Hello, and welcome to our ongoing series on Generative AI in Finance. I’m Sylvain Forté, CEO and co-founder of SESAMm, and in our first article of the series, we’ll explore how generative AI is reshaping the financial industry. At SESAMm, we’ve been fortunate to be at the forefront of this revolution, witnessing the transformational power of large language models like ChatGPT and its iterations.

Unprecedented Evolution in Generative AI

Let's begin with an overview of the current generative AI landscape. Over the last few years, we've seen an explosion in the capabilities of generative AI, particularly in text processing. From BERT to GPT4, large language models (LLMs) have demonstrated increasingly impressive capabilities. These models, performing at a human level for many tasks, are rapidly evolving, making the past six months feel like an exponential leap in the AI domain.
Generative AI is no longer a speculative idea but rather an early adoption phase of a powerful technology. At SESAMm, we've leveraged our partnerships with OpenAI and other organizations to gain high-level access to these AI models, allowing us to harness this potential and democratize access to intelligence. It’s an exciting shift that, while reshuffling business models and job roles, promises enormous productivity gains and increased overall value. The key, of course, is ensuring that these benefits extend to society as a whole.

The Disruption in Financial Sector

The finance sector, with its vast array of text-based tasks, stands to gain enormously from generative AI. Any repetitive yet intelligence-heavy tasks — think verification, document generation, or client communication — are ripe for automation.
Finance, despite being a highly intelligent sector, often sees that intelligence is misspent on routine tasks. Generative AI can realign this balance, reducing costs, enhancing service quality, and building trust. Whether private equity, asset management, or commercial banking, AI can streamline processes, delivering an efficiency boost that significantly enhances customer satisfaction.
In private equity, the automation possibilities could reshape the sector, bringing it closer to the public markets. In asset management and banking, cost reduction and service enhancement could lead to a dramatic rise in customer satisfaction.

Concrete Use Cases of Generative AI in Finance

So, how does this look in practice? Generative AI can automate numerous finance tasks, including creating reports, verifying information, summarizing news or earnings calls, and even making internal data searchable. Imagine a system that can help asset managers match various types of datasets based on a user query in natural language, thereby making data access and interpretation simpler. This could vastly improve the user experience with business software, reducing effort and time spent. While some applications, like a fully automated financial advisor or AI-led trading and hedging, might present more significant challenges, their potential benefits could revolutionize these sectors.

Overcoming Roadblocks

Of course, every transformation comes with challenges. The key is discerning which use cases are suited for full automation and which require human oversight. Data privacy concerns will also influence decisions about whether to use proprietary or open-source models.
There will inevitably be resistance to change within organizations, but the 'Google test' can help navigate data privacy issues: if an employee would conduct that search or share that data on Google, it's likely safe to share with a proprietary Generative AI solution.

Generative AI and Risk Mitigation

Risk mitigation strategies can greatly benefit from generative AI. From detecting and preventing fraud to managing market risks, generative AI can verify identities, cross-reference databases, and analyze vast amounts of data. For instance, at SESAMm, we're developing an ESG controversy detection solution that can be an invaluable tool for risk mitigation.

Improving Investment Decision-Making

Generative AI’s ability to process and analyze massive amounts of data accurately and quickly makes it a formidable tool for investment decision-making. By identifying patterns, trends, and correlations that humans might miss, generative AI can provide a more comprehensive, data-driven perspective, aiding portfolio optimization, asset allocation, and investment risk management.

Streamlining Operations for Efficiency

Generative AI's efficiency and accuracy promise to transform financial institutions. By automating time-consuming tasks like report generation and client communication, AI can free employees to focus on strategic tasks that require critical thinking.
Imagine being able to ask complex questions to your banking app in natural language and getting immediate, accurate responses. Such high-quality service was unthinkable a few years ago, but with generative AI, it's within our reach.
The future of the financial sector is undeniably tied to the successful implementation of generative AI solutions. The potential is vast, the challenges are surmountable, and the rewards are great. In my view, generative AI is the key to a more efficient, cost-effective, and customer-centric financial sector.

