Under the background of global warming, heat wave events have frequently occurred around the world and increased the mortality risk greatly. Based on the daily meteorological data from 1951 to 2015 and daily mortality data from 2007 to 2013 in three cities (Nanjing, Chongqing, Guangzhou), a heat wave intensity index was firstly designed to quantify the heat waves, and then a distributed lag non-linear model (DLNM) was used to develop the vulnerability models of population under the heat wave events. Finally, Monte Carlo simulation method was run to assess the probabilistic heat wave risk and rated the premiums for heat wave life insurance. The results show that, the heat wave mortality risks and pure premium rates for the elder are both 9 to 28 times that of the young and the pure premium rates are inversely proportional to the level of socioeconomic development. The results in this study can provide guidance for developing weather index-based individual life/health insurance products and give support for the government to adopt comprehensive risk management measures to reduce public health risks.