Internship - CAT Analyst Intern

Internship
Puteaux
Salary: Not specified
A few days at home
Apply

AXA
AXA

Interested in this job?

Apply
Questions and answers about the job

The position

Job description

Your environment

As a leading global insurer, AXA faces highly sophisticated P&C challenges, among which natural catastrophe risk (CAT). Among disasters, climatic and seismic events show large variability in size and frequency, with devastating consequences; not to mention climate change which brings added uncertainty for the future. AXA acquired in 2018 100% of XL Group Ltd, a leading global Property & Casualty commercial lines insurer and reinsurer with strong presence in North America, Europe, Lloyd’s, and Asia-Pacific, increasing the Group exposure to natural catastrophe risk.

Group Risk Management

AXA GRM brings together a high level and multidisciplinary team of engineers, actuaries, and financial analysts. Its main missions focused on the following key areas:

  • analyze, model, and aggregate the Group’s risks (Economic Capital),
  • define the process enabling to limit the undertaken risks (e.g., Risk Appetite),
  • optimize the Group protections (Reinsurance, securitization, hedging, etc.).

Job background

The position belongs to the Platforms, Data & Analytics team within the Group P&C Risk Management Natural Events and Reinsurance team.

As part of AXA’s Internal Model under the Solvency II framework, the CAT and Reinsurance team are primarily in charge of delivering the annual CAT and Reinsurance modeling process, consisting of:

  • Collecting all CAT exposure data on a per-entity and per-location basis
  • Assessing the risk on a per-entity and per-peril basis (cyclones, earthquakes, floods, hailstorms, wildfires, …) which feeds the whole AXA value chain at both entity and group level (reinsurance strategy, capital, underwriting, …)
  • Model property reinsurance structure, estimate the efficiency of the Group Reinsurance covers and manage the Nat CAT Risk Appetite Framework
  • Developing in-house models, methodologies, and applications to support the Nat CAT risk management strategy and support internal needs of various stakeholders.

Your missions 

 A global insurance group as AXA needs to develop a sound understanding of the frequency, intensity, and impacts of natural hazard events. Live and historical records are one of the most important sources to derive such information. Besides, reporting of live events, and potential loss estimates, provide critical early information to risk managers and claim handlers. An automatic procedure, also labelled as LiveCat, must be in place to retrieve documentation and compute first estimate of AXA losses during a live catastrophic event.

The intern will actively contribute to this effort by improving the current LiveCat procedure. Main steps will be:

  • Understanding of current procedure and scripts 
  • Automatic detection of footprints of catastrophic events with characteristics specific for each peril.
  • Export of footprint in AXA’s GIS platform for risk assessment and underwriting.
  • Calculation of gross loss using AXA’s catastrophe models

Vous rejoignez une entreprise :

-    Responsable, vis-à-vis des personnes, y compris ses employés et ses clients, et de la planète. -    Aux valeurs fortes-    Qui encourage la mobilité interne, et la formation de ses employés-    Qui vous offre de nombreux avantages (en savoir plus ici : Reward & Benefits - french | AXA Group)-    Flexible, qui permet le travail hybride, au bureau et à la maison.

Les informations fournies par les candidat(e)s seront traitées de manière strictement confidentielle et utilisées uniquement à des fins de recrutement.


Preferred experience

Your profile 

  • Master student with background in data sciences, Earth sciences, geospatial sciences and/or informatics, engineering school
  • Interest in climate and Earth sciences,
  • IT skills o R or Python, basics required, proficiency appreciated. o ArcGIS or QGIS experience, proficiency is a plus
  • Analytical skills and ability for abstraction.

Want to know more?

Apply