In our newest research, "ESG Controversies: A Comparative Study of Public vs Private Sectors," our ESG and Research & Analytics teams present an exhaustive study on the nuances of ESG controversies across public and private sectors. We combined artificial intelligence with our extensive dataset of over 25 billion documents to extract ESG controversies in both sectors. This research highlights the increased visibility and scrutiny of public companies compared to the more discretion in private companies. A case study on IKEA uncovers challenges in product safety and human capital, underlining the importance of proactive sustainability practices. The study examines these sectors' alignment with major ESG frameworks, including the UN Global Compact and Sustainable Development Goals, offering invaluable insights for enhancing corporate ESG strategies.

‍Key takeaways:

• Public companies are under constant observation, leading to higher exposure to ESG risks such as pollution, labor disputes, and governance failures. This visibility is partly due to regulatory requirements for transparency, making every aspect of their operations subject to public and investor scrutiny.

• Private companies, while benefiting from less regulatory oversight, encounter substantial repercussions from ESG controversies. These can manifest as sudden shifts in investor confidence, challenges in securing financing, or damage to reputation, underscoring the critical need for comprehensive risk management approaches that encompass environmental, social, and governance factors.

• The case study on IKEA provides an in-depth look at specific issues like product recalls due to safety concerns and the complexities of managing a global workforce. It highlights IKEA's efforts to implement forward-thinking sustainability initiatives and human capital management practices as key components of its corporate strategy, demonstrating the tangible benefits of such measures in mitigating ESG risks.

ESG controversies and breaches of SDG goals vary notably between public and private sectors. Public companies frequently encounter more visible and consistent ESG risks, while private companies, although subject to less scrutiny, experience significant impacts when controversies occur.

Dive deeper into ESG controversies and uncover strategies for navigating these challenges effectively. Download "ESG Controversies: A Comparative Study of Public vs Private Sectors" and equip your organization with the insights needed to enhance your ESG practices for a sustainable future. Fill out the form below to access your copy and lead the way in corporate sustainability.

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In our recent webinar titled "ESG Controversies: A Comparative Study of the Public and Private Sectors," Sylvain Forté, CEO, and Alexandre Tiesset, Head of ESG, explored the transformative impact of Artificial Intelligence (AI) on understanding and evaluating ESG controversies, especially in the context of public versus private sectors. This in-depth discussion provided unique insights into the challenges and opportunities presented by ESG data analysis.

One of the primary challenges highlighted was the disparity in data availability between public and private companies. Public entities are subject to stricter disclosure requirements, which often results in a wealth of data facilitating ESG assessment. In contrast, the opacity of private companies complicates the evaluation of their ESG performance, creating a demand for innovative solutions to ensure equitable and accurate comparisons across the investment spectrum.

SESAMm, with its pioneering AI-powered text analysis tool TextReveal, stands at the forefront of tackling these challenges. By analyzing billions of documents, TextReveal extracts crucial ESG insights, addressing the data scarcity in the private sector and enabling a more nuanced understanding of ESG controversies.

The webinar underscored the importance of data normalization to counteract biases, allowing for more precise comparisons across sectors and companies. With the help of AI, SESAMm can conduct analyses across a vast number of entities, offering investors a comprehensive view of potential risks and controversies.

The Ikea case study served as a prime example of SESAMm's capability to perform deep dives into specific companies. The analysis revealed Ikea's slightly higher environmental controversies than the consumer discretionary sector average, including accusations of greenwashing related to deforestation. On the social front, Ikea faced challenges with product safety, human rights breaches, data leaks, and privacy violations, such as the 2021 lawsuit against Ikea France for alleged privacy violations of staff.

Furthermore, the webinar touched on the challenges Ikea faces under specific Sustainable Development Goals (SDGs), including health and well-being (due to product recalls and workforce health concerns), Sustainable Cities, and Responsible Consumption and Production. Despite these issues, Ikea shows fewer problems related to industry innovation and infrastructure, and peace, justice, and strong institutions, indicating areas of better risk mitigation.

In conclusion, the integration of AI into ESG evaluation marks a significant advancement in investment analysis. As the demand for sustainable investment options grows, the need for sophisticated tools to analyze ESG controversies becomes increasingly evident. The webinar's insights highlight AI's potential to enhance our understanding of ESG risks and opportunities, paving the way for more responsible investing.

