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

Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs