Guy Carpenter has identified climate change as a growing factor in natural peril risk calculations for insurers in the Asia Pacific region.
Over the last decade, the frequency and severity of weather-related disasters – including floods, hail, severe convective storms, and wildfires – have increased. Notable events include Super Typhoon Yagi in 2024, which caused significant damage from the Philippines to Myanmar and resulted in more than 300 fatalities in Vietnam, as well as record-breaking rainfall in Hong Kong in August 2025 that led to widespread flooding and landslides.
While high-profile catastrophes attract attention from the media, the insurance industry, and the public, Guy Carpenter notes that less focus is given to the gradual rise in annual insurance claims caused by “silent climate” events. These smaller, high-frequency losses may not make headlines but steadily accumulate, eroding insurer margins and presenting a long-term challenge for the sector.
Traditional catastrophe models, according to Guy Carpenter, are designed to assess extreme natural peril risks and often overlook the cumulative impact of silent climate risks. By prioritizing major events, these models may underestimate smaller, frequent losses, leaving insurance portfolios exposed to unforeseen financial strain.
To address these evolving risks, Guy Carpenter suggests that insurers in Asia Pacific diversify their portfolios geographically and implement risk-based pricing, particularly for new developments and construction.
This approach can encourage developers and local governments to consider climate risks in planning and approval processes. Enhancing building codes and urban planning, such as China’s “Sponge City” initiative, can also increase resilience to extreme weather events.
Regulatory developments are also shaping the region’s insurance landscape. New risk-based capital regimes in Hong Kong and climate risk stress tests in Malaysia are enhancing market resilience, while the adoption of advanced technologies such as artificial intelligence and machine learning is helping insurers and reinsurers improve risk evaluation and develop new products.
In the long term, Guy Carpenter advises insurers to integrate climate science data and long-term trend analysis into internal risk models to better predict the frequency of minor losses. Working with commercial model vendors to improve model accuracy is essential, as is making more data publicly available to foster a shared understanding of climate risks across the industry.
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