Watch the webinar replay now:

Dive deeper into ESG controversies and uncover strategies for navigating these challenges effectively. Download "ESG Controversies: A Comparative Study of Public vs Private Sectors" and equip your organization with the insights needed to enhance your ESG practices for a sustainable future. Fill out the form below to access your copy and lead the way in corporate sustainability.

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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.

In our most recent webinar, "Unmasking Greenwashing: How to Identify Genuine and Deceiving Sustainability Initiatives with AI," Sylvain Forté, SESAMm’s CEO and Co-founder, discussed our recent ebook entitled with the same name focusing on the vital role of AI in identifying and understanding ESG controversies, focusing on greenwashing and reputational laundering.

Greenwashing, the act of misleadingly portraying products or services as environmentally friendly, and reputational laundering, where companies create a facade of ethical behavior, are increasingly prevalent challenges. These practices mislead investors and consumers, obscuring the reality of a company's environmental impact. Our webinar highlighted the complexity of these issues and their relevance across various industries.

We discussed how AI technology is revolutionizing the detection of greenwashing and reputational laundering. By analyzing vast amounts of web data, including news articles, social media, and public records, AI uncovers patterns and red flags that might indicate deceptive practices. This is particularly pertinent for stakeholders in the financial sector, such as private equity firms, who must navigate the intricate landscape of ESG compliance and sustainability.

Our recent research study underscored the importance of this technology. We found that mentions of greenwashing and related controversies have grown exponentially over the years. This increase aligns with a rising global awareness of environmental issues and the demand for corporate transparency. AI's ability to sift through and analyze this growing body of data is invaluable in providing accurate, timely insights into potential ESG risks.

We also noted an interesting trend: while greenwashing mentions are increasing, their growth rate is slowing down. This suggests that as regulatory frameworks around ESG become more formalized and the market becomes more educated, instances of unintentional greenwashing decrease. It's a sign that clearer rules are helping companies avoid these pitfalls.

Our analysis also revealed that different industries experience varying levels of exposure to greenwashing claims. Sectors like food, drug retail, and oil and gas have seen significant increases in accusations of reputational laundering. However, we also observed a positive trend in the fashion industry, where regulatory frameworks have led to a decrease in greenwashing mentions.

Lastly, we highlighted the importance of distinguishing between negative and positive ESG mentions. While it's crucial to identify and monitor greenwashing allegations, it's equally important to recognize and support genuine sustainability initiatives. Our analysis showed that positive ESG initiatives often have a more significant impact on public perception than negative ones.

Watch the webinar replay now:

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.

In our latest research, “Unmasking Greenwashing with AI” our ESG and Research & Analytics teams provide a comprehensive analysis of greenwashing trends using AI-powered text analysis.

• Notable increase in mentions of greenwashing, with a 3.3x rise since 2021.
• This increase suggests both a real growth in deceptive sustainability practices and a rise in public awareness.
• Greenwashing represents 55% of all reputational laundering, underscoring a major shift towards environmental deception.
• Surge in climate lawsuits with over 3x increase in climate change lawsuits since 2020, highlighting legal risks for misleading practices
• It underscores the financial sector’s dual role in both contributing to and fighting against greenwashing through its investment practices

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SESAMm recently hosted a webinar led by Lead Solutions Engineer Leo Shamash. The session focused on the critical role of Artificial Intelligence in identifying and managing ESG (Environmental, Social, Governance) risks and controversies, especially in private companies.

During the webinar, Leo Shamash shared insights on how SESAMm’s advanced AI technologies analyze millions of daily articles to provide accurate ESG risk assessments.

Why is this important for private equity firms? Because traditional methods of risk assessment are often labor-intensive and limited in scope. SESAMm’s AI-driven approach offers a scalable, efficient solution. The webinar also touched on SESAMm's extensive data lake comprising over 20 billion documents, making it one of the largest repositories for tracking ESG risks and controversies.

Watch the webinar replay now:

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Join us for our next webinar on November 15 at 4 PM Paris time/10 AM New York time, and watch Sylvain Forté share his insights into how artificial intelligence can help distinguish between genuine sustainability efforts and greenwashing. Book your spot.

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 landscape of the finance sector is evolving rapidly. A few weeks ago, SESAMm announced a new addition to its technologies, Generative AI. This tool is key to enhancing decision-making, streamlining operations, and staying ahead in the industry.

