David Platt Joins SESAMm’s Advisory Board to Support Strategic Growth
03/31/2026
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5 mins read
SESAMm is pleased to announce the appointment of David Platt to its Advisory Board. David has spent his career at the intersection of M&A, corporate strategy, and risk intelligence - most recently as Senior Vice President, Chief Strategy Officer at Moody’s Corporation, where he contributed to the diversification of one of the world's leading financial data companies.
During his twelve years at Moody’s, David helped architect the firm’s diversification into data, analytics, and technology-driven risk assessment. He oversaw more than 75 transactions valued at $9 billion, including landmark acquisitions in climate risk, cybersecurity, and private company data. Before Moody’s, he held senior M&A roles at Deutsche Bank, Bank of America, Citigroup, and Credit Suisse First Boston, advising on complex transactions and corporate strategy for global clients.
“Over the course of my career, I’ve focused on helping organizations scale by expanding into new markets, strengthening their strategic foundations, and building platforms that help institutions better measure, manage, and understand risk,” said David Platt. "SESAMm has built an impressive platform at the intersection of AI and risk intelligence, and I’m excited to support the team as they shape their strategy and scale the business globally.”
David’s appointment comes as SESAMm continues to scale its AI-powered risk intelligence platform and expand its global presence. His experience driving profitable and strategic growth initiatives and scaling data and analytics platforms will help guide the company’s strategic direction.
"David has sat on both sides of the table, as a buyer of data and analytics capabilities, and as a trusted advisor to some of the world's largest financial institutions," said Sylvain Forté, CEO and Co-Founder of SESAMm. "That perspective will be invaluable as we shape SESAMm’s strategic direction and execute our next phase of growth."
David is a CFA charterholder and has served on the boards of BitSight Technologies and ICRA, an Indian credit rating agency. He holds an MBA from the University of Chicago Booth School of Business.
A few months ago, Sylvain Forté, CEO of SESAMm, and Julia Haake, Head of ESG Ratings Agency at Ethifinance, sat down and dove deeper into how AI and new regulatory standards are reshaping the future of ESG ratings for rating providers. Download the ebook and have an insider’s view into their thoughts on ESG regulations for rating agencies, the challenges they face, and the possible solutions.
Raiffeisen Bank International’s (RBI) Advanced Analytics and AI Tribe is crucial to the bank’s operations. The team delivers, maintains, and operates AA&AI (digital) solutions allowing Retail and Whole-Sale Banking to increase revenues (and to fulfill their role as the first line of defense). They are pioneers in using cloud-based infrastructure. With more than 50 data scientists, data engineers, machine learning engineers, and cloud engineers, they play a crucial role in transforming RBI into a data-driven company.
The AA&AI tribe at RBI recognized a significant opportunity in SESAMm, a leading AI-powered analytics, and data solutions provider. SESAMm’s solutions offer access to an extensive range of web-based information, which is otherwise challenging to obtain. This data is critical for RBI’s operations, enabling the bank to stay ahead of the curve regarding market trends, consumer preferences, and industry insights.
Key successes for RBI after working with SESAMm include:
Generated analytics on clients to specifically monitor companies exposed to the Ukraine war, enabling the bank to proactively identify potential risks and minimize its exposure to geopolitical events.
Integrated specific languages within RBI’s core market, including Russian, Romanian, Slovak, Czech, and Polish, improving the bank’s ability to analyze and understand regional data.
Integrated SESAMm’s data with RBI’s internal visualization dashboard, allowing the bank to leverage the insights generated by SESAMm’s AI-powered analytics to improve decision-making and drive business growth.
Why RBI chose SESAMm: Coverage, early warning signals, and customizability
Raiffeisen Bank International decided to partner with SESAMm due to several key factors:
SESAMm’s excellent coverage, including that of the CEE market, is a crucial need for RBI. This coverage enables RBI to obtain critical data and insights that help inform the bank’s decision-making process.
SESAMm’s product, TextReveal API, provides data and the underlying natural language processing (NLP) capabilities, enabling RBI to analyze data at a deeper level. This capability is significant for the bank’s operations in the CEE region, where multiple languages are spoken.
The relationship built between SESAMm and the RBI team during the proofs-of-concept (PoCs) brought confidence in the quality of SESAMm’s products and the potential value they could bring to the bank.
Overall, the combination of SESAMm’s excellent coverage of the CEE market, NLP capabilities, and positive relationship with the RBI team made them the ideal partner for the bank’s data and analytics needs.
The Collaboration
After SESAMm and Raiffeisen Bank International agreed to collaborate, SESAMm began working with David Eschwé, the Head of Group Advanced Analytics at RBI. SESAMm onboarded the RBI team on TextReveal API and opened dashboards and API access to RBI. This access allowed RBI to generate historical datasets. SESAMm worked with the RBI team to define the roadmap and key milestones, particularly for integrating Central and Eastern European languages. This enabled RBI to access critical information efficiently that could help their internal teams generate early warning signals to better mitigate potential risks that can harm the bank. By working closely together, SESAMm and RBI achieved key milestones, demonstrating the value of the collaboration to both parties.
The results
By leveraging SESAMm’s solutions, RBI was able to monitor more than 1,000 clients, generating analytics on companies exposed to the Ukraine war and creating early warning signals to mitigate better potential risks that could harm the bank. Additionally, SESAMm’s solutions provide substantial yearly savings in raw-data-related costs, allowing RBI to allocate resources more efficiently and effectively. Through this collaboration, SESAMm helped RBI achieve more significant insights into their data, improve their risk management processes, and achieve considerable cost savings.
"Our partnership has been a great success. Thanks to SESAMm, we can now answer business-relevant questions within days, including those related to the critical topic of ESG” —David Eschwé, Head of Group Advanced Analytics in RBI.
About Raiffeisen Bank International
Raiffeisen Bank International AG (RBI) is a leading Austrian banking group that operates across Central and Eastern Europe. It is headquartered in Vienna, Austria. RBI offers a wide range of banking and financial services, including corporate and investment banking, retail banking, leasing, and asset management. With a focus on sustainability and social responsibility, RBI is committed to providing high-quality banking services while supporting the communities in which it operates.
Reach out to SESAMm
Whether you’re a financial institution, an asset manager, or a data-driven company looking to gain insights into your data, SESAMm’s technology and team of experts can help you achieve your goals.
SESAMm has a large data lake of more than 20 billion articles (growing by 5–10 million a day) and 14 years of data in 100 languages. But its size alone is not what makes it good; it’s a refined process to find the exact data you want that makes it better.
Here’s an example to help explain the point. We’re sometimes asked for help researching data to forecast and monitor the commodities market, even by large companies with their own commodities desk of traders and quant researchers. Why would they seek help from outside their firm?
Simply put, traders want an edge. They want information advantages that others are likely to miss, so they look to alternative data from various sources, anything that adds value and is from different angles. And, as it turns out, commodities are a more challenging segment to analyze when it comes to alternative text data. Unlike for companies, commodity texts are scarcer and need more domain knowledge to unravel their implications. A simple sentiment analysis doesn’t bring enough relevant information.
For a more in-depth view, join us as we discuss NLP-derived alternative data, its benefits, challenges for researchers, and why bigger isn’t always better in the world of data.
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