  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.
