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AI* to help assess the impact of climate change on the activities in the financial sector

An R&D programme carried out in partnership with Skema Business School and Côte d’Azur University.


AI makes it easier to assess and anticipate financial climate risks (e.g. risks for insurers, credit risks, and/or market risks).


The predictive machine learning model developed takes advantage of the increase in existing climate data to refine the accuracy of forecasts of climate risks and their impact on the activities of the financial sector, enabling optimisation of the management of the associated financial risks.


This method, developed on a predictive platform, is based on a two-stage process using the latest machine learning techniques:

  1. Identification, collection, and analysis of existing climate data to estimate the climate risks identified (e.g. fires, floods);

  2. Integration of these estimated climate risks into the financial data considered, such as claims rates or asset values, to assess and anticipate the potential related financial risks.


Banks, insurance companies, asset managers.


Doctor Anass Akrim

Doctor Anass Akrim

Anass obtained his PhD in Artificial Intelligence and Applied Mathematics in predictive maintenance (aeronautics sector). He studied Applied Mathematics, Computer Science and Finance at Paris Dauphine University. He also has an engineering degree from the Ecole des Mines in Big Data and Data Science, combined with a double degree in Banking and Finance from the IAE in Saint-Etienne. Anass has worked in a variety of business sectors and on a range of A.I. applications: time series processing (stock price prediction, automatic trading), financial fraud detection, predictive maintenance (aeronautics sector).

  • Article académique : A. Akrim et al. “Self-Supervised Learning for Data Scarcity in a Fatigue Damage Prognostic Problem” Engineering Applications of Artificial Intelligence, 2023, doi :
  • Note : “L’intelligence artificielle dans le secteur financier, le défi de la « Data Scarcity » ”
  • Working paper : “L’IA pré-entraînée : une technique innovante pour une détection de fraudes plus performante” (à venir)

Sébastien ATTIA

Sébastien holds a master’s degree in Datascience applied to Finance from the University of Paris I Panthéon-Sorbonne, and joined the Square Research Center as part of a CIFRE doctorate. Sébastien is carrying out his thesis in partnership with Skema Business School and the Université Côte d’Azur.


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