  The risk of reinsurance portfolios covering globally occurring natural
catastrophes, such as earthquakes and hurricanes, is quantified by employing
simulations. These simulations are computationally intensive and require large
amounts of data to be processed. The use of many-core hardware accelerators,
such as the Intel Xeon Phi and the NVIDIA Graphics Processing Unit (GPU), are
desirable for achieving high-performance risk analytics. In this paper, we set
out to investigate how accelerators can be employed in risk analytics, focusing
on developing parallel algorithms for Aggregate Risk Analysis, a simulation
which computes the Probable Maximum Loss of a portfolio taking both primary and
secondary uncertainties into account. The key result is that both hardware
accelerators are useful in different contexts; without taking data transfer
times into account the Phi had lowest execution times when used independently
and the GPU along with a host in a hybrid platform yielded best performance.