During our recent webinar, CEO Sylvain Forté sheds light on SESAMm’s integration of Generative AI for private equity and asset managers. If you missed the session or need a refresher on the key takeaways, watch the replay here:

For in-depth insights into the future of finance powered by Generative AI, check out our Generative AI series.

• Part 1.
• Part 2.

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.

CEO Sylvain Forté demonstrates SESAMm’s NLP platform TextReveal® ESG Alerts and Monitoring for public and private companies at FinovateSpring 2023. He uses Wirecard, a German FinTech company that went bankrupt following a fraud accusation, as an example to illustrate the platform's ability to identify potential controversies and assign them severity scores automatically.

Furthermore, he demonstrates another use case with Twilio, an API messaging and phone services provider, which had previously been exposed to major cybersecurity issues. TextReveal ESG Alerts and Monitoring was able to immediately identify the controversial events, providing valuable insights to users.

In this video, Sylvain Forté also showcases what differentiates our solution from competitors while shedding light on our massive 20-billion article data lake, our advanced AI technology and algorithms, and how we combine both to provide major financial institutions, private equity funds, and banks with timely and accurate data to help them detect any issues with investments, suppliers, or clients.

Watch the full recording:

Reach out to SESAMm

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

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.

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Tokio Marine & Nichido Fire Insurance Co., Ltd. (TMNF) tapped SESAMm for a joint research venture to predict future stock price movements. SESAMm provided various NLP indicators, such as digital sentiment calculated for single stocks or indices (seen as an entity), as well as its experience in machine learning to work on this task.

These studies concluded with two key findings:

1. Relationships exist between NLP data from news and social networking sites and investor behavior under specific circumstances. Researchers and investors can use the “digital sentiment” as an indicator of investor sentiment to anticipate price changes. They can then use this anticipation for a specific company or, more generally, any entity that can be isolated in a text (like an index).
   
   
2. By focusing on more stressed situations, like the 2015 market sell-off, the U.S.-China trade war, the coronavirus pandemic, and the start of the Ukrainian crisis, we could show that digital sentiment is beneficial in times of significant stress in the market. Digital sentiment more accurately reflects the stress level in these complicated situations. It, therefore, helps to predict stock price movements more accurately in these stressed cases, providing a tail hedge. It’s not biased by an excess of confidence linked to the “central banks put” for instance.

Providing safety and security since 1879

Tokio Marine Insurance Company was first established in 1879. Over the years, it has added products and services, acquired other businesses, and merged with other companies to eventually become Tokio Marine & Nichido Fire Insurance Co., Ltd. Commonly called Tokio Marine Nichido today, the company is a property and casualty insurance subsidiary of Tokio Marine Holdings, the largest non-mutual private insurance group in Japan. Its products and services provide safety and security to its clients and partners, contributing to more fulfilling lifestyles and business development.

One of the company’s philosophies is to be a good corporate citizen and fulfill its social responsibilities, including protecting the global environment, promoting human rights, creating a responsible working environment, and contributing to society and individual local communities. Recently, the Emperor of Japan awarded Tokio Marine Holdings, Inc. the Medal with Dark Blue Ribbon for donating to the Japan Student Services Organization to support students who face financial difficulty during the

COVID-19 pandemic. Individuals, corporations, or organizations are awarded the Medal with Dark Blue Ribbon for their outstanding contributions to the public.

Transforming and accepting the challenge to grow

According to TMNF, “The business environment surrounding the insurance industry is changing at a faster pace than ever due to changes in demographics, advances in technologies, such as autonomous driving and AI, and longer-term trends, such as the intensification and frequent occurrence of natural disasters, as well as further progress in digitalization due to the COVID-19 pandemic.”

