SESAMm has been prominently featured in the Datos Insights Commercial Banking & Payments Fintech Spotlight Report for Q2 of 2024. This recognition highlights SESAMm’s innovative capabilities and its significant impact on the financial industry, particularly within private equity and asset management.

SESAMm's Capabilities and Impact

SESAMm's AI-driven platform excels in processing vast amounts of data, offering deep insights, and enhancing decision-making for financial institutions and corporations. With a proprietary data lake comprising over 25 billion articles in more than 100 languages, SESAMm provides comprehensive ESG data that supports detailed risk assessments, controversy monitoring, and positive impact identification. This extensive database is continuously updated, adding approximately 10 million new articles daily, ensuring users have access to the most current information.

Our services are available as a SaaS or API plug-in, allowing banks and other financial institutions to leverage hyper-local data. This feature enables clients to understand the nuances of ESG criteria impacts, both positive and negative, on public and private companies. The platform’s customizable filters and alert systems, based on 90 ESG risk categories and the United Nations Sustainable Development Goals (SDGs), offer an unparalleled level of detail and usability.

SESAMm’s primary clientele includes private equity firms, asset managers, corporates, and financial institutions, including some of the largest European banks. By partnering with these entities, SESAMm helps expedite due diligence processes, investment monitoring, and ESG risk assessments, addressing a critical need for timely and accurate data in these sectors.

About the Datos Insights Fintech Spotlight

The Datos Insights Fintech Spotlight is a quarterly report that highlights leading fintech companies making significant changes in the industry. The report focuses on innovations and solutions that address current market challenges, providing financial institutions with valuable insights into emerging technologies and best practices.

Why SESAMm Stood Out

SESAMm’s selection for this spotlight recognizes our robust data processing capabilities, comprehensive ESG insights, and tangible value to its clients. Our ability to streamline complex research processes, support thorough due diligence, and offer real-time monitoring makes it a valuable tool for financial professionals. SESAMm continues to lead the way in leveraging AI to navigate the evolving landscape of ESG and sustainability, solidifying its position as a key player in the fintech space.‍

Access the report here.

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.

Identifying environmental, social, and governance (ESG) controversies is a complex challenge. The large amount of data that is added to the web daily makes it difficult to analyze, leaving important insights hidden among irrelevant information. Traditional risk identification methods struggle with this, making it difficult to uncover critical issues that could impact investments.

This article explores the intricacies of ESG data trends. As businesses worldwide strive to adopt more sustainable and ethical practices, the importance of ESG metrics has risen to the forefront of strategic planning and public discourse.

Identifying Controversies with AI

Traditional controversy detection methods often need help uncovering hidden risks buried within unstructured sources like social media, local news, and niche industry reports. This section explores the advantages of using AI tools—such as natural language processing and machine learning—to detect these risks more accurately and efficiently. By leveraging AI, firms can gain deeper insights and respond proactively to emerging ESG issues, ensuring more robust risk management and informed investment decisions.

Key Challenges in Identifying ESG Controversies

In the finance world, especially when dealing with small companies, sometimes private, identifying ESG controversies presents significant challenges. These companies often lack extensive public records, and the data that is available can be sparse, fragmented, or hidden within vast amounts of irrelevant information. Traditional methods of risk identification struggle to navigate this sea of digital noise, making it difficult for private equity firms to uncover critical issues that could impact their investments.

One of the primary hurdles is the lack of valuable, structured data on smaller firms. Unlike large corporations, which are often required to disclose detailed financial and operational information, small private companies might operate with minimal public visibility. This opacity complicates the identification of potential ESG risks, as relevant data is often buried in unstructured sources like social media, local news, or niche industry reports. The challenge is not just about finding information but also about extracting meaningful insights from a diverse array of sources that may not adhere to standardized reporting practices.

Additionally, the diversity in language and terminology used by smaller firms further complicates the identification of ESG controversies. Risks are often discussed in context-specific ways, using industry jargon or localized expressions that do not easily translate into a standard risk assessment framework. This linguistic variation can lead to misunderstandings or even the complete overlooking of critical ESG issues. Therefore, private equity firms require advanced tools capable of interpreting and standardizing this information to ensure comprehensive risk identification.

Artificial Intelligence vs. Traditional Methods

Artificial Intelligence (AI) has emerged as a game-changing tool for identifying ESG controversies, offering significant advantages over traditional methods. While conventional approaches rely heavily on structured data from formal reports and disclosures, AI technologies, such as natural language processing (NLP) and machine learning, can analyze vast amounts of unstructured data from diverse sources. This capability is particularly crucial for private equity firms focused on small companies, where relevant information may be scattered across social media posts, obscure local news articles, and other non-traditional outlets.

Traditional methods often fall short in dealing with the unstructured and fragmented nature of data related to smaller firms. These methods might miss emerging controversies discussed informally in niche blogs or industry-specific forums. In contrast, AI-powered tools can continuously monitor these sources in real time, identifying potential ESG risks before they escalate. This proactive approach allows firms to address issues early, providing a more comprehensive and nuanced understanding of the risks associated with their investments.

Moreover, AI's ability to process and analyze diverse languages and terminology offers a significant edge. By decoding industry-specific jargon and translating localized expressions into a standardized risk framework, AI helps private equity firms overcome the linguistic barriers that traditional methods struggle with. This capability ensures that no critical ESG controversy is overlooked due to language differences, thereby enhancing the accuracy and effectiveness of risk assessments.

To sum it up, while traditional methods have their place, AI technologies provide a more robust, dynamic, and precise approach to identifying ESG controversies. By leveraging AI, private equity firms can better navigate the complexities of data sourcing, interpretation, and risk management, ultimately leading to more secure and informed investment decisions.

Streamlining ESG Controversy Detection with AI

Detecting ESG controversies with AI involves several crucial steps, each contributing to the precise identification of potential risks. The attached diagram illustrates a generalized AI-driven approach to detecting ESG controversies.

Step 1: Data Collection

The first step in this AI process is collecting vast amounts of web-based information to create a comprehensive data lake. This data lake acts as a repository, storing raw data in its original format. AI systems thrive on large datasets to enhance accuracy, and the data lake ensures that this requirement is met by allowing real-time data ingestion. By preserving historical information, the system can perform trend analyses that are crucial for identifying emerging controversies.

Step 2: Organizing & Cleaning the Data

Once collected, the data undergoes an essential organization and cleaning process. This step involves standardizing and categorizing the data to make it more accessible for analysis. By filtering out irrelevant information and tagging essential data points, the system can quickly and efficiently process large datasets. This organization allows for faster analysis and ensures that only the most relevant information is considered, eliminating the noise that can obscure critical insights.

Step 3: Connecting the Dots

With the data organized, the AI system creates a Knowledge Graph (KG) that maps the relationships between key entities, topics, and themes. This step is crucial for understanding how different companies, products, and brands are interconnected. The Knowledge Graph is continuously updated to reflect new data, ensuring that the system remains accurate and relevant in its analysis.

Step 4: Adding Contextual Understanding

The AI system then moves on to interpret the text, employing various techniques such as Named Entity Recognition (NER) and lemmatization. These tools help the system identify and classify key elements within the data, allowing it to grasp the context and main points of the information. This step is vital for accurately understanding the specific topics and issues related to each company, enabling the system to group related articles and monitor the evolution of controversies.

Step 5: Analyzing with Algorithms

In this step, the AI applies sophisticated algorithms to the organized and contextualized data. These algorithms focus on uncovering insights such as sentiment analysis, ESG controversies, and impacts of Sustainable Development Goals (SDGs). The system continuously refines these algorithms to maintain high levels of accuracy and performance, ensuring that the analysis remains relevant as new data becomes available.

Step 6: Turning Analysis into Actionable Insights

Finally, the AI system transforms the analysis into actionable insights. By delivering these insights in a fast and easy-to-understand format, the system empowers users to make informed decisions quickly. For example, a controversy intensity score might be used to prioritize which issues require immediate attention, allowing users to focus on the most significant risks in their portfolios.

This AI-driven process, depicted in the attached diagram, showcases the streamlined approach to detecting ESG controversies, providing private equity firms with the tools they need to manage risks effectively and maintain a competitive edge in the market.
For more detailed information on how SESAMm identifies insights with AI, please efer to this document.

Conclusion

To sum up, identifying ESG controversies, particularly in smaller, less visible companies, presents significant challenges for traditional risk assessment methods. However, integrating artificial intelligence offers a transformative solution. AI tools can effectively analyze vast amounts of unstructured data, revealing hidden risks and enabling informed investment decisions. As the demand for sustainable and ethical practices grows, leveraging AI will enhance risk management and foster responsible investment approaches, allowing firms to navigate the complexities of ESG data more effectively.

‍
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.

