Introducing SESAMm’s New AI-Powered Secondaries & Credit Screening
July 22, 2025
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5 mins read
Screen smarter. Act faster. Flag hidden risks at scale.
Speed and accuracy are critical in due diligence, especially when screening for reputational or compliance risks across large portfolios. That’s why we built SESAMm’s Secondaries & Credit Screening report: a faster, smarter way to assess exposure to restricted and controversial business activities.
How it works
Designed for investors, compliance teams, and financial institutions, this report uses SESAMm’s generative AI and large language models (LLMs) to analyze millions of documents and flag companies involved in sensitive sectors.
With just a list of company names, it highlights potential involvement in:
Fossil Fuels & Nuclear
Weapons & Military Equipment
Predatory Lending
Gambling & Betting
Adult & Violent Content
Severe Human Rights & Labor Violations
Tobacco, Alcohol & Recreational Drugs
Each result includes linked sources and a clear explanation, providing not just a flag but the context behind it.
Fast, Transparent, Scalable
Whether you're conducting secondary deal due diligence, reviewing a loanbook, or aligning portfolios with exclusion lists, this new report offers:
Scalable, fast batch screening: Upload a list of companies and get standardized, structured results in minutes.
Transparency: Each flag is backed by a justification and includes access to cited sources.
Faster decisions: Get standardized Excel outputs in minutes.
Deeper insight: Uncover risks that go beyond traditional industry classifications.
A New Standard for Risk Screening
Already in use by leading financial firms, the Secondaries & Credit Screening report brings clarity to complex decisions, helping teams flag risks earlier, faster, and more confidently.
Ready to Get Started?
Reach out to see a sample report or request a custom screening of your own list. With SESAMm’s Secondaries & Credit Screening, your next due diligence process just got faster and smarter.
Generative Artificial Intelligence has burst onto the scene, bringing with it significant ESG challenges, particularly around data privacy, labor practices, and corporate governance.
A major issue is the source of AI training data, with lawsuits against OpenAI, Anthropic, and Google DeepMind over alleged copyright violations. Global regulatory bodies are also investigating AI companies for anti-competitive behavior and privacy breaches.
Concerns over transparency in AI and the spread of misinformation continue to grow, with AI models accused of generating false or biased content. Additionally, worries about cybersecurity vulnerabilities, such as data leaks and hacking risks, have further fueled scrutiny. Labor and working conditions also remain a concern in the industry, with reports of low wages and weak protections, while whistleblowers call for better safeguards and highlight governance instability.
What does the GenAI landscape look like for ESG issues? Read on to find out.
OpenAI: Navigating Copyright Infringement and Regulatory Scrutiny
As a leader in Gen AI, OpenAI has faced increasing scrutiny over ESG issues, particularly copyright infringement. It has been sued by major news outlets, publishers, and music labels for allegedly using copyrighted content without permission to train its AI models. Beyond copyright concerns, OpenAI has been fined for privacy violations and is under regulatory scrutiny, including antitrust investigations in the U.S. and Europe. Data security risks, working conditions for AI data workers, and internal governance challenges—such as whistleblower concerns and executive upheaval—have also drawn criticism.
Anthropic: Balancing Ethical AI Practices with Data Privacy Challenges
Despite lower volumes of ESG controversies, Anthropic still faces scrutiny over data privacy, ethical AI, and corporate governance. The company has been sued for allegedly using copyrighted material in AI training and accused of bypassing anti-scraping rules. Security concerns grew after vulnerabilities in its Claude AI model and a confirmed data leak. Its ethical AI stance has also been questioned over reported military ties. Meanwhile, former employees have called for stronger whistleblower protections, highlighting transparency and accountability concerns.
Microsoft AI: Facing Antitrust and Intellectual Property Controversies
Microsoft's AI controversies have grown into serious legal challenges from 2023 to 2025. The company faces lawsuits over its Copilot chatbot, raising intellectual property concerns. Ongoing antitrust inquiries are examining Microsoft’s AI partnerships, while publishers have filed copyright claims against the company. With investigations by U.S. regulators, the EU, and UK watchdogs, scrutiny has intensified globally. Microsoft’s hiring practices have also come under fire, particularly its recruitment of key talent from AI startups, raising concerns over potential anti-competitive behavior.
DeepSeek: Data Privacy and Ethical Use in AI-Powered Discovery
Although relatively new, DeepSeek has been the center of attention for the past few months. It has been involved in anti-competitive practices scandals over its disruption of OpenAI and issues linked to data privacy and cybersecurity. Countries like Australia, South Korea, France, and India have criticized and, in some instances, banned the AI platform. Additionally, DeepSeek has been questioned about its supply chain and forced labor practices.
Mistral AI: Open-Source Development and Accountability in AI Systems
Mistral AI, a French AI startup, has been hit with data privacy and cybersecurity controversies, anti-competitive practices, and senior management issues.
The rise of Gen AI has come with significant ESG challenges. Its major players, like OpenAI, Anthropic, and Microsoft, face issues such as copyright infringements, privacy violations, labor practices, and environmental impacts. As regulators step up their investigations, these firms will have to focus on transparency, ethical practices, and sustainability or risk additional controversies.
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.
As generative AI has grown from a fledgling concept to a force disrupting most industries, its broader implications have come under scrutiny. Public perception of generative AI has also evolved significantly due to its association with various Environmental, Social, and Governance (ESG) factors. In this article, we’ll offer an extensive ESG analysis of generative AI, focusing on how different industries react to it, the ESG risks it potentially fuels, and the ESG positive impact events it has given rise to.
