Orateur
Description
The modern insurance landscape is increasingly shaped by the emergence of new risks with destructive potential, challenging the feasibility of developing sustainable financial protection mechanisms. Many administrations and regulators frequently emphasize the potential uninsurability of certain risks, such as those stemming from natural disasters linked to climate change or cyber-attacks associated with rapidly advancing artificial intelligence. To address these challenges, index-based insurance is often highlighted as a technical tool capable of providing coverage in situations that might otherwise seem intractable. This paper proposes the design of index insurance coverage for extreme losses, focusing specifically on cases where these losses exhibit heavy-tailed distributions. The index coverage is structured to activate above a predetermined threshold, while traditional indemnity-based insurance remains in effect below this threshold. This approach seeks to combine the advantages of both coverage types. The proposed methodology begins by adapting the standard utility of wealth framework to accommodate heavy-tailed losses. An approximation of this utility is then developed to account for the scarcity of economic loss data that is often encountered in practice. Finally, the study concludes with an empirical verification, demonstrating that the proposed insurance framework remains effective even in scenarios of limited loss data, provided sufficient data on the index is available.