The modern world is in a peculiar place right now. We’ve got the technology and resources to improve our planet, but we often don’t know how to use them despite our best intentions. Or, at the very least, we don’t know where to put our efforts.
Consequently, some investors are looking into Sustainable Development Goals (SDGs). Not only do they want their investments to earn more, but they also want them to do good. If you’re also interested in doing good with your investments, it’s essential to understand the SDGs and their meaning for your portfolio.
In this article, we’ll break down the SDG basics, SDG scores, their relevance to investing, and how SESAMm can help you get and read SDG metrics. But first, a quick review of SDGs.

What SDG means

SDGs, or Sustainable Development Goals, are a set of 17 goals that the United Nations set in 2015 to be achieved by the year 2030, a framework that “provides a shared blueprint for peace and prosperity for people and the planet, now and into the future.” The global goals and the 2030 Agenda for Sustainable Development cover issues such as human rights, poverty, health, education, gender equality, and environmental sustainability, and they were designed to be universal across countries and continents worldwide. Here are the 17 UN Sustainable Development Goals:

• SDG 1: No Poverty: Striving to end poverty in all its forms everywhere. This goal underscores the importance of equitable resource distribution and access to basic needs.

• SDG 2: Zero Hunger: Aiming to end hunger, achieve food security, improve nutrition, and promote sustainable agriculture, thereby ensuring that everyone, everywhere, has enough quality food to lead a healthy life.

• SDG 3: Good Health and Well-being: It emphasizes the need for universal healthcare access, including reproductive, maternal, and child healthcare, and combats health threats by supporting research and development of vaccines and medicines.

• SDG 4: Quality Education: Envisioning inclusive and equitable quality education and lifelong learning opportunities for all, this goal recognizes education as the foundation of empowerment and prosperity.

• SDG 5: Gender Equality: Achieving gender equality and empowering all women and girls to participate fully in societal, economic, and political spheres

• SDG 6: Clean Water and Sanitation: This goal aims to ensure the availability and sustainable management of water and sanitation for all, recognizing the essential role of water resources in sustaining life and ecosystems.

• SDG 7: Affordable and Clean Energy: Promoting access to affordable, reliable, sustainable, and modern energy for all; this goal underscores the critical nature of energy in achieving other SDGs and the transition towards renewable energy sources to combat climate change.

• SDG 8: Decent Work and Economic Growth: It focuses on promoting sustained, inclusive economic growth, full and productive employment, and decent work for all, highlighting the role of the private sector in initiating impactful initiatives.

• SDG 9: Industry, Innovation, and Infrastructure: Aiming to build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation, this goal recognizes the importance of a robust infrastructure and an innovative ecosystem as drivers of economic growth and development.

• SDG 10: Reduced Inequalities: This goal seeks to reduce inequality within and among countries, focusing on policies designed to achieve greater equity and involve stakeholders from all sectors of society in decision-making processes.

• SDG 11: Sustainable Cities and Communities: It aims to make cities and human settlements inclusive, safe, resilient, and sustainable, emphasizing the need for green public spaces, improved urban planning, and sustainable construction practices.

• SDG 12: Responsible Consumption and Production: Focusing on promoting resource and energy efficiency, sustainable infrastructure, and providing access to a better quality of life for all, this goal underscores the importance of adopting sustainable practices and reducing waste.

• SDG 13: Climate Action: Taking urgent action to combat climate change and its impacts, this goal underscores the necessity for countries, stakeholders, and the private sector to collaborate in reducing emissions and enhancing renewable energy usage.

• SDG 14: Life Below Water: Aimed at conserving and sustainably using the oceans, seas, and marine resources for sustainable development, this goal addresses the critical importance of our aquatic ecosystems.

• SDG 15: Life on Land: Protecting, restoring, and promoting sustainable use of terrestrial ecosystems, sustainably managing forests, combating desertification, halting and reversing land degradation, and halting biodiversity loss.

• SDG 16: Peace, Justice, and Strong Institutions: Promoting peaceful and inclusive societies for sustainable development, providing access to justice for all, and building effective, accountable, and inclusive institutions at all levels.

• SDG 17: Partnerships for the Goals: This goal recognizes the importance of revitalizing the global partnership for sustainable development and the role of strong partnerships in achieving the SDGs, involving governments, the private sector, civil society, and others.

What are SDG scores?