To learn more about SESAMm’s innovative solutions and how we’re pushing the boundaries with generative AI, read the second part of this series here.

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.

Discover our whitepaper highlighting the power of web data on predictive analytics for the financial industry: how alternative data strengthen the market, the challenges of collecting web data and case studies presenting different approaches, such as ESG, showcasing TextReveal features and capacities for investment purposes.

In complement, please find here our Recorded Webinar “Predict financial movements with web data”.

Introduction

In the past, investment management institutions relied mostly on traditional data to gain an edge in investing. Traditional data ranges from SEC filings to earnings reports and pricing information any type of data produced by the company itself. The rise of the digital age, however, has opened up new sources of data for investors beyond the scope of traditional data. The seemingly infinite scope of alternative data includes data produced from credit cards, satellites, social media and perhaps most importantly the web.

With the additional integration of alternative data, investment management institutions and hedge funds in particular that once relied only on traditional data now have an edge in predicting the rise and fall of the markets. As increasing numbers of financial institutions jump on the bandwagon of alternative data, spending on alternative data by trading and asset management firms is set to exceed $7 billion by 2020.^[1]

What was only a few years ago a question of when institutions should start using data has shifted to the question of how they can organize and structure these mostly unstructured datasets. And with 4 billion webpages and 1.2 million terabytes of data on the internet estimated to be generated globally by 2025, there is no shortage of web data to sort through. As increasing numbers of investment management institutions incorporate alternative web data into their predictive algorithms, it will change the face of investment as we know it.

This white paper is intended to be a guide for investment management (IMs) institutions to better understand how alternative web data is quickly becoming an essential component for generating alpha and mitigating investment risk. In addition, it explores different models of web data crawlers and what IMs need to look for as they incorporate alternative web data into their predictive analytics models.

Section 1: Beating the Market with Alternative Web Data

“Your company’s biggest database isn’t your transaction, CRM, ERP or other internal database. Rather it’s the Web itself…Treat the Internet itself as your organization’s largest data source.”
— Gartner

As previously mentioned, alternative data includes any type of data that is beyond the scope of traditional data: satellite imagery, social media data, and web data (which includes news sites, blogs, discussions and forums) along with credit card data. Alternative web data, which falls under the broader category of big data, is typically unstructured and demands a process for structuring it in order to deliver insights.

Access the full whitepaper

At SESAMm, we have always been at the forefront of utilizing artificial intelligence (AI) for Environmental, Social, and Governance (ESG) risk analysis. Our journey began in 2014, leveraging natural language processing (NLP) to analyze vast amounts of data to identify company risks - from public equities to expanding into private assets. Our technology stack, deeply rooted in AI-first principles, has evolved significantly over the years, incorporating deep learning and large language models since their inception.

2023 marked a significant leap in generative AI, breaking data quality and precision barriers. Our ability to attain human-level precision in ESG control detection across dozens of languages is a testament to our commitment to continual technological advancement. We plan to further integrate generative AI into our processes, enhancing data quality and expanding our coverage, especially for smaller firms and infrastructure projects that often go unnoticed in the market.

Enhancing User Interaction with AI: The Future of Client Engagement

A significant focus for SESAMm in 2024 is transforming how clients interact with our SaaS platform. Last year, we introduced a prototype of our generative AI chatbot, which marked the beginning of a new era in user interaction. Our goal is to utilize generative AI not just for data improvement but to enhance the overall user experience. This includes making data more accessible and addressing challenges like the lack of unique identifiers in the private space.

Accelerating Innovation and Development with AI

Our team of 60 engineers and researchers is the driving force behind our rapid development and innovation. The integration of large language models has enabled us to deliver features more quickly and efficiently. With a robust infrastructure and an agile AI team, we're pushing the boundaries of what's achievable with AI, outpacing traditional human analyst capabilities. This agility in innovation is crucial for our continued leadership in the market.

The Future of AI Technologies in SESAMm's Roadmap

We keep a close eye on the latest AI advancements, from new open-source libraries to cutting-edge commercial models. Our team is deeply engaged in fine-tuning models for specific applications, especially in tracking ESG events and uncovering insights about smaller, lesser-known companies. This approach reflects our culture – an AI-first company specializing in the financial and ESG space, always eager to incorporate more technology and innovate.

