A Lifecycle Approach to Insurance Solvency

At present, most well-known insurance regulatory bodies focus on reviewing the solvency of insurance companies within a one-year period. However, the operation of insurance companies is a long-term business, with most policyholders planning on holding a policy over many years, not just one. This research adopts a new perspective for measuring the insolvency risk faced by insurance companies over a longer time period by estimating their full expected lifetime (the number of periods into the future that an insurer can be expected to remain solvent, given their initial capital reserves), which has significance for insurance regulation. This research uses python numerical methods to simulate the operating conditions of insurance companies with different initial reserves, and capture the period in which the company becomes insolvent. The results show that, as is logical, the higher is the initial reserve fund, the longer one can expect the company will be in business before insolvency. In addition, our simulation model helps to explain how the relevant probability density for the insolvency date, given an initial reserve fund, can be estimated. By comparing different probability density functions, we find that a lognormal density form provides a reasonable starting point for the density in question.