  Stochastic simulation techniques employed for the analysis of portfolios of
insurance/reinsurance risk, often referred to as `Aggregate Risk Analysis', can
benefit from exploiting state-of-the-art high-performance computing platforms.
In this paper, parallel methods to speed-up aggregate risk analysis for
supporting real-time pricing are explored. An algorithm for analysing aggregate
risk is proposed and implemented for multi-core CPUs and for many-core GPUs.
Experimental studies indicate that GPUs offer a feasible alternative solution
over traditional high-performance computing systems. A simulation of 1,000,000
trials with 1,000 catastrophic events per trial on a typical exposure set and
contract structure is performed in less than 5 seconds on a multiple GPU
platform. The key result is that the multiple GPU implementation can be used in
real-time pricing scenarios as it is approximately 77x times faster than the
sequential counterpart implemented on a CPU.
