A Structural Simulation Model for Measuring General Insurance Risk

Motivation: As use of economic capital models expands, the need for a robust approach to the measurement of reserving and pricing risk becomes increasingly important. The paper describes a stochastic simulation model developed by the authors that has some attractive advantages over other published approaches to risk measurement. A particular issue is the need to measure reserving and pricing risk over a one-year time horizon; the model does both one-year and run-off risk measurement.

Method: The Structural Model separates overall insurance risk into systematic and non-systematic risk elements, using an Economic Scenario Generator to simulate the former and the Practical method to simulate the latter. In addition, it combines stochastic chain ladder projections of past years with a stochastic ARMA loss ratio model for recent and future years, facilitating the measurement of reserving and pricing risk in an integrated way.

Results: The Structural Model offers several benefits, described in the paper and illustrated using an empirical dataset. Illustrative validation results are also presented. These include some useful ideas about validation that may be applied to other approaches, as well.

Conclusions: The Structural Model is a practical approach to measuring reserve and pricing risk in an integrated way, over either a one-year or run-off risk horizon. Its ability to separate systematic economic risks from general claim misestimation risk is particularly relevant, given the concerns about a resurgence of inflation. It can be successfully validated using historical data on past reserve and pricing errors.

Availability: No software is being made available with the paper.

Keywords: Economic capital, stochastic reserving, financial modeling, inflation risk, economic scenario generator, ARMA model