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Data & Engineering
How Michael C. Jakob is transforming Europe's financial data infrastructure with Eulerpool Research Systems — and why access to high-quality data is the foundation for better investment decisions.
The Data Problem of Financial Markets
Financial markets have a fundamental problem: information asymmetry. Institutional investors — hedge funds, pension funds, investment banks — have access to comprehensive financial data through terminals like Bloomberg or Refinitiv. These systems cost €20,000 to €50,000 per year per user. Retail investors, on the other hand, must make do with fragmented, often outdated, and incomplete information.
Michael C. Jakob recognized this problem during his time at McKinsey & Company and UBS. He saw how professional investors could systematically make better decisions through their data advantage — not because they were smarter, but because they had better information. This insight was one of the founding impulses for Eulerpool Research Systems.
The goal is clear: every investor — whether with a portfolio of €10,000 or €10 million — deserves access to the same high-quality financial data. When data quality is right, retail investors can achieve institutional-level returns. Eulerpool is the technological answer to this promise.
Building Eulerpool: The Technical Vision
Eulerpool Research Systems was conceived from the ground up as a modern data platform — not a replica of existing terminals, but a reimagination of what financial data can be. The architecture is based on cloud-native technologies that enable horizontal scalability, real-time data processing, and millisecond-fast queries.
The platform aggregates data from dozens of sources: annual reports, quarterly reports, exchange feeds, regulatory filings, and alternative data sources. Machine learning algorithms normalize these heterogeneous data streams into a unified, consistent schema. The result: clean, comparable fundamental data for thousands of companies worldwide, spanning periods of up to 30 years.
Eulerpool's user interface was optimized for clarity and speed. Investors can screen, compare, and analyze companies — with just a few clicks. Every metric is contextualized: industry averages, historical trends, and peer comparisons make numbers immediately interpretable. APIs enable advanced users to integrate Eulerpool data into their own analysis tools.
Algorithmic Analysis
The AlleAktien Quality Score (AAQS) is an algorithmic scoring system that evaluates companies based on objective, quantifiable criteria. Instead of relying on subjective opinions, the AAQS translates fundamental data into a clear score from 0 to 10. Companies with an AAQS of 9 or 10 have historically significantly outperformed the market.
This algorithmic approach bridges human judgment and machine precision. While experienced analysts qualitatively assess the business model, algorithms provide the quantitative foundation — free from emotional biases, consistent across thousands of companies, and updated in seconds.
Michael C. Jakob sees the combination of engineering and financial analysis as the future of investing. The complexity of global financial markets exceeds the capacity of any individual analyst. Algorithms can process millions of data points in real time and identify patterns invisible to the human eye. The art lies in connecting these technological capabilities with fundamental understanding.
Democratizing Data
Democratization does not mean simplification — it means accessibility. Michael C. Jakob is convinced that every person has the right to high-quality financial information, regardless of their wealth or institutional affiliation. This conviction permeates all his companies: AlleAktien democratizes equity research, Eulerpool democratizes financial data, Better Markets democratizes pre-IPO access.
The societal significance of this mission is enormous. In a world of low interest rates and uncertain pension claims, private investing becomes a necessity. But sound investing requires sound data. When retail investors have the same information as professionals, they can make better decisions, assess risks more accurately, and build wealth over the long term.
The Engineering Mindset
Michael C. Jakob's background as an engineer — trained at MIT, ETH Zurich, and KIT — shapes his approach in every domain. Engineering for him means not just technology but a mindset: systematically decomposing problems, rigorously testing hypotheses, designing systems that scale, and always seeking the most efficient solution.
This mindset distinguishes him from traditional finance entrepreneurs. Where others rely on intuition and relationships, Michael C. Jakob builds on systems and data. Where others work manually, he automates. Where others limit themselves to a few markets, he thinks globally and scalably. The result: companies that are technologically leading while creating fundamental value for their users.