Cementing Leadership in AI-Powered ESG Analysis

Our vision extends beyond 2024, aiming to be the premier global player in ESG controversy and risk analysis. With regulations evolving globally, we anticipate a significant expansion in our market. Our focus remains on delivering unparalleled reputational insights, especially in the investment world, but also rapidly expanding into supply chain analysis and client monitoring. We're not just keeping pace with the market but setting the standard for AI-powered ESG analysis.

The Expanding Global ESG Landscape: Opportunities and Challenges

As regulations intensify worldwide, including in polarized markets like the US and Asia, we see a growing demand for ESG analysis. This global shift presents both opportunities and challenges. Our strategy includes further integrating our solutions into various ecosystems, such as ESG reporting tools, portfolio management systems, and CRMs. Through strategic partnerships, we aim to position SESAMm as an integral part of the global ESG analysis framework.

Walking the Talk: SESAMm's Commitment to Sustainability

In 2024, SESAMm is not just about leading in technology; we're deeply committed to practicing what we preach regarding sustainability. We have a robust ESG Manifesto and a series of actions aligned with environmental, social, and governance principles. Recognizing our relatively limited carbon footprint as a tech company, we focus on making impactful choices and fostering a culture of awareness and change within our team.

We've implemented programs for environmental awareness, like our Climate Risk training, conducted by certified employees. Our efforts in governance are highlighted by the appointment of our first independent board member, Stephane Beson, signifying our dedication to having diverse external perspectives guiding our company.

Regarding environmental footprint, we prioritize partnering with providers that use clean energy in their data centers. This conscious decision-making extends to selecting partners who can offset their carbon emissions, reflecting our commitment to sustainability.

Remote Work and Sustainability: A Dual Focus

Our approach to remote work has always been progressive. We see it as not just a productivity enhancer but also as a key sustainability strategy. Given our global presence, with teams in France, New York, Tunisia, and London, remote work is essential. It brings our team closer, transcends cultural barriers, and reduces our carbon footprint by significantly cutting down on travel. This strategy aligns with our dedication to work-life balance, recognizing the importance of flexibility for our employees.

Targeting the Right Market with Tailored Services

2024 is a year of strategic focus for SESAMm, especially in terms of our target market. We're seeing a growing trend among banks to aggregate ESG controversy data. Our unique capability to provide comprehensive coverage, encompassing mixed assets portfolios, positions us as a key player for these institutions.

We continue strengthening our presence in private equity and expanding our reach into the banking sector, private debt, and infrastructure funds. Our dedicated corporate business practice is another area of expansion, helping European companies monitor ESG controversies. We also focus on sustainability and ESG teams, procurement teams, and third-party risk teams, ensuring a broad yet targeted market approach.

Upholding Data Security and Privacy

Data security and privacy are paramount, especially given the increasing sophistication of cyber threats. Our co-founder and CTO brings invaluable expertise in cybersecurity. We conduct annual audits, have robust systems to monitor and preempt attacks, and continuously train our teams to be vigilant. While we don't deal with personal data, we focus on protecting critical systems for our clients, ensuring that we maintain the highest standards in data security.

Building a Team for the Future

Looking ahead, our confidence in 2024 stems from our team's exceptional capabilities. We've implemented agile processes and onboarded talented individuals across all levels. Our team's passion and dedication are key drivers in adapting to market changes and delivering high-quality services. It's not just about where SESAMm is now but how our team will continue to excel and innovate in the future.

A Vision of Innovation and Responsibility

As we move into 2024, SESAMm stands at the forefront of AI-powered ESG analysis, not just through technological innovation but also through a steadfast commitment to sustainability and security. Our focus on the right markets, combined with a forward-thinking approach to remote work and data protection, positions us to meet the evolving needs of our clients.

Join us at SESAMm as we navigate the future of ESG analysis, leveraging our expertise to foster a sustainable, secure, and innovative business environment. Explore SESAMm's cutting-edge solutions and be part of a future where technology meets responsibility.

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.