods. This scarcity of reliable information makes it challenging for private equity firms to make informed decisions, heightening the risk of overlooking critical issues that could impact their investment process.

The difficulties extend beyond just locating information. Many small companies operate without a significant online presence or may not be required to disclose as much information as publicly traded firms. This lack of transparency can further blur critical data points. Furthermore, the data that is available is often unstructured, residing in various forms such as social media posts, obscure local news articles, or industry-specific reports. Extracting meaningful insights from these disparate sources requires sophisticated data processing capabilities, which traditional methods often lack. As a result, private equity firms are left with a significant challenge: how to separate valuable data from the noise without missing critical risk indicators, thereby optimizing their deal sourcing and investment strategies.

Diverse language and terminology

Smaller firms frequently face existential risks, and the potential rewards for identifying these risks early on can be significant for the private equity firms that invest in them. However, mainstream methods of risk identification often fall short, as these companies may not use standardized language to describe materiality. Instead, risks are discussed in varied and context-specific ways, complicating the task of recognizing relevant information. Therefore, it is essential to adopt a specialized approach that analyzes and decodes these firms' unique terminologies and business idiosyncrasies, ultimately translating them into a standardized language that can be effectively used in risk assessment.

The diversity in language is not just a barrier to risk identification but also to the communication of these risks within and between private equity firms. When a small firm uses industry-specific jargon or localized expressions to describe potential threats, it can lead to misunderstandings or underestimations of the actual risk. For instance, a manufacturing startup in a developing country might describe supply chain disruptions in terms that do not translate easily to a global investor’s risk framework. Additionally, cultural differences in how risk is perceived and reported can lead to further complications. This linguistic diversity necessitates the use of advanced natural language processing tools that can interpret data through a common lens while considering industry-specific contexts. For an insurance company, understanding financial models, insurance principles, and regulatory frameworks is crucial. Conversely, assessing risks for a beauty company requires a focus on product safety, consumer preferences, and market trends. By appreciating the specific contexts of each industry, private equity firms can better identify and evaluate potential risks, enhancing decision-making processes, risk and portfolio management strategies, and operational efficiency.

The dynamic nature of the industries themselves further complicates the challenge. For example, the tech industry evolves rapidly, with new risks emerging as technologies develop and consumer expectations shift. What might be considered a negligible risk today could become a significant issue tomorrow as regulatory landscapes, market conditions, and technological advancements alter the playing field. In contrast, industries like agriculture or real estate might have more stable risk profiles but are subject to sudden changes due to environmental factors or policy shifts. This variability across industries means that a one-size-fits-all approach to risk assessment is inadequate. Private equity firms must adopt flexible, industry-specific risk models that can adapt to the unique characteristics and evolving landscapes of the sectors they invest in, thus optimizing their AI capabilities.

The Power of AI in Enhancing Risk Management in Small Firms

AI technologies, particularly natural language processing (NLP) and machine learning algorithms, are important tools for private equity firms aiming to monitor and manage risks in small firms. These technologies can sift through vast amounts of data, extracting the valuable 10% and identifying patterns, trends, and subtle nuances in the language used to describe risks. By detecting these patterns, AI can reveal potential risks that might not be immediately apparent through traditional methods. This proactive approach to risk identification allows firms to address issues before they escalate, providing a more comprehensive and nuanced understanding of the risks facing small firms.

AI's ability to process unstructured data is particularly valuable in this context. Many of the risks that small firms face are discussed informally in places like social media, niche blogs, or local news outlets. Traditional risk management tools might overlook these sources, but AI-powered tools can analyze them in real-time, detecting emerging threats as they develop. Moreover, AI can cross-reference these insights with structured data from financial reports, regulatory filings, and other formal documents to create a holistic risk profile. This multidimensional analysis helps private equity firms not only identify risks but also understand their potential impact, enabling more informed, data-driven decision-making that enhances operational efficiency and competitive edge.

Beyond risk identification, AI also enhances risk mitigation strategies. By continuously monitoring data and learning from new information, AI systems can adapt to changing conditions, offering updated risk assessments that reflect the latest developments. This dynamic approach allows private equity firms to stay ahead of potential issues, making it possible to implement preventative measures rather than reacting to crises after they occur. In this way, AI capabilities contribute significantly to the optimization of risk management processes.

How SESAMm’s Advanced Technology Enhances Risk Assessment

SESAMm’s TextReveal® is at the forefront of this technological revolution, enabling private equity firms to efficiently navigate the vast digital landscape and extract the crucial information needed for informed decision-making. Through our proprietary data lake amounting to over 25 billion online articles with 15 years of historical data and our AI algorithms, TextReveal® can quickly identify and retrieve valuable insights, even when the information is deeply buried or highly specific. The tool's ability to analyze and understand the diverse language and terminology used in discussions about risks on the web empowers private equity firms to objectively assess the materiality of certain risks or identify emerging threats that have yet to be formally recognized.

TextReveal® goes beyond merely identifying risks—it categorizes them, providing context that helps private equity firms understand the severity and relevance of each risk. For example, if a small biotech firm is mentioned in discussions about regulatory hurdles, TextReveal® can determine whether these mentions are isolated incidents or part of a broader trend. It can also assess whether the language used suggests an imminent threat or a longer-term concern, enabling firms to prioritize their responses accordingly. Additionally, TextReveal® integrates sentiment analysis, which can gauge the overall tone of discussions surrounding a company, offering further actionable insights into potential reputational risks.

