The ESG Scorecard: A Deep Dive into The U.S Private Equity Landscape

METZ, LORRAINE, FRANCE, March 22, 2023 – SESAMm, a rising fintech company, announced today the opening of a new business location in Singapore. The expansion into Singapore marks a significant milestone for the company as it seeks to extend its reach and tap into the thriving Southeast Asian market.

The new location will be the company’s first business residency in Southeast Asia, where private equity, public equity, and asset management are ripe for solutions focused on alternative data sources, particularly those sourced with NLP solutions. Singapore will serve as a hub for the company’s regional operations, driving growth through new business development.

“We are thrilled to expand into Singapore, a move that represents a significant milestone in our growth strategy,” said Sylvain Forté, SESAMm CEO. “Singapore is a key financial center in the region, and our presence here will allow us to serve our existing clients better and tap into new business opportunities.”

Recently, SESAMm closed its Series B2 round with €35 million from France and U.S. investors along with Singapore-based venture capital firm AFG Partners, a firm that recognizes the significant growth and potential in the region.

“As a fund backed by investors from the financial services sector, AFG’s specialization and our unique network of investors and ecosystem partners provide a platform for global fintechs to scale regionally across Asia,” said Ivan Ong, Principal at AFG Partners. “SESAMm’s proven traction in international markets positions it well to enter Asia, and we see clear strong appetite from financial institutions and corporates to adopt their solution. We look forward to scaling the business across Asia with them,” said Ong.

The new location will support employee growth, with plans to expand the team in the coming months. Singapore business will be led by Thibaut Gunsey, Head of Sales—Asia, who brings nine years of financial-industry experience to the company.

“I am excited to broaden my role within SESAMm at such a pivotal moment in its growth,” said Gunsey. “Our Singapore office will allow us to better serve our local clients and regional growth, and tap into new business opportunities. I look forward to leading the local team and working with new clients to achieve their business goals.”

SESAMm’s expansion into Singapore comes as the company continues to experience strong growth. The company’s focus on innovation and customer service has earned it a reputation as a leading player in the fintech industry.

About SESAMm

SESAMm is a leading NLP technology company serving global investment firms, corporations, and investors, such as private equity firms, hedge funds, and other asset management companies. SESAMm provides datasets and NLP capabilities to generate alternative data for use cases, such as ESG and SDG, sentiment, private equity due diligence, corporate studies, and more. With access to SESAMm’s massive data lake, comprised of 20 billion articles and messages and growing, its clients can make better investment decisions. With offices in Metz, Paris, Tunis, London, Tokyo, New York, and soon, Singapore, the company is well-positioned to serve clients across the globe.

For more information about SESAMm and its products and services, please visit sesamm.com.

Media contact:

Jorge Alvarez
Chief Marketing Officer
press@sesamm.com

Over the past years, the for-profit childcare sector in France and the United States has moved from a largely quiet corner of the healthcare and social assistance industry into a subject of sustained public, regulatory, and investor scrutiny. Criminal convictions, government inspectorate findings, parliamentary inquiries, securities litigation, and a wave of investigative journalism ask the same question: Does the ownership and financing model that now dominates the sector come at the direct expense of child safety and care quality?

To help answer that question, we took a look at the controversies surrounding the industry and examined that question through media and ESG-controversy data, tracking mention volume and controversy-tagged coverage across five major operators spanning both French and US Markets, from January 2019 through August 2026:

• People & Baby - France
• Babilou - France
• Les Petits Chaperons Rouges / Grandir - France
• La Maison Bleue - France
• KinderCare Learning Companies - United States

This article combines whole-market trends with a narrower, controversy-specific signal to distinguish genuine escalation in safety and governance failures from routine growth in industry coverage, studying the case of one of the sector's most heavily implicated operators: People & Baby.

For-profit Childcare Market ESG Controversies

Mention volume holds flat from 2019 into early 2022, when pandemic closures and suspended inspections suppressed the incidents that generate coverage, though not the underlying risk. The break came in June 2022, when an infant died at a People & Baby crèche in Lyon, France after an employee gave her caustic drain cleaner. A staff member received a 25-year criminal sentence, and the government commissioned a sector-wide review. From 2023 onward, the pattern stops reverting, and each cycle peaks higher than the one before it.

In 2023, a sector-wide IGAS report concluded that the industry showed "institutionalized mistreatment" and called for a "cultural change." Five months later, in September, two investigative books appeared in the same week: Le Prix du Berceau and Babyzness, each documenting understaffing, restricted meals, and abuse. Their reach was sectoral rather than targeted, and the parliamentary hearings and regulatory crackdowns that followed pulled in operators with no incident of their own.

The following year compounded the effect on both sides of the Atlantic. Les Ogres (Victor Castanet, September 18, 2024), a 416-page investigation built over two and a half years on 200 witnesses and internal whistleblowers, centered on People & Baby but alleged complicity from municipalities and senior government officials who looked the other way. It triggered government-wide nursery reviews, and its ripple effect continued to build through the quarter. Within the same period, a Wisconsin television investigation found that an Oak Creek KinderCare location where an 11-month-old had tested positive for cocaine earlier that year had accumulated more than two dozen prior violations, including staff aggression and undocumented injuries. The state suspended the center's license, then revoked it. KinderCare had listed that October.