“The business environment surrounding the insurance industry is changing at a faster pace than ever…”

“While these changes in the business environment pose a threat, we consider them to be excellent opportunities for transformation and the creation of new value.” So they’ve adopted the concept, “Transformation (“X”) and Challenge to Growth 2023: Aiming to be the company most chosen for quality and its passion.” Ultimately, it strives to support customers and local communities in times of need while contributing to social responsibility. Five social issues that it will prioritize are:

• Global climate change and the increase in natural disasters
• The increased burden of long-term care and healthcare due to the aging of society and advances in medical technology
• Technological innovation and its effects on the environment
• Symbiotic society and responding to the novel coronavirus
• Industrial infrastructure and how it supports economic growth and innovation

Leveraging a partner with the right technology

To secure and protect its clients’ assets while elevating social issues, Tokio Marine Nichido sought out an edge in the stock market. Under these circumstances, it was fortunate that TMNF discovered SESAMm in 2020 through the Plug and Play Japan program, a platform with an event that connects Japan to markets abroad. SESAMm had presented its NLP alternative data solution, TextReveal®, to which TMNF considered the platform for access to alternative data and sought collaboration with the SESAMm team for a research project.

“SESAMm has the technology to extract sentiment from news data with a neural network.”
– Tokio Marine & Nichido Fire Insurance Co. Ltd representative

Extracting relations between NLP data and the financial market

In 2021, Tokio Marine Nichido Insurance began collaborating with SESAMm to develop an AI analytics model for alternative data. It models the effect of news and social networking data on investor behavior for stock and bond markets. In other words, it structures text information into knowledge usable by TMNF.

Monitor risks and topics

NLP data can improve the understanding of the market’s behavior by exhibiting the most important topics over time, with a direct indication of the importance of the topics through the text volume (Figure 1).

Researchers can also use it to focus on a specific topic or a certain period. For instance, a short analysis of the most frequent keywords in the press, which preceded the market fall during the COVID-19 pandemic, showed the significant predominance of pandemic-related terms (Figure 2).

Focusing on the equity market

NLP tools provide specific data, like sentiment, to get more detailed information at the company level and for many underlyings. Indicators for equity indices, for instance, can be calculated and provide a clean sentiment to monitor markets.

In many situations of stress over recent years, such sentiment proved to be an early indicator of the market’s future degradation. For example, there was a time lag of as long as a month between the time COVID-19 became the main news focus and the time it affected the U.S. stock market. By using SESAMm’s technology to analyze news data during this period, the team found that the U.S. digital sentiment had already deteriorated sharply before stock prices reacted (Figure 3).

This sentiment deterioration occurred because of the fear of the coronavirus’s spread’s effect on the global economy (see Figure 2). Even with an all-time high S&P 500, U.S. investors didn’t initially consider this risk. In comparison, HSI companies were closer to the coronavirus spread risk. So as a result, HSI investors reacted ahead of their U.S. counterparts. In other words, by using natural language data, it was possible to capture a risk overlooked by U.S. investors but related in the publicly available texts and take action ahead of the market deleveraging.

Generalizing the results to the credit market

Tokio Marine Nichido also expanded the scope of the research to U.S. high-yield bonds index trade. In the credit market, a high yield has a high beta, which makes its risk comparable to the equity market.

Research shows that, on a risk-adjusted basis, the NLP-data-built signal has a positive and consistent performance through the timeline compared to the U.S. HY T.R. index benchmark (Figure 4). Its performance has a low correlation with the index (Figure 5), so the sentiment is diversifying. It not only acts as a diversifier but delivers higher returns than the benchmark when the U.S. High Yield market sold off (Figure 6). As such, the NLP signal diversifies, hedges, and protects against adverse periods. It provides a mechanical pick-up in risk-adjusted return when running alongside traditional strategy.

The NLP signal outperforms the index in realistic backtest conditions, including long allocation only, turnover constraints, and trading fees (Figure 7). The quantitative model integrates some macro indicators, but the previous NLP signal induces the main source of outperformance and risk mitigation.

TMNF is also applying the research to estimate the Fed’s stance—hawkish or dovish—using natural language data, too. It hypothesizes that the market will be focused on the Fed’s stance on interest rate hikes in the next few years.

“The model developed in collaboration with SESAMm is simple in structure, yet, it’s an orthodox and robust model that uses valid data as input.”

Summarizing the collaboration

In developing models, Tokio Marine Nichido believes it’s essential to consider “what data to consider” and to keep it simple. And TMNF achieved these tenets. The model developed in collaboration with SESAMm is simple in structure, yet, it’s an orthodox and robust model that uses valid data as input which is preferable to a risky over-fitting by increasing complexity.

Get in touch with SESAMm

To learn more about Tokio Marine Nichido’s case study or to request a TextReveal demo, reach out to us.