SESAMm has developed a proprietary metric – the Intensity Score, which calculates an event's relevance based on its news coverage and sentiment. It uses negative sentiment, article dispersion, and empirical ESG risk measures to determine how likely an article is to represent a high-risk controversy. The Intensity Score gives TextReveal users a clear understanding of which events require their attention.

Users can also opt to receive email alerts for the more severe controversies, ensuring they’re always aware of significant risks.
In addition to the severity, controversies are also categorized by risk and sub–risk type, making it easy to analyze specific areas of concern.

Moreover, SESAMm's platform is designed to be intuitive and user-friendly, making it accessible to investment professionals who may not have a technical background. This ease of use ensures private equity firms can quickly incorporate AI-driven insights into their risk management processes without a steep learning curve. By streamlining the data analysis process, TextReveal® allows firms to focus on strategic decision-making, confident they have a comprehensive understanding of the risks and opportunities associated with their investments and portfolio companies. This level of operational efficiency and optimization is key to maintaining a competitive edge in the fast-paced world of private equity.

TextReveal’s Risk Assessment module enables deep company and thematic research in multiple languages through on-the-fly keyword searches. Users have full access to articles, sentiment analysis, and trending topics to get a complete understanding of the risks. We’ve even developed an AI Text Summary feature that provides a quick summary of a selected article, saving time and enabling a faster analysis.

In summary, the integration of AI tools and natural language processing technologies is transforming risk management in private equity, particularly for firms dealing with small, private companies. By leveraging these advanced tools, private equity firms can enhance their due diligence processes, better monitor risks and controversies, and ultimately make more informed investment decisions that lead to higher rewards and operational efficiency.

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 request a demo, contact one of our representatives.

The Securities and Exchange Commission (SEC) has voted to cease defending its climate disclosure regulations in court, marking a significant shift in U.S. corporate sustainability reporting requirements. This decision, announced on March 27, 2025, under Acting Chairman Mark Uyeda's leadership, has substantial implications for the ESG landscape.

The Decision

The SEC’s withdrawal from defending its climate disclosure rules comes amidst ongoing litigation before the U.S. Court of Appeals for the Eighth Circuit. Originally adopted in 2024, the rules were intended to provide investors with standardized information about companies' climate-related risks, emissions, and the financial impact of those risks. Uyeda justified the withdrawal by stating, “The goal of today’s Commission action is to cease the Commission’s involvement in the defense of the costly and unnecessarily intrusive climate change disclosure rules.”
The regulations faced swift opposition from industry trade groups and Republican state attorneys general, who argued the SEC had overstepped its authority. The legal challenge quickly gained momentum, and with the change in SEC leadership, the agency opted not to continue defending the rules.
Caroline Crenshaw, the lone Democratic commissioner, sharply criticized the move. She described it as an attempt to “unlawfully undo valid regulations” and accused her colleagues of “watching the rule’s demise while eating popcorn on the sidelines.”

Market Implications

The decision reintroduces regulatory uncertainty for companies. Many had already begun preparing internal systems and compliance structures based on the 2024 rules. Now, in the absence of a federal standard, they may be forced to rely on voluntary reporting frameworks or navigate a fragmented set of expectations from investors, states, and international markets. This lack of uniformity is likely to lead to inconsistent reporting practices and difficulties in cross-company comparisons.
Investors, meanwhile, will face greater challenges in accessing reliable and comparable data on climate-related risks. Without SEC-mandated disclosures, much of the burden of transparency shifts to individual companies and third-party ESG data providers. Investors will likely need to increase due diligence efforts, adopt varied methodologies, and potentially absorb higher costs to obtain the data needed to manage climate risk effectively.

The Broader Context

This decision does not exist in isolation—it aligns with a broader trend of regulatory rollback on climate issues in the U.S. and signals a widening divergence between American and international disclosure approaches.

The divergence creates complexity for multinational corporations that must now navigate different expectations in different jurisdictions. This fragmentation may also create competitive disadvantages for U.S.-listed firms, especially those competing for capital in more disclosure-forward markets.

SEC Leaves the ISSB

In a related move that further isolates the U.S. from international sustainability efforts, the SEC recently withdrew from two key ISSB governance groups: the IFRS Sustainability Jurisdictional Working Group and the Sustainability Standards Advisory Forum. These groups are central to building alignment on global ESG disclosure standards.

The SEC’s exit from these forums signals a significant retreat from coordinated climate disclosure initiatives and weakens the U.S. role in shaping global ESG norms.

Market Response

Despite the rollback, some companies may continue voluntary climate-related disclosures. Those that have already invested in reporting infrastructure may opt to maintain transparency to meet investor expectations, mitigate reputational risk, and support long-term sustainability goals.

Simultaneously, ESG data providers and rating agencies are expected to play a more prominent role in filling the information gap. Financial institutions may also develop their own internal frameworks to evaluate climate risks, further privatizing what was once a public regulatory function.

Looking Forward

The path ahead remains uncertain. State-level legislation may introduce a patchwork of new rules. Global investors—particularly those with mandates in the EU or UK—may continue demanding robust disclosures from U.S. firms. And future federal administrations could choose to reintroduce or reshape mandatory disclosure regimes.
In the interim, companies and investors will need to adapt by maintaining flexible reporting systems, monitoring evolving voluntary frameworks, and diversifying their sources of ESG data. While federal requirements may have receded, the underlying investor interest in climate-related financial risk is not going away. Climate disclosure, in one form or another, remains firmly on the radar.

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.