The largest spike of the period lands in 2025, and it is where two operators' exposure changes character. KinderCare faces a wave of securities fraud lawsuits, consolidated in Gollapalli v. KinderCare, which alleges that SEC registration filings promised "the highest quality care possible" while the Oak Creek violations were accumulating. Once an operator is listed, a safety failure becomes a disclosure failure. In France, an IGAS audit of La Maison Bleue, distinct from the 2023 sector report, documented systemic quality-of-care issues, accounting anomalies, and payroll optimizations designed to maximize public subsidy payments at the expense of staffing ratios. State auditors characterized some findings as potentially criminal, regulators referred the operator to a prosecutor, and the report prompted demands for further audits.

For People & Baby the consequences moved from reputational to structural: the group entered court-supervised accelerated safeguard proceedings, handing majority ownership to creditor fund Alcentra and slating dozens of locations for closure. The sequence runs into 2026 with KinderCare's $33M lawsuit over a child abuse cover-up, prosecutors seeking an investigation into People & Baby, and Babilou sued for negligence over a child's injury.

The signal is the floor, not the peaks. Baseline mention volume rose two to three times over and never returned to its prior level, and that elevated floor separates the five operators into two groups. People & Baby, La Maison Bleue, and KinderCare each triggered an event that radiated outward, and each carries a different kind of exposure: an ownership change, an unresolved regulatory referral, and investor litigation.

Babilou and Les Petits Chaperons Rouges never appear on that timeline, which is the point. Babilou carries scrutiny of its own over micro-crèche operating margins and the strikes in Montauban, but no corporate-level criminal indictment. Les Petits Chaperons Rouges draws enforcement at the site level rather than the group level, through the state-ordered emergency closure and admitted operational "dysfunctions" in National Assembly testimony, while remaining cited for the gap between parent company Grandir's expansion and site-level compliance. Neither has restructured, and both sit above the floor anyway.

Top Subrisks

ESG risk exposure in the for-profit childcare sector concentrates almost entirely in the social pillar, with a minor governance exposure and an absence of environmental risks. This reflects a business model in which labor practices and care quality directly determine commercial and reputational viability.

Case Study: People & Baby

People & Baby is a France-based childcare provider headquartered in Paris, operating approximately 600 crèches and reporting revenue of about USD 119 million.

People & Baby’s ESG exposure is defined above all by repeated child-safety and regulatory-compliance failures, including abuse allegations, a child death, and inspections identifying significant deficiencies, while financial restructuring and sustained labor disputes add pressure to the company’s operating and governance profile.

The mention curve describes a company hit by two distinct crises rather than one continuous controversy. Through 2020 and 2021, the exposure was latent, visible only in local and union-press labor and discrimination litigation reported by outlets such as anti-k.org and rapportsdeforce.fr, none of which were high-authority sources. The company's own peak arrives a year before the sector's, which is the point of the case: People & Baby was the operator whose crisis set the wave that the other four were later caught in.

The first spike came in 2022 as a child-safety crisis, built on the death of an infant in a Lyon crèche and the temporary closure of a Bordeaux facility, and accompanied by government sanction threats and staff testimony on conditions. Coverage receded through 2023, then overtook that peak in 2024 on a crisis of a different character, financial and legal rather than clinical: Victor Castanet's Les Ogres, the Anticor complaint over misappropriated public funds, the opening of a Paris prosecutor's investigation, and the accelerated safeguard procedure. What remains through the first half of 2026 is thinner and still declining, though none of it has been resolved. 

Four cases account for nearly all of People & Baby's exposure: the Castanet, Anticor, and public-funds case, the child-safety case covering the Lyon death and the Bordeaux closure, employee litigation culminating in a Court of Cassation ruling, and the Lille abuse convictions and their sentencing. Spread across 19 sub-risk categories, the same material looks far more diversified than it is. Tags such as Child Labor, Tax Strategy, and Right to Property register because a case touched them once in passing, not because the operator carries exposure there.

The 2026 residue is qualitatively different from a story burning out. What remains is structural rather than incidental: a redundancy plan that removed an entire CGT delegation, a whistleblower retrospective, and two Villejuif nurseries closed. The sector union has shifted its demand accordingly, moving from accountability for individual incidents to an administrative investigation and People & Baby's withdrawal from nursery management altogether. Read alongside the 2025 change of control and the 44 announced closures, the operative residual exposure is loss of public delegations and license to operate, not reputational drag.

Neither crisis is closed. The 2022 safety failures were never structurally resolved, and the 2024 governance case remains before the courts, though counter-signals exist: an ex-director was acquitted on appeal, and one municipality has maintained its contract. The variables to track are the outcome of the fraud investigation, contract renewals with municipalities, and any further union escalation.

The Takeaways:

Across seven years, for-profit childcare has moved from near-invisibility to sustained scrutiny in three markets at once. What surfaced as isolated incidents in individual centers has become a question about the operating model: state inspectors, parliamentary committees, investigative journalists, and prosecutors have converged on the same finding, that margin is held by cutting staffing in a service where staffing is the service. The consequences have stopped being reputational. Operators have lost licenses, entered court-supervised proceedings, changed hands, and closed centers, and in France, the demand has shifted from holding an operator accountable for a given incident to removing it from nursery management altogether. The coverage has thinned since its peak, but nothing in the data suggests the underlying question has been settled.

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.

Below is an approximation of this video’s audio content. Watch the video for a better view of graphs, charts, graphics, images, and quotes the presenter might be referring to in context.

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.