With this paper, the authors have wished to present a mathematic model allowing to predict the number and the cost of incoming catastrophes. The data it is built upon include wind catastrophes affecting the southeast area of the United States and which damages exceed a billion dollars.

Over the last fifty years, numbers and costs of natural disasters have indeed multiplied, and insurers and reinsurers, struggling to cover the associated losses, have turned to financial markets in order to obtain new hedging capabilities, among which products “excess of loss contracts” (named XL) and cat bonds.

The model intends to assist in the pricing of insurance risk transfer products, such as XL contracts or cat bonds. To read online : https://www.risklibrary.net/risk-management/cat-bonds-artificial-neural-networks-example-reinsurance-products-pricing-using-machine-learning-methods-29456?cta=true