Read any risk report in 2024 and one thing is clear: climate related risks are more volatile, expensive and fast-moving than ever before. In this scenario, the need for accurate risk prediction and effective risk management has never been more critical. Insurers must navigate a dynamic risk landscape where historical data alone is insufficient, making the integration of advanced technologies such as AI a critical ally for insurance risk engineering processes.
In this post, we explore how the insurance industry can adapt to an evolving climate landscape by leveraging artificial intelligence to mitigate risks and ensure resilience in the face of growing uncertainties.
We’ll look at:
- The Impact of a Changing Climate
- The Impact on Insurers
- Cost Trends
- Underwriting Challenges
- The Protection Gap
- Impact on Human Safety and Business Continuity
- The Challenge for Risk Engineers
- The Value of AI for Risk Engineering for Climate Change
The Impact of a Changing Climate
We don’t have to look far to see how these changes are playing out in our world, for example:
- “Increased coastal flooding this century will put over 70 million people in the path of expanding floodplains”
- Warm, dry conditions are lengthening fire seasons. Following the hottest summer on record last year, Europe has lost more than 460,000 hectares of forest to wildfire already this year.
- Increased rainfall and temperatures are influencing the frequency of earthquakes and volcanic activity.
The Impact on Insurers
Here are some of the ways climate change is impacting insurers:
Cost Trends:
Underwriting Challenges:
The Protection Gap:
Impact on Human Safety and Business Continuity
The Challenge for Risk Engineers
Risk Engineering helps insurers make informed decision-making to establish proper coverage and ultimately reduce and prevent loss. It’s a process designed to provide clarity about all of the factors that could cause damage, injury or loss of property or life. It involves gathering a wide variety of data on the factors that could cause damage loss, including climate forces, human activities and market and operational factors. Key data types include:
- Site surveys and other existing information about a property and related assets
- Weather and natural hazard data on the site, incorporating earthquake, storm and flood footprints
- Reports on criminal activities like theft, vandalism and injuries
Given the volatility of climate-related factors, insurers need the most up to date information to understand the evolving risk landscape.
The Value of AI for Risk Engineering for Climate Change
Risk engineers have always been inundated with information, and today’s complexity has significantly increased the volume, velocity and urgency that goes into reporting. A risk engineer or even a team of engineers cannot manually read every document nor personally inspect every property. Existing digital solutions that simply read text are inadequate for risk engineers because they need to correlate details and cross-reference data across all the sources you’re using for analysis.
This is where the power of AI and its strengths in analyzing and correlating information become critical allies for the risk engineering process. Here are some of the ways that artificial intelligence can help risk engineers address the risks from a changing climate:
1. Leverage all of your information: Take advantage of all of your information—from historical site surveys to the latest natural disaster and climate risk data—to identify risk exposure and areas for further investigation and analysis. By reading and understanding all your available reports and documentation, the expert.ai Insurance Platform allows you to leverage all of your information, eliminating the manual reading and analysis that often results in the majority of risk analysis documents going unread and unincorporated in analysis. Expert.ai technology comprehensively reads and analyzes information on facilities, locations and other climate risk factors with precision, ensuring that nothing is missed.
2. Strengthen forecasting abilities and augment insights: Expert.ai aggregates information by location, providing a comprehensive view across several documents. Each aspect of property is assessed fully and effectively, considering location, occupancy description, construction type and any other protection and/or exposure attributes to illuminate areas that could affect risk exposure, including risk posed by natural catastrophes. The system evaluates every risk qualifier, grades each category individually and compiles an overall risk score (or forecast) that is configured based on your internal scoring approach.
3. Leverage intelligence to identify interconnected risks: Leverage an understanding of interconnected risks to support ESG, sustainability efforts and regulatory compliance. Climate disclosure requirements are evolving rapidly. Starting in 2025, the EU’s Corporate Sustainability Reporting Directive goes into effect for environmental and social reporting for EU member nations and European subsidiaries. California’s Climate Accountability Package will require companies with more than $500M in annual revenues to disclose their climate-related financial risk.
These regulations highlight the wider impact of climate risks to the business strategy and to the larger ecosystem of suppliers, infrastructure and utilities, labor that are critical to an organization’s business and therefore, to the overall risk landscape.
4. Provide mitigation recommendations: Take risk analysis even further by providing risk mitigation suggestions to customers and feedback to business models to help avoid and manage risk.
Conclusion
The integration of AI in the insurance industry is not just a technological advancement but a necessity in the face of escalating climate risks. By leveraging AI, insurers can enhance their risk prediction and management capabilities, addressing the challenges posed by an increasingly volatile climate. AI’s ability to process vast amounts of data, provide accurate forecasts and identify interconnected risks positions insurers to better protect their clients and ensure business continuity. As climate change continues to drive extreme weather events, the adoption of AI will be crucial for insurers to navigate the evolving risk landscape, maintain resilience and deliver sustainable solutions for a safer future.