Document Type : Original Article
Researcher
insurance expert
Ministerial Ethics Committee
Climate change and air pollution (such as O 3 and PM 2.5 ) have created new systemic risks that can lead to a significant increase in mortality, especially in polluted cities like Tehran, Isfahan, and Ahvaz. Traditional actuarial models for calculating life insurance premiums do not adequately reflect these risks. This is the first study to investigate the effects of weather dynamics using deep learning methods and air pollution data on life insurance actuarial analysis in Iran.
The results of this research will help insurance companies and the Central Insurance of I.R. of Iran to establish insurance fairness by adjusting mortality table coefficients based on polluted/clean geographic regions and to price the risk based on actual risk (instead of transferring the costs of polluted cities to clean cities). The required data includes mortality records (age, date, cause of death, region) and time-series data on weather and air pollution (such as PM 2.5 , NO2 , temperature, humidity, and wind speed).