Deep Neural Network Algorithms for Parabolic PIDEs and Applications in Insurance Mathematics

Understand

In recent years a large literature on deep learning based methods for the numerical solution partial differential equations has emerged; results for integro-differential equations on the other hand are scarce.

• In this paper we study deep neural network algorithms for solving linear and semilinear parabolic partial integro-differential equations with boundary conditions in high dimension.
• To show the viability of our approach we discuss several case studies from insurance and finance.