A system to quantify insurance premiums for extreme rainfall downpours

My aim is to develop an open-source prototype system to help planning the financial strategy of insurance/reinsurance firms and quantifying insurance premiums related to extreme downpours with lead times up to a decade.

Extreme downpours consist of very heavy rain intensities concentrated in a few minutes up to a few hours. They may cause urban pluvial floods, flash floods and debris flows, with disproportionate human and economic impacts that make them a major item in insurance and reinsurance losses. To properly plan firms’ financial strategies and quantify insurance premiums, we need to anticipate the probability of observing such extremes in the coming year/decade. We still cannot do that. Climate variability challenges our loss estimates for the upcoming years, and climate change is rapidly increasing the frequency and intensity of such events, challenging the assumptions of the statistical models we use to quantify these extremes. In addition, downpours are caused by convective processes, which are not resolved by most of our models. The available convection-permitting models have computational costs so high that they cannot yet be run for decadal-long simulations with frequent re-initiations. My idea is to combine near term forecasts with a physics-informed statistical model able to predict the probability of extreme downpours from changes in wet-day temperature. I will introduce the theory behind the statistical model, showing some applications and demonstrating its ability to predict the statistics of extreme downpours from wet-day temperatures only. I will then lay out the structure of the prototype system and describe the validation strategy, to be carried out in close cooperation with Moody’s Insurance Solutions, a professional partner from the insurance and reinsurance business that will run in-house loss modeling chains based on the system’s forecasts and evaluate its potential usefulness using retrospective simulations and records of past losses.