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

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 105. 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.