High-quality exposure data key to effective nat cat risk management: Verisk
November 4 2024 by InsuranceAsia News
Although nat cat modelling in the Asia Pacific has made significant progress, a key challenge remains – a lack of the availability and quality of exposure data, said Ashish Jain, vice president and managing director of extreme event solutions at Verisk Singapore.
As the region is experiencing rising nat cat losses, driven by several factors, including climate change, inflation and rapid urbanisation, which increases risk exposure as populations are concentrating in cities vulnerable to hazards, it’s critical for insurers to obtain accurate property data and up-to-date replacement values in order to produce reliable loss projections, said Jain.
However, while countries like Australia, New Zealand, and Japan have reliable geocoding and risk data, other markets, including China, India, and South-East Asia, still face gaps.
“Collaboration with insurers in these regions will contribute to better data collection practices, but there is still considerable room for improvement to ensure more accurate risk assessments,” said Jain.
To address these challenges, catastrophe modelers are utilising advanced technology to refine coarse data by distributing exposure to finer geographical resolutions and making informed assumptions about missing risk characteristics, such as construction type, building height, and year of construction.
“Verisk integrates probabilistic modeling techniques to account for uncertainties in incomplete datasets. These innovations improve modeling outcomes, even with limited data availability,” said Jain.
“As an industry, it is essential that we continue to work together, raising awareness about the importance of high-quality exposure data while providing technological solutions that help developing markets overcome these challenges and build long-term resilience.” Ashish Jain, Verisk
For China and India, critical markets due to their size and rapidly increasing insurance penetration, Verisk offers insurers with advanced models for earthquake, typhoon, cyclone and multi-peril crop risks. Regarding flood risk, Verisk has introduced high-resolution probabilistic flood hazard maps for both countries, providing insurers with the tools to better underwrite and quantify flood risks at a granular level.
“Together, these solutions enable the insurance industry to comprehensively evaluate natural catastrophe risks, supporting sustainable growth and resilience in these high-growth markets,” said Jain.
“As an industry, it is essential that we continue to work together, raising awareness about the importance of high-quality exposure data while providing technological solutions that help developing markets overcome these challenges and build long-term resilience,” Jain added.
He also called for insurers to regularly reassess their exposures, especially during periods of high inflation and implement long-term strategies to address the incremental effects of climate change, ensuring that insurance remains affordable and sustainable.
Modelling emerging risks
In addition to nat cat risks, emerging risks, such as political violence and civil unrest, are also in Verisk’s focus. It has developed a global predictive scoring model for strikes, riots, and civil commotion (SRCC), which are human-driven peril with irregular patterns and fewer historical insured losses compared to natural catastrophes
“Recent trends—five SRCC events in the last five years each exceeding US$1 billion in insured losses—highlight the growing need for precise forecasting,” said Shane Latchman, vice president and managing director of Extreme Event Solutions at Verisk London.
“We leverage detailed claims data and large historical datasets of riots, applying machine-learning algorithms to identify socio-economic and political conditions predictive of future unrest.”
By integrating these insights, Verisk could better assess the frequency and severity of SRCC events, helping insurers improve their ability to understand and manage their exposure to this evolving risk.
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