The recording of this presentation has been updated in February 2024.

Starting with a real world set of N economic scenarios, and an asset class to act as numeraire, the RASS is a subset of size N(1-a) which is calibrated to the current market and maximizes the present value of the Net Illiquid Liability of an insurer. The Net Illiquid Liability is the present value of risk adjusted liability cash flows less the present value of risk adjusted illiquid asset cash flows. This scenario set turns out to have many useful risk management applications ranging from constructing a market consistent balance sheet to pricing new illiquid instruments and A/LM. The RASS is extracted from the whole scenario set by solving a linear program. The parameter a is a CTE level that controls the amount of conservatism in the linear program. The model can be thought of as a compromise between the actuarial and financial engineering approaches to risk. We will argue that the model could be used not only for risk management but, with some adjustments, as a foundation for market consistent financial reporting and regulatory reporting. The presentation will conclude with some practical and theoretical examples. One example, is that of putting a value on a 60-year insurance product with only 30 years of market data to work with.