The stakeholder response
Key Takeaways
Summary
Addressing the scale, accumulation and uncertainty of the capex super-cycle will require insurance markets to adapt, including through better risk quantification, data sharing and accumulation management.
Good to know
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The capex super-cycle's risks
underscore need for better data sharing
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Syndication can bundle capacity
from multiple carriers to achieve scale
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Lender expectations
should be aligned with insurance market capacity
The massive infrastructure boom emerging from the capex super-cycle is creating risks that are large, concentrated and interconnected. Individual assets represent investments of tens of billions of dollars, with failures potentially amplified through shared power, digital and supply-chain dependencies.
The technological novelty that comes with this transformation may initially leave insurers without historical loss data with which to assess these exposures and price risk. Addressing this combination of scale, accumulation and uncertainty demands that insurance markets adapt.
Insurers, asset owners, investors and policymakers looking to create the conditions to foster resilient, high-capacity insurance markets may want to focus on key priorities:
- Improving risk quantification: Engineering surveys, commissioning data, operational telemetry, digital twins and continuous monitoring can all help build underwriting datasets where historical claims experience is limited. Even before loss history matures, greater investment in risk engineering and analytical tools can accelerate learning and attract capacity.
- Improving data sharing: Secure mechanisms that allow engineering and operational data to be shared with insurers and reinsurers will help free up capacity needed to advance projects. Better information can reduce underwriting uncertainty and improve risk assessment, accumulation management and capital allocation.
- Managing accumulation and maximum loss: To better understand the dimensions of risk linked to these projects, better accumulation models that can capture dependencies across interconnected AI and energy systems are needed. Clear visibility of correlated exposures supports more efficient deployment of insurance and reinsurance capacity.
- Integrating risk mitigation early in design: Resilience should be built into projects from the outset through recognised engineering standards, redundancy, and tested contingency plans. By mitigating dependency risks and probable maximum losses (PML), asset owners can improve insurability and enable insurers to offer greater capacity on terms that are sustainable.
- Aligning lender expectations with insurance market capacity: The approach to protecting large-scale infrastructure assets that is now standard practice in the petrochemicals, power generation and offshore energy sectors offers a path to greater insurability for modern AI infrastructure and advanced manufacturing. This includes insurance programmes designed around PML rather than full replacement value, with layered placements reflecting available market capacity and realistic loss scenarios.