With a 200-year legacy, parametric insurance has been relatively slow to gain traction, often viewed by traditional insurers as a specialized offering suitable for high-risk exposures. The escalating challenges posed by inflation and heightened climate volatility are pushing insurance providers away from conventional markets, compelling stakeholders to seek out alternative risk management solutions, particularly those driven by artificial intelligence. Projections indicate that the parametric insurance market could reach $29.1 billion by 2032, signaling a potential turning point for this insurance approach.
As the frequency and severity of climate change-related disasters increase, and traditional insurers grapple with underwriting difficulties in high-loss regions, there is a growing acceptance of parametric insurance within the industry. Parametric policies operate by covering the likelihood of a specific event occurring, triggering automatic payouts when predefined parameters are met—such as a hurricane of a specified intensity at a particular location. Unlike traditional insurance, parametric payouts are not based on actual losses incurred by the policyholder, leading to what is known as basis risk—the variance between the policyholder’s actual financial loss and the insurance payout received.
The persistent challenge of basis risk has been a key factor hindering the widespread adoption of parametric insurance. However, advancements in AI technology now offer the potential to mitigate basis risk significantly, opening the door to innovative hybrid products that blend parametric features with the precision of traditional insurance coverage.
AI applications are revolutionizing the interpretation of complex environmental data to provide actionable insights for catastrophic events like droughts and wildfires.
The intricate nature of designing parametric solutions, encompassing pricing strategies and sophisticated data analytics requirements, has historically posed implementation challenges for insurers at scale. Following the aftermath of Hurricane Maria in 2017, which left Puerto Ricans with $1.6 billion in unresolved insurance claims, entrepreneur Jonathan Gonzalez founded Raincoat. This company, a part of the author’s investment portfolio, collaborates with established insurers to integrate an AI-driven application layer that facilitates advanced parametric products covering various risks. By leveraging neural networks and machine learning algorithms, Raincoat enhances the ability to predict and respond to environmental events, whether sudden occurrences like hurricanes or gradual phenomena such as droughts.
While emerging markets have shown the highest adoption rates for parametric insurance due to cost considerations, mature insurance markets are also witnessing a surge in parametric solutions driven by inflation and the escalating impact of climate-related disasters. In response to the escalating homeowner’s insurance crisis in the U.S., some insurers are withdrawing from high-risk states, leading to a rapid expansion of excess and surplus markets. Companies like Kettle, specializing in commercial parametric wildfire coverage, utilize AI to refine pricing models and reduce basis risk by generating synthetic wind speed data without the need for costly hardware sensors on every building. Similarly, Fathom, acquired by Swiss Re, leverages AI to analyze global factors influencing flood frequency and severity, offering valuable insights to insurers and asset managers seeking advanced risk assessment tools.
Given the increasing frequency of natural disasters compared to half a century ago, the evolving climate landscape represents a critical juncture for the insurance sector. Ultimately, customers prioritize enhanced experiences, superior products, and increased protection, regardless of whether their insurance coverage is labeled as parametric. As predictive analytics and data sources continue to evolve, the insurance industry is poised to integrate parametric principles more extensively to enhance existing products and develop innovative risk management solutions tailored to the evolving environment.
Disclosure: The author has invested in Kettle and Raincoat, two companies mentioned in the text, through Anthemis. The initial investment in Kettle took place in 2020, followed by the investment in Raincoat in 2022.
