Insurance, academia, and capital markets, brought together to build the infrastructure for how risk is measured.
The people building and running Intellegri day to day.
Leads strategy, commercial growth, and the company's direction across insurance and capital markets.
Shapes go-to-market and product strategy, connecting the BHM to real underwriting workflows.
Leads the science behind the BHM, developed over 15 years of peer-reviewed research at Liverpool.
Oversees engineering and model validation, translating research into production-grade tooling.
Advisors who have led risk and analytics functions at some of the industry's largest firms.
Brings decades of catastrophe and risk modelling leadership to the board.
Deep experience in catastrophe risk analytics and insurance data platforms.
Talk to the team about the BHM or explore opportunities at Intellegri.
Andre is an Insurtech pioneer who founded Sciemus, the first truly technical MGA at Lloyd’s. By adapting military-grade technology for the insurance market, he built the world’s largest satellite insurer and led the company to become a Deloitte Technology Company of the Year. He drives Intellegri’s strategic vision.
Simon is a world leader in Bayesian modelling and the original developer of the Big Hypotheses Model. An RAEng Research Chair, he leads the Signal Processing Group at the University of Liverpool, overseeing approximately 80 researchers funded by organisations including the MoD, Dstl, and the European Space Agency. A global authority on using state-of-the-art Bayesian statistics to solve problems involving "awkward data," he sits on the governing body for the Stan probabilistic programming language and is a past President of the International Society of Information Fusion. He previously led the technical team at QinetiQ that supported the original Sciemus algorithms.
Dr Alex Phillips is a postdoctoral data scientist in the Signal Processing Group in the University of Liverpool's Electrical Engineering and Electronics department. Alex's research background is in applying Bayesian modelling to complex, real-world problems. He has a wealth of experience applying his expertise to a diverse range of application fields, spanning from defence and security to epidemiology and bioinformatics. His background includes developing epidemiological models for the UK government during the COVID-19 pandemic to track the R-number and infection spread.
Nick is a proven SaaS commercial leader who previously led Customer Success at Native Data to a $45m exit. A former officer in the Foreign and Commonwealth Office, he served as a specialist adviser to the UK and US governments on data collection and analysis in conflict zones. He was an early investor in Sciemus.