Each Sustainable Development Goal has specific targets or indicators that help measure progress toward achieving those targets over time. SDG scores are numerical values given to each entity (country, company, person, etc.) based on their performance in meeting specific targets or indicators for each particular goal. Incorporating these evaluations into the decision-making process is crucial for stakeholders across various sectors, including the private sector, healthcare, financial services, and more. These stakeholders can leverage insights from SDG scores to prioritize initiatives that address critical issues like climate change, emissions reduction, and ecosystem preservation.

How do SDGs relate to ESG?

The environmental, social, and governance (ESG) framework is a tool to achieve and comply with the SDG goals. From a company’s perspective, ESG and SDG frameworks emphasize the importance of measuring and reporting progress. Companies incorporating ESG criteria into their operations often report on their sustainability performance, which can directly show their contribution towards achieving specific SDGs. For investors, ESG metrics provide a tangible way to evaluate companies' potential risks and opportunities related to sustainability, which can also align with the broader objectives of the SDGs.

The SDGs primarily focus on global challenges such as poverty, inequality, climate change, and environmental degradation, which represent the environmental and social pillars of ESG.

Within the same principles, several of these goals directly relate to the governance pillar of ESG. On the one hand, goal 16 aims to reduce corruption and bribery, develop effective and transparent institutions, and ensure inclusive and representative decision-making. On the other hand, goal 17 strives to enhance international cooperation, encourage effective public, public-private, and civil society partnerships, and ensure that policies are coherent and integrated, all of which are governance-related issues.

While the SDGs might not explicitly label these aspects as 'governance' in the way the ESG framework and regulatory landscapes do, the inclusion of these goals demonstrates a clear recognition of the importance of governance in achieving sustainable development.
SDGs and ESG also have different purposes. ESG measures companies’ environmental, social, and governance performance risks and initiatives, while SDGs evaluate any entity’s performance in reaching its goals. Put another way, SDGs represent the goals, while ESG concerns methodology and processes.

Learn more: “Gain Insights From Financial and ESG Data Using AI: A Comprehensive Guide.”

Why are SDGs important to investors?

At the company level, SDGs help align corporate strategy with society’s needs. Because the UN designed SDGs to be measurable, countries, companies, and people can hold themselves accountable for progress toward achieving them. And because the goals are measurable, we can score a company’s efforts, giving you an indicator to invest responsibly by aligning your portfolios with SDGs.

According to a publication by McKinsey & Company, sustainable investing appears to have a positive effect, if any, on returns. In other words, investors care about SDGs not only because they benefit society but also because they measurably support better investment decisions. For example, by incorporating SDGs into company assessments, investors can identify well-run businesses that are better positioned to benefit from the positive effects of improved social and economic conditions. SDGs also allow investors to make better-informed decisions within a defined investment time horizon by focusing on a company’s business exposure toward them. Investors can thus better measure and track a company’s opportunity exposure as a result of its achievement of the SDGs.

How to measure an entity’s SDG score

There are tools available to measure progress toward each goal—and those tools will play an essential role in helping investors decide which entities they want to invest in and which ones they don’t want to support. For example, SESAMm’s platform, TextReveal®, can analyze web data to generate SDG scores for virtually any entity in our data lake.

How SESAMm provides SDG scores

SESAMm provides SDG scores through its platform, TextReveal, a platform that allows investors to gain insights into companies, people, or topics. Specifically, we use artificial intelligence (AI) to track entities’ contributions toward SDGs, including public and private companies.

We track the 17 Sustainable Development Goals and the 169 underlying targets to detect negative news and positive events, using a similar algorithm we use for ESG alerts and gathering alternative data. Each UN SDG item displays a score from 0 to 5 to show the intensity of the company’s positive impact. Then, we translate the information into multiple languages.

We queried the Norwegian carbon capture company, Aker Carbon Capture, using our SDG positive impact dashboard over the past three years. As you might notice, Aker contributes to the goals associated with Partnerships, Climate Action, Clean Energy, and Sustainability. Maybe they could do more regarding Decent Work and Economic Growth, and Responsible Consumption and Production, but overall, the company’s online data shows a positive contribution.

See how SESAMm can help you with your SDG research

SESAMm is the leading provider of AI solutions and analytics for investment firms and corporations.

Our AI and NLP platform, TextReveal:

• Analyzes text in billions of web-based articles and messages
• Generates investment insights, ESG and SDG analysis used in systematic trading, fundamental research, risk management, and sustainability analysis
• Enables a more quantitative approach to leveraging the value of web data that’s less prone to human bias
• Addresses a growing need in public and private investment sectors for robust, timely, and granular sentiment and SDG data

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.