Kettle, a insurtech company that creates machine-learning-powered reinsurers balancing risk in a dynamic climate, is using deep learning and proprietary algorithms to redesign the reinsurance industry to excel in protecting people from the burgeoning risks of climate change.
The company’s first product is wildfire reinsurance, which protects the businesses, homes, and livelihoods of Californians.
Co-founder Nathaniel Manning commented on this work in California, saying: “We are thrilled to be helping provide insight and relief to the California insurance market. There are 14 million structures in California, and in 2020 ~ 11,500 of them burned down, less than .1%. While the risks of wildfire have certainly increased over the past decade, the key is understanding exactly where the risk is. If we can do that, we can bring stability back to the California insurance market.”
With its smarter reinsurance model, Kettle manages risk in a changing climate and aspires to use data to improve the world.
Kettle beats the industry with its technology as it employs unique machine learning algorithms that analyze over seven billion lines of meteorological and ground truth data.
Its underwriting platform employs cutting-edge technology to provide customers with better protection and the insurance business with more reliable returns.
To do this, Kettle uses a computer vision-based extract, transform, and load (ETL) pipeline to handle the collected raw data. Kettle has gathered more than 7 billion rows of data with these machine learning skills, giving them a leg up on the competition.
Keeping people safe from the mounting dangers of climate change
Engler joins the organization with over a decade of expertise in the insurance and reinsurance industries.
Manning, prior to Kettle, worked with data for humanitarian action for many years. He was CEO of Ushahidi, the largest open-source crisis response software platform, and first chief data officer of USAID.
Kettle introduces cutting-edge technology to the $400 billion-per-year reinsurance industry.
Kettle’s model predicted that the fourteen largest fires, which caused 98 percent of the damage, would burn in the top 20% of regions most likely to burn throughout California’s hundred-plus million acres in 2020.
Furthermore, in 2021, Kettle’s model predicted that the Dixie and Kaldor fire areas are some of the most dangerous areas in California.
Subsequent to its success, the company recently announced a $25 million Series A funding round led by Acrew Capital.
Source: AI Magazine