Tag Archives: AXA

Talk on climate models and insurance

Tomorrow morning, at 7 am, I will give a talk at the Actuarial Conference # 62 on climate models and insurance, getting back on two recent paper.

  • Flood, French’s Nat Cat System and Fairness

The first paper is Insurance against NaturalCatastrophes: Balancing Actuarial Fairness and Social Solidarity with Laurence Barry (PARI) and Molly James (EURIA)

Based on official risk areas (PPRL and PPRI)

we will investigate the prices of houses and apartments

and discuss connections between risk and wealth.

  • Subsidence and predictions

The second paper is Predicting Drought and SubsidenceRisks in France with Hani Ali (Willis Re) and Molly James (EURIA)

We did try several models to predict subsidence frequency

GLMs and also random forests

Then we got predictions for frequency, in 2017

and 2018

Then, we’ve been able to derive some risk maps

Here are predictions for costs for 2017

for 2019

and for 2020

I still wonder how to take into account climate change in this approach (except that we are more and more likely to be in the upper left corner – hot and dry)

  • Extensions (wildfires in Québec and RL)

Finally, I will (very briefly) discuss two recent works, the first one with Amirouche Benchallal (UQAM) and Yacine Bouroubi (Sherbrooke) on wildfire in Québec

and the second one, with Nouri Sakr (Columbia) and Mennatalla Mohamed Hassan (AmericanUniversity in Cairo) on government intervention in the context of natural catastrophes.

Unusual data for insurance, joint research initiative

We recently started a joint research initiative, funded by the AXA Research Fund, to work on unusual data for insurance

Insurers sometimes lack information at the time of claim submission, such as the structure of a building, the presence of health risks common to a group of people, or the spatial diffusion of a pandemic. Unusual data, such as satellite images, personal network connections, and tweets can be used to populate this information gap. In this joint research initiative, we will use images, network data, and texts for risk analysis from an actuarial perspective. Specifically, the project will explore how using unusual data can contribute to smoother claims assessment and reduced data quality risk, allowing for better risk selection and pricing. The project will look at three types of unusual data: pictures/satellite images, network data, and text data.

More information will be shared via a dedicated website (https://jridata.github.io/), even if I will also mention interesting papers, conferences and open-source codes on this blog….