As part of the InterLuft project, we are envisioning future use cases of ubiquitous air quality data in our cities: This article is part of a series of visions of the future and thought experiments on how our surroundings might become more environmentally sensitive with the increasing availability of environmental datasets. Read on to find out more!
(Re-)insurances companies as a powerful ally in the fight against air pollution
Air pollution affects everybody. It is detrimental to a nation’s health, it affects ecosystems and crop yields, and even directly influences economic indicators like stock prices. Through this deep connection with the economy and in an age where the first courts are recognizing air pollution as people’s cause of death, air pollution data is also highly relevant for insurance and reinsurance companies to consider; both when modelling risk, and when working towards damage prevention.
Indeed, air pollution is nowadays regularly called an “emerging risk factor” for the insurance sector, and could become a major factor for underwriting (evaluating and analyzing the risks involved in insuring people and assets) and thereby pricing for – but not limited to – life insurances.
With the increasing understanding of air pollution as a risk factor for a whole host of asset classes, insurers and reinsurers may be incentivized to implement their own clean air efforts in areas with particularly high risk involvement on their side, for instance in neighborhoods or cities where they have insured a significant amount of customers. Larger insurers might even consider partnering with (municipal) governments to drive more systemic change towards more livable urban environments. They could also provide local data to their customers and provide incentives if they protect themselves from high levels of air pollution, for instance through following smog alerts, wearing masks and using indoor air filtration devices.
Additional data equals additional incentives to curb air pollution
These trends would also be driven by the increasing availability of hyperlocal air quality data. Street-level or block-level air quality information is going to create a much better understanding of pollution exposure and connected risks for local populations, as well as physical assets like crop and lifestock. The required data stems from lower-cost sensors, satellites, as well as interpolation algorithms.
More data leads to a better understanding of the status quo, and may lead to the discovery of additional business cases for clean air action, including in the insurance sector. If implementing clean air actions leads to overall lower costs for an insurer than covering air pollution-related damages, it will be easy for them to decide what to do.
In the meantime, it will be up to particularly innovative and sustainability-committed actors to pilot first use cases around air pollution-related risks. If you are in the insurance sector and would like to start working with hyperlocal air quality data in your products and processes, please do not hesitate to reach out!