Artificial Intelligence and Internal Models: respective performances

SCOR Foundation Conference led by Henri Fraisse and Mathias Laporte, January 26, 2023

Image AI & Internal Models

On January 26, the SCOR Foundation for Science held a conference-debate titled "Artificial Intelligence and Internal Models: respective performances", with Henri Fraisse and Mathias Laporte from the General Inspectorate of the Banque de France. 

Henri Fraisse and Matthias Laporte shared the results of their recent study on the efficiency and competitiveness of using artificial intelligence for capital requirement calculations, compared to the traditional internal model approach: This is a hot topic, particularly right now when Solvency 2 regulation is the subject of an in-depth review. The results show all the advantages for banks of investing in artificial intelligence, but also the relative relevance of their traditional tools. This study was carried out on the banking sector, but is also applicable to the (re)insurance sector insofar as the empirical challenges linked to internal models are largely similar. The working paper “Return on Investment on AI: The Case of Capital Requirement” will be published by the internationally renowned Journal of Banking and Finance.  

For more information, access the presentation and working paper from the links to the right: