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Tamping down wildfire threats: How insurers can mitigate risks and losses

Climate risk management is a critical human and business challenge – one that is increasingly visible in the current escalation of the twin perils of wildfire and flooding. In 2021, economic loss due to wildfires was $20 billion in the United States, less than half of those insured, marking the seventh year in a row such losses surpassed $2 billion.

Produced by Capgemini in collaboration with the Insurance Information Institute, this Tamping down wildfire threats report discusses how insurers are poised to aid at-risk communities through pre-emptive mitigation leveraging advanced data technologies and data, and by offering community-based catastrophe insurance programs and other solutions.

Key findings:
• Collaboration - As wildfires are an issue that connects many stakeholders a joint approach is necessary to tackle it. This means partnering with communities to create strategies that focus on proactive risk prevention.
• Advanced tools and technology - Deployment of sophisticated prediction tools and machine learning-based pricing and risk models can enable more accurate risk assessments.
• Insurers as first responders - Although insurers are already on the frontline in catastrophic weather events such as wildfires, more needs to be done to inform public policy to create partnerships that drive change.

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Why data readiness comes before AI in insurance

How can insurers continue to evolve without losing the visibility, accuracy, and confidence needed to operate at scale? This blog highlights why getting the foundations right, including data readiness, holds the key to making AI a genuine accelerator within the insurance industry.

Does your AI accelerate solutions or amplify the status quo?

For most insurers, the question has moved past whether to adopt AI. However, what’s still unresolved is whether the operating model underneath that AI can keep pace with change. This blog highlights why the quality of an insurer’s operating model determines whether AI becomes a genuine accelerant.

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