EOS project

Actuaries and STatisticians endeavour to design innovative, inclusive insurance products in a changing RISK landscape (ASTeRISK)

Actuaries design and value risk transfers by analyzing insurance data sets with a sophisticated statistical toolbox. Current practice faces technical challenges in the design and estimation of risk models from fine-grained data. At the same time, trust in modern-day insurance is under pressure. Policyholders and regulators expect value creation from the collected granular data in the form of better insurance products and a wider coverage of (new types of) risks. New forms of mutual insurance (e.g., peer-to-peer covers) recently emerged outside traditional insurance, inspired by evolutions in the sharing economy. In response to these challenges our project aims to shape the statistical toolbox necessary for building valid, reproducible and viable risk models for the granular data collected in a variety of key actuarial tasks. Building on solid methodological foundations our project innovates by explicitly incorporating a dynamic prediction and prevention view into these risk models.  Moreover, we aim to contribute to a better, more inclusive and fair access to insurance with the design of a wide array of new risk-sharing solutions and the development of novel quantitative tools to spot (proxy) discrimination in insurance pricing.  Finally, the project targets tailored statistical models to assess actual riskiness and to refine the implementation of the recent ‘right to be forgotten’ that should improve the access of cancer survivors to essential insurance products.

Promoter: Katrien Antonio (KU Leuven) and Donatien Hainaut (UCLouvain)
Website : https://eos-asterisk.netlify.app/