Generative AI: Public Perception Since Launch
Generative AI was initially met with widespread enthusiasm as the next evolutionary step in artificial intelligence. OpenAI's ChatGPT garnered significant attention quickly upon its release in 2022, as it amassed 100 million monthly active users in just two months post-launch. However, as its capabilities have become more powerful and universal, many ESG controversies have emerged, impacting the public sentiment towards the technology. A notable drop in sentiment polarity was observed from October to December of ‘22, going from 0.4 to 0.22. The decline in polarity was attributed to some critical topics, notably the environmental toll of its energy consumption and the ethical difficulties posed by its potential to disseminate false information.
* Polarity, a proprietary metric developed by SESAMm, ranging from -1 to 1, represents the aggregate of positive and negative sentiment.
Generative AI and its Implications on ESG
In What Industries Is Generative AI Mentioned More Often?
As expected, the IT industry was initially the most mentioned, along with Generative AI. However, as the technology became more widespread, other sectors have garnered more attention among web publications and social media. In particular, the communication and finance sectors are capturing a substantial share of the attention. In particular, data privacy in finance and communications are the main concerns, and fraud for finance is also being widely discussed on the web.
ESG Controversies Fueled by Generative AI
When we looked at ESG controversies and risks in detail, we found that most of the attention and mentions are related to social risks, particularly Human Rights (right to privacy), labor rights, and customer relations (customer privacy). Governance has also gotten its fair share of ESG controversies, primarily focused on anticompetitive practices (copyright infringement). On the environmental side, controversies are concentrated on water consumption (by Gen AI tools) and climate change, specifically energy consumption. However, the number of mentions and controversies has decreased considerably.
Data Breaches: The Focal Point
By far, the lion's share of ESG controversies and mentions gravitate towards social risks, specifically data breaches. From Italy banning Chat GPT in April to Samsung’s alleged data leak in August, controversies around data privacy have been among the most concerning topics surrounding Chat GPT ESG risks. In just five months, mentions of data breaches went from virtually 0% to over 10% of total mentions.
Digging deeper into data breaches at companies, we found that the number of breaches did increase significantly after generative AI tools became available. In particular, we see that the number of internal (employees) vs. external (non-company affiliated) data breaches increased by almost 50% when using generative AI tools from 14% to 21%.
The Silver Lining: ESG Initiatives Generated by Generative AI
Despite all the risks and controversies emerging, generative AI is also an enabler of positive ESG initiatives. Interestingly, on the positive impact side, we see a similar volume of mentions of initiatives on the three ESG dimensions.
Generative AI has shown promise in optimizing energy use, reducing waste, and even modeling and mitigating the impacts of climate change. On the environmental side, we see a rapid increase in mentions related to its applications in efficiency and productivity, asset reliability, operational safety, lower energy consumption, and reduced environmental impact.
The technology also has the potential to revolutionize healthcare by enabling more accurate and early diagnosis, thereby contributing to social well-being. Generative AI could also transform web surfing and make it easier for users to navigate the internet and find or generate information.
Conclusion
As our analysis shows, generative AI is bringing unprecedented capabilities and complex ESG risks and controversies. We expect to see it evolving, with public sentiment shifting and industries grappling with its ESG implications. But we are still in the very early stages of this new trend and will continue monitoring its evolution.
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.
SESAMm Incorporates Generative AI to Enhance ESG Risk Mitigation and Process Efficiency in the Finance Sector
FOR IMMEDIATE RELEASE
PARIS, France - July 12, 2023 - SESAMm, a leading player in financial technology, announces a transformative initiative to incorporate Generative AI solutions into its operations and product offerings. This strategic move is geared towards assisting financial firms in enhancing risk mitigation focused on ESG controversies and streamlining their processes.
The implementation of Generative AI follows a three-pronged strategic approach. This comprises the integration of large language models into their tech stack, the development of a client-facing conversational agent, and fostering a culture of AI utilization across all teams.
"With Generative AI, we are not only enhancing our internal processes but also focusing on the development of new features that redefine industry standards," stated Sylvain Forté, CEO & Co-founder of SESAMm. "These include intuitive dashboards, automated ESG/SDG event analysis tools, and a client interaction chatbot - all created to streamline data interaction and boost efficiency in risk management."
The integration of Generative AI has significantly enhanced SESAMm's product functionality already. This includes quicker and more intuitive interaction with data and introducing new features, such as ESG/SDG event summarization and automatic competitor searches for public and private companies.
SESAMm is also employing Generative AI for advanced risk mitigation. "Our innovative approach provides our clients a virtual team of ESG analysts and experts for detecting risk and ESG controversies, enhancing their risk mitigation strategies in a robust and comprehensive manner," Forté added.
SESAMm is preparing to launch a suite of AI-powered features later this year. "These new features, powered by Generative AI, reinforce our commitment to developing solutions that enhance risk mitigation and streamline processes for financial firms," Forté emphasized.
To explore more about SESAMm's Generative AI solutions and how they can boost your firm's operations, watch the video below:
Also, make sure you join our upcoming webinar, where Sylvain Forté will discuss live the future of fintech with Generative AI and how SESAMm is incorporating Generative AI into its processes and products. To register for the webinar, click here.
About SESAMm
SESAMm is a leading artificial intelligence and NLP (natural language processing) technology company serving global investment firms, corporations, and investors, such as asset managers, banks, private equity firms, hedge funds, and index providers. With over 100 employees and six offices worldwide, SESAMm celebrated its 9th anniversary in 2023.
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