Pierre-Edouard Arrouy

We offer some valuable insights into scenario reduction and trajectory selection for stochastic ALM valuation that could help improve results and minimize computation.

In the valuation of insurance liabilities, using high-quality credit data reduces the need for excessive constraints in the calibration process.

Increasing use of stochastic economic scenarios for valuation of liabilities has put more pressure on the operational process of carriers, but the RNG can help.

We highlight a Libor market model with constant elastic volatility, showing an interesting trade-off between parameters used and quality of results.

We present a calibration technique for one complex risk neutral model, relying on neural networks and significantly reducing computational time.

Learn why the best economic scenario generator solution provides the choice of different methods and what challenges real world models pose.

We explore a new methodology to show lower equity shocks, since stock markets are mean-reverting and insurers hold equities for the long-term.

While setting the overall discount rate under IFRS 17 might seem overwhelming, we give some practical considerations to get the job done.

This paper is part of a series covering the overall process for discount rates under IFRS 17, specifically the number of steps required to set a discount rate.

IFRS 17 requires preparers of accounts to derive discount rates for the valuation of the cash flows associated with their insurance contracts.