Europe 13 Demo Day


| Augmize automates actuarial reserving in commercial insurance with interpretable machine learning.


Commercial insurers forecast future claims to hold sufficient capital in reserve, and steer business planning away from losses towards profit.

Today, low forecasting accuracy and manual process means management receive blunt decision analytics, too late to take corrective action.

Augmize automates reserving to deliver timely decision analytics to management. We use interpretable machine learning to outperform current methods, meeting strict demands for model explainability.

We are trialling Augmize with an international insurer, over $1B of claims data, and are in negotiations for two paid contracts.

Meet The Founders


Jon has 5 years start-up experience building data and analytics products in capital markets as product lead. He has built pre-trade analytics platforms for global investment banks, and portfolio reporting tools for leading asset managers. He holds a masters degree in Physics from Imperial College London.


Favour has a PhD in Machine Learning from Oxford University as a Rhodes Scholar, specialising in datamining and interpretable models.

He has 10 years software development and data science experience, working on quantitative finance problems at the Oxford-Man Institute, and data mining for the US government.