  In this work, we will show strong convergence of the Multilevel Monte-Carlo
(MLMC) algorithm with split-step backward Euler (SSBE) and backward
(drift-implicit) Euler (BE) schemes for nonlinear jump-diffusion stochastic
differential equations (SDEs) when the coefficient drift is globally one-sided
Lipschitz and the test function is only locally Lipschitz. We also confirm
these theoretical results by numerical experiments for the jump-diffusion
processes.
