SESAMm Launches Controversy Exposure Score: A New Era for ESG Risk Analysis

Held from June 21–29, London Climate Action Week (LCAW) 2025 brought together over 45,000 participants across 700+ events, emphasizing London’s role as a global hub for climate finance and leadership. As geopolitical uncertainty clouds climate ambitions, this year’s event signaled a broader market pivot: investors are now prioritizing regions with regulatory clarity and policy momentum, namely Europe and Asia.

A joint survey from Bain & Company and the World Business Council for Sustainable Development, released during the week, found that 75% of global firms now prefer to invest in Europe or Asia for climate-related initiatives. Over half reported a declining appetite for U.S.-based projects, citing inconsistent federal climate policies and rising political risk.

Policy Signals from the UK

UK Energy Secretary Ed Miliband used the event to announce a bold step forward: the government will invest £30 billion annually in clean energy infrastructure through 2035. His remarks positioned the UK as a “clean energy superpower,” with a dual focus on energy security and economic renewal.

He also outlined plans for new corporate sustainability reporting standards, a move intended to improve transparency, build investor confidence, and ensure alignment with the UK's net-zero targets. These commitments were part of the UK’s post-Brexit green industrial strategy, distinguishing it from recent ESG policy slowdowns in Brussels and Washington.

Climate Finance and Market Confidence

 One of the most prominent themes throughout the week was capital mobilization. At the “Finance Live” forum, asset managers, banks, and insurers debated how to align their portfolios with net-zero goals while navigating geopolitical instability and rising greenwashing scrutiny. Key discussions included scaling blended finance vehicles, investing in transition technologies, and strengthening ESG data governance.

Meanwhile, sessions like the Nature Hub spotlighted biodiversity and natural capital, moving beyond carbon to more holistic definitions of environmental value. This reflects a growing consensus that an effective climate strategy must include nature-based solutions and ecosystem restoration.

The Broader Message: A Shift in Global Climate Leadership

While the U.S. backtracks on core climate regulations, London and Europe are entering a leadership void. For global investors, that means that developing a climate strategy now includes not only where to invest but also where to trust. In that context, LCAW 2025 offered both policy and finance updates and a credibility reset.

The takeaway is clear: in an age of fragmented regulation and climate politicization, market trust flows towards stability. London Climate Action Week didn’t just reflect that shift; it helped define it.

Online, Japan Investor Forum, July 2022.

Sylvain Forté, SESAMm's co-founder and CEO, discusses ESG data and its challenges. Further, he describes how to generate insights and reports on millions of companies, including micro-companies, using artificial intelligence and natural language processing.

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About SESAMm

To give you a bit of context, I’m CEO of SESAMm, a French company of around 100 people that has been in business for eight years and that specializes in artificial intelligence for finance, especially with a focus on ESG.

So we work with some of the largest insurance companies in Japan, such as Tokio Marine, Asset Management One, or Japan Post Insurance. And we have seen the rise of ESG investing in the past few years, especially in the past four years in Europe and in the U.S. And we see now this trend also in Asia and in Japan, more specifically.

Primary uses of ESG data

The primary uses of ESG that we see are first complying with regulation. That is the key priority for most asset managers, but also improving performance. Many quantitative teams are seeing ESG also as a way to have new factors integrated that could qualify to generate alpha in investment funds. ESG is also used a lot in order to better manage risk in portfolio and, finally, to better analyze sustainable investment opportunities.

ESG use cases

So a couple of the main use cases are detecting ESC controversies. So purely from the perspective of generating risk alerts, excluding assets that are not well rated in portfolios, or creating portfolios that contain best-in-class assets, meaning most sustainable assets.

And finally, I want to mention that this trend is really global. So it's across both public assets, equities, and bonds, and also across private equity. And we see private equity reacting very quickly to the ESG trend.

Traditional ESG data challenges

So now, let's discuss in more detail some of the key challenges of ESG data. Traditionally, ESG data is created by teams of analysts that are looking at individual companies that are gathering data from each of the companies, and that are then reading the press in order to complement that information. This approach is relevant, but it is hard to scale, and it presents some difficulty. Traditional ESG ratings agencies are, for example, MSCI or system analytics.

The problem with a lot of traditional ratings is that they don't cover small companies very well. And this is one of the key challenges currently in ESG is the lack of coverage. So it is very difficult to cover small caps, microcaps, and also private companies. In particular, in Asia, the coverage is very poor right now for ESG, and that means that many portfolio companies may not be covered by ESG rating. In Japan specifically, even large companies are sometimes not covered by traditional ESG providers. So that creates a lot of data inefficiency in the industry.

Another key challenge that we see in ESG right now is the frequency of ESG ratings. So oftentimes, ESG ratings are updated only one time per year or just a few times per year. And when ESG ratings are used for risk management, obviously, the market is moving much more quickly than one time or a few times per year.

In addition to that, we see that ESG ratings mostly takes into account information that is reported by management and does not take as much into account information that is from outside of the company. For example, in the case of government scandals, such as fraud scandals, it is actually better to have information that is not reported by the company but that also has an external point of view.

Lastly, the last key challenge I want to mention in ESG data specifically, and one challenge that I'm sure you are aware of in market data and fundamental data is that ESG data is oftentime, not point-in-time. So that means that you don't have a continuous dataset that has not been modified over time. ESG agencies tend to modify their ratings after the fact, and so that means that the rating that you will receive now for a data point in 2020 will not be the same that the rating that you would actually have received in 2020 point-in-time. That creates a lot of problems when you want to back-test data because you cannot reproduce actual historical results.

So these are all of the key challenges that we have identified in ESG data currently, and there are challenges in order to address the needs that we described. But there are actually some solutions that exist.

