Tokio Marine & Nichido Fire Insurance Co., Ltd. (TMNF) tapped SESAMm for a joint research venture to predict future stock price movements and discovered two key findings:

1. NLP data from news and social networking websites can have strong relationships with investor behavior. Thus, it’s possible to forecast investors’ rational reactions to changes in data and price movements based on those relationships.
   
   
2. NLP data proved to help anticipate tail events. For example, given the macroeconomic environment of the last 10 years, the stock market performed well. So in this context, investors are sensitive to negative narratives in times of uncertainty, such as the 2015 market sell-off, the U.S.-China trade war, the coronavirus pandemic, and the start of the Ukraine-Russian war, and post their concerns online.

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 text sentiment from news data with a neural network.”
– Tokio Marine & Nichido Fire Insurance Co. Ltd representative

Extract 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 impact of news and social networking data on investor behavior for stock and bond markets, transforming text information into knowledge usable by TMNF. For instance, when the model detects a negative narrative raising uncertainty in the market, investors can use this signal to reduce their risk exposure.

Predicting future stock price movements from news and social media data

Tokio Marine Nichido and SESAMm’s joint research found that natural language data from news and social networking sites effectively predict future stock price movements. In the case involving the pandemic, for example, there was a time lag of as long as a month between the time COVID-19 became news and the time it affected the U.S. stock market (Figure 1). By using SESAMm’s technology to analyze news data during this period, the team found that US news and social networking sentiment had already deteriorated sharply before stock prices reacted. This sentiment deterioration is due to the fear of the coronavirus-spread effect on the global economy. In an all-time high S&P 500, U.S. investors did not initially consider this risk. In comparison, HSI companies were closer to the coronavirus spread risk, resulting in HSI investors reacting ahead of those in the U.S.

The model can calculate sentiment for each company by analyzing the news of individual companies. It’s also possible to create a composite to measure the sentiment related to a stock index. The sentiment data also helps management and investor relations because it provides a quantitative means of understanding the extent to which investors are concerned about certain news about their company.

Verifying the results

Verification using Japanese has revealed that the timing of bottoming and ceiling of text sentiment precedes those of stock prices. The collaborating team compared the performance of:

• A model that uses only orthodox financial and economic data as inputs
• A model that considers NLP and financial and economic data, confirming that the latter could generate higher alpha

Since measuring sentiment is mean reversionary by nature, the TMNF team believes it provides good support for position management during rallies and crashes. It’s also valuable for avoiding forced loss-cut at the bottom when liquidity temporarily evaporates and the market crashes.

Expanding the research to other use cases

In addition to analyzing the stock market, Tokio Marine Nichido also expanded the scope of the research to include R&D on using natural language data in trading U.S. high-yield bonds. Research shows that NLP data can help provide a hedging signal for the negatively skewed high-yield market (Figure 3) by capturing deteriorating text sentiment (Figure 5). For example, these signals can inform investors to reduce positions before market reactions.

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 is 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 here:

The European Union faces a significant internal rift as its largest economies take opposing stances on the bloc's Corporate Sustainability Reporting Directive (CSRD) and CSDDD (Corporate Sustainability Due Diligence Directive), highlighting the delicate balance between environmental ambition and economic competitiveness in today's regulatory landscape.

A Continental Divide

According to recent reports, Germany and France—two of the EU's economic powerhouses—are pushing for a two-year delay to the CSRD implementation. This stance contrasts sharply with Spain and Italy, who advocate for maintaining the current timeline while potentially offering concessions to smaller businesses.

On one hand, at the Choose France summit on May 19, 2025, French President Emmanuel Macron called for the European Union to abandon the CSDDD, citing concerns over its potential impact on European competitiveness. Macron's stance aligns with German Chancellor Friedrich Merz, who also advocates for the law's repeal, arguing that it imposes excessive burdens on businesses, especially amid global competition from the U.S. and China. While some EU member states and industry leaders support revising or delaying the directive, others, including left-wing politicians and NGOs, defend it as essential for upholding European values and sustainability goals.

Spanish Environment Minister Sara Aagesen and Economy Minister Carlos Cuerpo, on the other hand, emphasized in a letter to the European Commission that sustainability reporting "supports the values and the priorities of the EU even beyond our borders, setting an example of leadership." Meanwhile, Italy's finance minister Giancarlo Giorgetti specifically urged against delaying CSRD for the tens of thousands of companies already preparing to report this year.

Why France and Germany Are Pushing Back: The Competitive Concerns

The Franco-German resistance to the current CSRD and CSDDD timeline stems from several key economic and practical concerns:

Administrative Burden on Businesses

German Finance Minister Jörg Kukies highlighted that approximately 13,000 German companies would be subject to extensive reporting requirements, with each needing "to provide around 1,000 data points or at least explain why fewer are provided." This represents a massive administrative undertaking, particularly for smaller enterprises with limited resources.

Economic Fragility and Global Competition

France's pushback comes amid broader economic concerns. The French government described the CSRD rules as "hell for companies," reflecting anxiety about imposing additional costs during a period of economic vulnerability. Both countries fear that excessive regulatory requirements could further weaken their competitive position against less-regulated economies, particularly the United States under the Trump administration, which has shown hostility toward environmental regulations.

Overlapping Regulatory Frameworks

German officials have pointed to the problem of multiple, uncoordinated sustainability reporting regimes. Kukies noted that "every CFO could tell absurd stories about how the same data has to be reported multiple times,"  arguing for a more streamlined approach where "each data point only has to be reported once."

Specific Reform Proposals

The German government has proposed significant changes, including:

• Postponing the CSRD application deadline by two years (to 2027) for large companies
• Increasing company size thresholds for reporting from €50 million in turnover to €450 million, and from 250 employees to 1,000
• Eliminating sector-specific reporting standards that would create additional complexity
  

Implications for Businesses and Investors

This regulatory uncertainty creates significant challenges for businesses operating across the EU. Companies face difficult strategic decisions about whether to proceed with sustainability reporting preparations or wait for potential rule changes.

For investors, this division introduces several critical considerations:

1. Reporting Inconsistency: Different implementation timelines across EU countries could create a patchwork of disclosure standards, complicating investment analysis.
2. Competitive Impacts: Companies in countries maintaining stricter timelines may face higher short-term compliance costs than competitors in countries securing delays.
3. ESG Data Reliability: Delays could affect the quality and comparability of ESG data, potentially undermining investor confidence in sustainability metrics.
4. Strategic Positioning: Forward-thinking companies that continue sustainability reporting preparations regardless of potential delays may gain competitive advantages in attracting ESG-focused investment.

Looking Ahead

The European Commission plans to publish an "omnibus" proposal to simplify green rules for businesses, aiming to enhance competitiveness while responding to global regulatory pressures, including potential deregulation under a second Trump administration in the U.S.

This internal EU debate reflects a broader global tension between advancing sustainability standards and addressing immediate economic pressures. Navigating this evolving regulatory landscape will require flexibility, foresight, and a balanced approach to ESG integration for businesses and investors alike.

As this situation develops, stakeholders should closely monitor European Commission decisions and prepare for multiple regulatory scenarios across the EU's diverse economic landscape.

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.

Introduction

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.