We classify structural conditions required for insurability.
Modern risk systems model probability, volatility, loss distributions, and tail exposure. These frameworks assume stable governance, enforceable control, and containable failure modes.
In tightly coupled and AI-mediated systems, those assumptions may not persist. Losses increasingly arise from correlation, opacity, and acceleration rather than discrete failure. Where governance cannot be enforced and failure cannot be contained, insurability becomes conditional.
Focus
Financial systems
AI-driven credit and automation compress decision cycles and erode contestability, attribution, and governance.
Cyber systems
AI-assisted attack and autonomous defence collapse assumptions of containment, recovery, and responsibility.
Critical infrastructure
Utilities and infrastructure become tightly coupled systems where failure propagates faster than governance can respond.
Health systems
AI-assisted care delivery diffuses accountability and shifts liability across institutions, vendors, and systems.
Publications
RealityRe publishes structural notes and briefings for institutional audiences. They are intended to be legible at board level, actionable for CUOs, and defensible in regulatory contexts. Publications avoid disclosure of proprietary methods and focus on structural conditions and signals.
See the Publications index for current notes and forthcoming releases.
Sustainability
Our work is grounded in a commitment to long-term sustainability: environmental, institutional, and societal. Insurability is ultimately a question of whether a future can be responsibly carried forward.
Read the Sustainability statement for how this commitment shapes our framing and priorities.