Geneva generates massive data. Few companies know what to do with it.
Geneva hosts over 100 commodity trading houses. Trafigura, Gunvor, Vitol, Mercuria: these companies handle colossal data flows (spot prices, volumes, logistics, counterparty risk). Yet a good chunk of the analysis still happens in Excel workbooks shared by email between front office and operations. That's reporting, not analysis. Nobody digs into the correlations between shipping delays and actual margins per transport corridor.
In private banking and wealth management, same story. Geneva manages roughly 25% of global offshore assets. Pictet, Lombard Odier, Union Bancaire Privee: client data exists, transaction histories too. But when a relationship manager wants to understand which client profile churns after 18 months, they rely on gut feeling. Not a statistical segmentation.
International organizations (UN, WHO, WTO, Red Cross, CERN) produce enormous data volumes. Some teams have data scientists. Most departments don't, and run on interns copying and pasting between systems.
Then there's Geneva's SME fabric: watchmaking subcontractors, mid-size trading firms, consulting boutiques, biotech startups in the Geneva Health Valley. They can't afford a full-time data analyst (Geneva salaries don't help). They have data, business questions, and nobody connecting the two.
What I do for businesses in Geneva
Exploratory analysis: finding what you weren't looking for
You have a business question? I take your raw data and dig. Principal Component Analysis (PCA) to reveal hidden structures in your trading or portfolio data. Clustering to segment your wealth management clients by actual behavior, not by assets under management. Correlation circles to understand which variables move together in your commodity data. For a trading house, that might reveal seasonal margin patterns per logistics route. For a private bank, client segments at risk of leaving that the relationship manager hadn't flagged. This isn't reporting. It's exploration.
Ad-hoc analysis: concrete answers to your questions
"Why do our cross-border clients have a 2x higher churn rate?" "Which trading corridors generate the most net margin after logistics costs?" "Is our pricing consistent across the CHF and EUR markets?" Every business question has an answer sitting in your data. I build the analysis end to end: extraction, cleaning, statistical exploration, results visualization. You walk away with a clear deliverable and actionable recommendations. Not an 80-page report that nobody reads.
Opportunity detection: making your data work for growth
Most Geneva companies use their data to look backward. How many transactions, what trading volume, what portfolio yield. I do the opposite: I use your data to look forward. Which client segments are underexploited in the Geneva-Lausanne-Lyon corridor? Which financial products could be bundled based on actual buying behavior? Which correlations between your sales efforts and conversions have never been measured? That's the kind of analysis that turns a data cost into an investment.
How it works
Tech stack
Frequently asked questions
Video calls, shared reports, async updates. I've worked this way for years with clients in Switzerland and France. For kickoff or sensitive phases, I come on-site. Geneva is a direct flight. And let's be honest: the trading house on Rue du Rhone doesn't need me sitting in their office. They need their analysis delivered on time, with the right conclusions.
Depends on the complexity of the question and the data volume. A focused ad-hoc analysis is a few days of work. A full dataset exploration with segmentation and modeling, more like one to two weeks. I bill in euros, which represents a significant cost advantage compared to local consultants billing in CHF. We scope the budget together on the first call.
The nLPD (new Federal Act on Data Protection) is stricter than GDPR on several points, including personal liability for company leaders. I work with private APIs and secure environments. Your data never passes through third-party tools without your explicit consent. We define the processing rules together before starting, in compliance with your Swiss legal obligations.
Deloitte and McKinsey have Geneva offices and do excellent work on multi-million projects. But for a targeted data analysis, their model doesn't fit: you pay a partner to sell, a manager to supervise, and a junior to do the work. With me, the same person scopes, analyzes, and presents. Faster, cheaper, and you talk directly to the person who touches the data.
How I work
Three packages, from quick validation to full analysis. Full details on the main page.