Global insured losses from natural catastrophes totaled US$129 billion in 2025, about 5% below the 10-year average, according to Gallagher Re's full-year Natural Catastrophe and Climate Report.
The United States accounted for US$100 billion, or 78%, of the global total. The January wildfires in Los Angeles generated the largest insured loss event of the year at an estimated US$41 billion.
Severe convective storms drove at least 47% of global insured losses, totaling US$60 billion. Of that figure, US$51 billion occurred in the US.
The year was also the third warmest on record, according to major global scientific agencies. It marked the first year since 2015 without a landfalling hurricane on the US mainland.
Aon's own report, also released this month, placed global economic losses at approximately US$260 billion and insured losses between US$120 billion and US$127 billion.
The report noted that 2025 marked the sixth consecutive year in which insured losses exceeded US$100 billion. It also recorded 30 billion-dollar insured loss events during the year, nearly double the historical average of 17.
Steve Bowen (pictured above), Gallagher Re's chief science officer, said several countries faced financial and societal strain from major disasters, with significant portions of economic losses remaining uninsured. He cited Jamaica, Myanmar, Indonesia, Sri Lanka, and Pakistan as examples.
Bowen noted that the reinsurance industry enters 2026 with US$838 billion in capital available for deployment, according to Gallagher Re's 1st View report.
"The complexity of natural catastrophe events is accelerating the need to better understand how both physical and non-physical risk profiles are evolving and becoming increasingly interconnected," Bowen said.
The report identified the growing integration of artificial intelligence as a development in weather and climate forecasting. AI-trained models have been used to improve analytics capabilities and support client decision-making on future risks.
Last year, AI became part of official agencies' tools for predicting tropical cyclone formation points, tracks, and intensity. However, the report noted that AI models require further training to improve precision in factors such as precipitation and other compound features that drive overall storm risk.
The report also examined the influence of El Niño and La Niña on the rapid intensification of tropical cyclones, weather and climate funding in insurtech, and the continued expansion of climate litigation.
