Philipp D. Dubach is a strategy consultant and independent quantitative finance researcher based in London and Zurich. His expertise covers banking strategy, AI economics and machine learning.
His consulting work covers digital transformation and AI implementation for financial institutions and industrial businesses. This includes operating models, governance and machine learning prototypes. He previously worked as a relationship manager for high-net-worth clients.
He holds an MSc in Finance from Imperial College London and a BSc in Banking and Finance. He also completed executive education at INSEAD.
In the media
Matthew Leising quoted Dubach’s analysis of AI revenue and capital spending alongside James Covello, head of Global Equity Research at Goldman Sachs. The MT Newswires report, AI Revenue May Jump Fivefold to $200 Billion as Spending Race Intensifies, was published on 15 May 2026 and is available through Fidelity and Yahoo Finance.
His writing on AI model economics is also cited by the Chartered Alternative Investment Analyst (CAIA) Association and others.
Research and software
His working papers use market data and statistical methods to study financial markets and digital behavior. Selected research includes:
- The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book: an analysis of 30 billion order-book events over 52 days, with an open-source replication package.
- Synthetic Consumer Panels Without Microdata: Iterative Proportional Fitting from Open Aggregate Statistics: synthetic Swiss consumer panels built from public aggregate statistics, without individual-level microdata.
His asset-allocation research is cited in the Journal of BRSA Banking and Financial Markets. His Polymarket study is cited in preprints by researchers at ETH Zurich and the University of Toronto and the Technical University of Munich.
Find his latest research papers, datasets and code on the research page. Preprints and working papers are available on SSRN and arXiv. Author profiles are on Google Scholar and ORCID.
On his blog, he regularly publishes essays on AI infrastructure, model costs and financial markets. His open-source projects include LLM routing tools, sentiment-trading systems and real-time data archives.
Researchers at City University of Hong Kong cite his essay on on-device AI in a working paper on AI service markets.
All opinions are the author's own. Privacy & contact.