The solution to ESG data challenges

And one of the key solutions right now that is merging in ESG is the use of artificial intelligence, in particular, what is called natural language processing, meaning text analysis.

What we do at SESAMm and what some other providers do is detecting ESG risks and positive impact with regards to sustainability by analyzing automatically billions of articles and messages in real time. So as an example, we have 18 billion articles and messages from common news websites, from social media, from blogs and forums, and from company reports. And we automatically detect ESG themes and risk and perform sentiment analysis in order to understand whether a company may be exposed to an ESG controversy or whether a company may have positive impact with regards to sustainability.

Advantages of AI for ESG data challenges

And the advantage of AI in that context is that it solves a lot of the challenges that we discussed before. So it helps access higher frequency data, it helps cover small companies, private companies, it helps also find information that is independent, that is public, and that is not necessarily just reported by management, and it also is point-in-time information that can easily be backlisted.

How SESAMm tackles ESG data challenges

So I'll mention a couple of use cases to illustrate that in more detail. But basically, at SESAMm, we create an ESG datasets in order to track more than 90 different ESG risks and also the 17 sustainable development goals in order to precisely identify positive impact. And we do that on millions of companies, not just large public companies but also small caps and also private companies.

SESAMm ESG data use cases

Some of the use cases that I wanted to illustrate for that is using artificial intelligence in order to perform ESG monitoring using alerts. What that means is that we automatically generate ESG alerts on portfolios, for example, of equities or bonds on a daily basis, including portfolios of Japanese equities. And this data is then used by quantitative analysts and also fundamental managers to systematically exclude companies that are exposed to controversies in a portfolio. And this is a very efficient approach to systematically exclude companies that are not sustainable that are exposed to them.

Secondly, we have companies generate ESG signals by combining market data and ESG AI data to generate alpha. So basically, we create long-only and long-term portfolios, and we incorporate these ESG signals in order to improve the alpha of these portfolios.

The two last examples I wanted to mention, one is positive impact. So there is a specific framework called the UNSDGs for sustainable development goals, which is well suited to automatically detecting positive impact actions by a company, such as implementing, for example, a new net zero carbon policy. And we automatically track these announcements and these positive actions that companies perform in order, again, to share this information in the form of alerts to help fundamental managers track the sustainability actions of their portfolio companies and automatically report on them without having to do manual research.

The last use case I wanted to illustrate, and it's going to be my last point, is due diligence in private equity. So this is not only applicable to public assets but also to private assets. As an example, we have the Carlyle Group, a very large private equity company in particular with the Japanese team, and we have them generate various kinds of analytics at the stage when they evaluate the company. And in particular, we help them monitor and track potential ESG risk and sustainability factors which are very important to assess potential private assets opportunities. So this is the last use case that I want to mention. And as you can see, there are many opportunities in a growing field in ESG that started in Europe and came out to Asia. But there are also a lot of the challenges which artificial intelligence can help solve in some cases and which are illustrated with some examples.

Thank you very much.

Human rights concerns took center stage in November, with rising scrutiny on how digital platforms and luxury brands safeguard vulnerable users and workers. Across the market, allegations of child exploitation, extremist activity, and labor abuses exposed significant governance and oversight gaps. The month’s top three most controversial companies were Roblox Corporation, Snap Inc. (Snapchat), and Tod’s, each facing escalating legal and regulatory pressure.

#1: Roblox Corporation: Intensifying Allegations of Child Exploitation

Roblox, the video game developer, experienced a surge of human rights–related controversies, driven by lawsuits and criminal cases involving child exploitation and online extremism. Multiple families in the United States filed suits alleging that predators used the game to groom and coerce minors, in some cases leading to severe psychological harm.

Regulators also increased pressure. The Texas Attorney General sued the company, accusing it of violating safety laws and misleading parents about the risks associated with young users. Additional criminal cases surfaced in the US, Ireland, and Argentina, where adults were convicted of grooming minors through Roblox. The company faced further backlash after its CEO referred to the child predator crisis as an “opportunity,” prompting criticism even as Roblox highlighted new age-verification tools aimed at improving safety.

#2: Snap Inc.: Social Messaging Platforms Under Renewed Scrutiny

Snap Inc., known for its messaging app Snapchat, emerged as the second-most controversial company in November following several serious incidents involving minors. In the United States, a missing 13-year-old girl was found in a Pennsylvania basement after meeting a man on Snapchat, who has since been charged with human trafficking and sexual assault. Another investigation led to the arrest of a New York man after Snapchat flagged suspected child sexual abuse material on his account.

At a broader level, new research from the Canadian Centre for Child Protection revealed widespread online sexual violence among youth, with Snapchat cited as one of the primary platforms involved. The company was also named in a major lawsuit filed by US school districts against Meta, Google, Snapchat, and TikTok, alleging that platforms suppressed internal research on youth harm and failed to implement meaningful protections.

#3: Tod’s: Supply Chain Labor Abuses Trigger Legal Action

In the luxury sector, Tod’s faced heightened scrutiny following new developments in an ongoing investigation into labor exploitation at its supplier factories. Italian prosecutors expanded their probe into three company executives, citing evidence of serious labor violations involving 53 workers employed by subcontractors. Issues raised included long working hours, low wages, inadequate safety standards, and poor living conditions.

Authorities also highlighted potential negligence and omissions by management, arguing that Tod’s failed to act on inspection findings that documented the abuses. Prosecutors have requested a six-month advertising ban and previously sought judicial administration over the company’s supply chain controls.

Conclusion

November’s top controversies underscore increasing pressure on companies to ensure robust human rights protections, both online and across global supply chains. As regulators, law enforcement, and civil society intensify oversight, firms in technology and consumer markets face rising expectations to demonstrate stronger safety systems, transparent governance, and proactive risk management.

Reach out to SESAMm

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