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The Application of High Performance Computing to Solvency and Profitability Calculations for Life Assurance Contracts

机译:高性能计算在寿险合同偿付能力和获利能力计算中的应用

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In the UK, pension providers are required by law to demonstrate solvency on a regular basis; the regulations governing how solvency is demonstrated are changing. Historically, it has been sufficient to report solvency using a single 'best estimate' set of assumptions. The new regulations require a Monte Carlo approach to finding a worst-case scenario that requires computing power which is outside the systems currently available in the industry. This paper aims to show that the new regulations could be met by moving away from current actuarial valuation software packages and producing well-performing ab initio code, employing a variety of HPC techniques. Using a combination of algorithmic improvements, serial optimisations and multi-core parallelism, we demonstrate a performance improvement over commercial software of a factor of over 10^5. We show that this brings the Monte Carlo simulations within the bounds of practicality, and we suggest possibilities for further improvements, for example using clusters of GPUs. We also identify other possible use cases for high performance solvency and profitability calculations.
机译:在英国,法律要求养老金提供者定期证明其偿付能力;有关如何证明偿付能力的规定正在改变。从历史上看,使用一组“最佳估计”假设来报告偿付能力就足够了。新法规要求采用蒙特卡洛方法来找到最坏的情况,这种情况要求计算能力超出行业当前可用的系统范围。本文旨在表明,通过使用多种HPC技术,摆脱当前的精算评估软件包并生成性能良好的从头编写代码,可以满足新法规的要求。通过结合算法改进,串行优化和多核并行性,我们证明了与商用软件相比性能提高了10 ^ 5倍。我们证明这将蒙特卡洛模拟带入了实用性的界限,并且我们提出了进一步改进的可能性,例如使用GPU集群。我们还为高性能偿付能力和获利能力计算确定了其他可能的用例。

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