The use of proxy models within the insurance sector has grown considerably in recent years, particularly in the area of capital management. This growth has been largely driven by the increased demands of a changing regulatory and risk management landscape set against the inability of traditional modelling techniques to keep up.

This paper takes a look at some of the types of proxy model available to practitioners, suggesting a basic framework for “replicating formula” type proxies into which many current proxy models fit. Within this framework—drawing heavily on recurring themes of complexity, accuracy and use of the model—the options available in the design and implementation of a model are discussed, as well as the potential impact of the choices made.

Finally, four specific proxy models are discussed in greater detail, two of which are the subject of a case study. This leads to a key result concerning the distinction between risk scenario accuracy and risk distribution accuracy as the key driver for risk capital estimation.