Introduction
In the last decade, there has been a significant rise in the number of satellite launches with a growth from mere 1000 to 5000 satellites orbiting currently and projected to grow to 12000 by number and $1 trillion in spend by 2030. The key driver of the surge have been : a) advances in hyperspectral imaging b) lower launch cost coupled with lower computation cost c) NASA, ISRO, ESA and technology companies like Google Earth engine powering easy and free plug-ins for large-scale consumption/applications.
Insurance industry has been tapping into the use of real-time imagery for the flood, hurricanes etc. for live NatCat monitoring and processing claims for a while now. The underwriting space is seeing increased adoption and this article will delve into details of a few use cases and benefits.
I. Precision Pricing
a) Property Insurance: Natural catastrophe risks are the biggest cause of property loss and estimation of the TIV is always a challenge and lot of times zip code level averages are used to price those covers. High resolution imagery not just gets the building measurements accurately but also captures information like roof and façade material, presence of swimming pool, roof quality and neighbourhood area details like vegetation etc. Hence, accurate models can built to estimate TIVs and fed into the traditional CAT models with enriched exposure data extracted from these images.
b) Crop Insurance: Sentinel-1 which is equipped with Synthetic Aperture Radar (SAR), can capture high-resolution images regardless of weather conditions or sunlight. This is particularly useful for monitoring soil moisture, pH and other conditions of the soil. This can help with assessing the risk at the time of sowing, project the risk at various growing stages of the crop. Further coupled with future weather pattern predictions this can translate to a precise crop insurance pricing for different variants.
II. Rise of Micro and Index based insurance
The parametric products in the insurance industry is witnessing an increase and expected to touch a $1 trillion size by 2028 with growing need for simplifying NatCat insurance in the advent of rising extreme events. The traditional CAT covers are typically very large and don’t see a lot of penetration in developing countries. Innovative climate-related parametric insurance covers offer tailored solutions to manage various climate risks by leveraging modern technology and data.
a) Drought index based cover for businesses depending on water supply
b) Cloud index based cover for solar fields.
c) Heatwave index based cover for dairy production/health issues
d) Excess rainfall based cover for loss of income for gig workers like delivery folks/street vendors
These products provide timely and objective payouts based on predefined parameters, improving resilience and financial protection for businesses and individuals exposed to climate-related hazards.
Role of AI/Technology
Data Processing: Deep learning techniques improve the quality of satellite images by reducing noise, correcting distortions, detecting change and also aid in labelling the data by better LULC classification, object identification etc.
Predictive Modelling: Most traditional climate models follow physics based approach while techniques like LSTM will lead to a more accurate prediction by incorporating accurate current state of weather.
Automation/Scalability: AI enables the handling and analysis of massive amounts of satellite data efficiently, making it scalable for large-scale applications and global monitoring.
Conclusion
Insurance industry can see massive benefits in the underwriting space in terms of better product design, better pricing and risk management along with risk monitoring.
Author: Suguna Jayaraj, Pricing Director, MIC Global
Disclaimer: The opinions expressed within this article are the personal opinions of the author. The facts and opinions appearing in the article do not reflect the views of IIA and IIA does not assume any responsibility or liability for the same.