Modeling stroke insurance from prevalence rates and analyzing the impact of COVID-19 on asset shares

This study focuses on the financial aspects of stroke in Indonesia through insurance modeling, using prevalence rates as a primary data source due to the limited availability of detailed medical information. We employ the Weibull and Gompertz mortality models to evaluate which model better captures the dynamics of stroke mortality in Indonesia. The analysis includes calculating transition probabilities, net single premiums, and reserves. We also analyze the impacts of the COVID-19 pandemic on the asset shares of stroke insurance. Our calculations suggest that older people are less likely to remain healthy under the Gompertz model, while younger people are less likely to remain healthy under the Weibull model. This implies that an insurance company’s assets are safer with the Gompertz model, while the Weibull model could lead to higher sales due to lower premiums. In a pandemic, the asset shares are more conservative under the Gompertz model than the Weibull model. Based on these results, we propose scenarios for future post-pandemic financial planning for the insurance industry in Indonesia.