Data Science

Laurent Dupont shares the lessons of a recent TechSprint concerning the explainability of ‘black box’ models

Artificial intelligence-related risk differs from traditional model risk, explain Andrew Morgan, Valerie du Preez and Natasha Naidoo –how can we get to grips with it?

Olga Mierzwa-Sulima, Robin Whytock and Jdrzej wieewski share their experience of building a machine learning algorithm that helps track biodiversity in Gabon’s tropical forests

Alin Radu, Laurent Sabatié and Davide De Santis discuss insurers’ use of novel data sources and structures to create innovative parametric products

Niall Fennelly sets out key lessons around electronic health records for insurance, and explores what the future could hold

David Lu and Wendy Wang investigate the increasing global incidence of lung cancer among women who have never smoked

Gillian Rutherford-Liske and Samantha Dunn explain the role general insurers can play in tackling extreme weather and ecosystem loss

Jonathan Khanlian outlines how the machine learning technique of reinforcement learning can be viewed from an actuarial perspective

Louise Pryor, Colin Dutkiewicz and Krishna Kumar Shrestha reflect on the ICAT’s recent R number hackathon, and what it means for the profession’s future skillset and role in society.

The proportion of the global population exposed to floods has grown by a quarter since 2000, a 10-fold difference from what scientists previously thought, analysis has uncovered.