Introduction

Most conversations about insurance stress start with price. That is understandable: premiums are visible, immediate and politically sensitive. But in many lines of business, price is the last step in a longer chain.

When an insurer cannot reliably distinguish lower‑risk from higher‑risk assets, it has only blunt tools left: broad rate increases, stricter terms, higher deductibles, lower limits, or withdrawal. Those decisions can look like a “pricing problem”. They are often an “information problem” made visible.

Evidence-based analysis

Supervisors are explicit that capability is now the test, not just disclosure. The UK ’s (PRA, 2024) updated climate supervisory statement SS3/19emphasises that climate change and society’s response create financial risks relevant to prudential objectives, that risks are becoming apparent now, and that firms should address information gaps by engaging counterparties or using public/external sources were material. In other words: boards are expected to know what they are exposed to, and to be able to evidence how they know. (PRA,2024).

European supervision points in the same direction. ’s2025 monitoring exercise (EIOPA, 2025) on climate scenarios in the ORSA (Own Risk and Solvency Assessment) reports significant progress but highlights persistent challenges, including limited availability and quality of reliable, granular, standardised data. EIOPA notes that data limitations can drive simplified approaches and qualitative assumptions, affecting reliability and comparability across firms. (EIOPA, 2025).

The international rulebook is converging. The 2025application paper (IAIS, 2025) supports supervisors in integrating climate-related risks into supervision, reinforcing the expectation that climate risks are incorporated into governance and risk management in ways that are proportionate but operational. (IAIS, 2025).

Why data quality drives underwriting and capital

Physical risk losses are shaped by three ingredients: hazard (what the environment does), exposure (what is in the way), and vulnerability (how easily assets are damaged and how quickly they recover). A hazard map alone is not enough. Underwriting becomes decision‑useful only when insurers can link those ingredients at the right spatial resolution. (EIOPA, 2025).

“Granularity” simply means detail. A postcode average is not an asset‑level flood depth profile. A regional wildfire zone is not the same as property‑specific fuel, slope, access and defensible space. When exposure data is coarse or incomplete, firms fall back on proxies that are poor substitutes for observed resilience.

This matters for capital because uncertainty is not symmetric. If an insurer cannot tell whether a portfolio is concentrated in the tail of the loss distribution, the prudent response is to hold more capital, buy more reinsurance, or reduce capacity. That is not because the expected loss necessarily rose; it is because the distribution became harder to defend.

The Financial Stability Institute’s (BIS, 2023) work on the “insurability tipping point” captures the core supervisory concern: where risk becomes difficult to price or transfer, coverage may become unaffordable or unavailable, with implications for financial stability and protection gaps. BIS frames data and disclosure as central to assessing how insurers are responding to climate-related perils. (BIS, 2023).

Concrete examples where the data constraint is visible

First, provides a clear case of data and model governance becoming a board requirement. Lloyd’s 2022 thematic review (Lloyd’s, 2022) on catastrophe modelling and climate change found variation in managing agents’ approaches to representing current climate and managing climate-driven uncertainty. It set explicit requirements, including board discussion of climate change in the “view of risk”, explicit reference to current climate in model validation documentation, and a framework to address current and future climate impacts by region and peril. (Lloyd’s, 2022).

Second, EIOPA’s monitoring exercise is itself a supervisory signal: if firms cannot access reliable, granular, standardised exposure and vulnerability data, their ORSA scenario work risks becoming descriptive rather than controlling. The gap shows up as variability and limited comparability across markets. (EIOPA, 2025).

Third, market availability issues increasingly trigger public intervention, signalling that capacity withdrawal is no longer treated as a purely private matter. In, state law requires a mandatory one-year moratorium on cancellations and non‑renewals in specified areas after a declared wildfire emergency. The moratorium does not “solve” underlying risk, but it is evidence that authorities are already using policy instruments when insurance availability becomes socially and politically destabilising.(California Department of Insurance, 2025).

Finally, industry research is now documenting sustained stress in property insurance affordability and availability. ’s 2025 work(The Geneva Association, 2025) highlights that insured losses from natural catastrophes now regularly exceed USD 100bn annually and links rising losses to both hazard trends and exposure/vulnerability choices, how and where assets are built, and to what standards. It also discusses insurer actions in some markets to limit coverage or withdraw as protection gaps widen. (The Geneva Association,2025).

Decision-relevant implications

For insurers, “data strategy” is now underwriting strategy. A minimum viable insurability dataset is less glamorous than a new model vendor, but often more decisive:

• geospatial locations with documented accuracy and a process for resolving uncertainty;
• core asset attributes relevant to perils (e.g., elevation, construction type, critical equipment location);
• evidence of risk reduction measures and maintenance regimes that can be audited;
• linkage from assets to policy terms (limits, deductibles, endorsements) and concentration reporting;
• model and scenario assumptions documented so boards can approve a defensible “view of risk”. (Lloyd’s, 2022).

EIOPA’s findings suggest that differences in data and simplifications directly affect reliability. Proportionality is appropriate, but it is not a licence for low resolution where exposures are material.(EIOPA, 2025).

For banks and insurers, a new practical lesson is emerging, resilient actions only influence insurance terms if they are auditable. If protection measures cannot be evidenced and mapped, they are unlikely to be priced in. That creates an incentive to treat “insurability evidence” as part of asset management, not as an afterthought during renewals.

Sources

Prudential Regulation Authority (2024) SS3/19 update (PDF):https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/supervisory-statement/2024/ss319-november-2024-update.pdf

EIOPA (2025) Monitoring exercise on climate scenarios in ORSA (PDF):https://www.eiopa.europa.eu/document/download/058569c7-13b9-495e-a82b-9e912bb703d2_en?filename=Public+statement+on+the+monitoring+exercise+on+the+use+of+climate+change+scenarios+in+the+ORSA.pdf

International Association of Insurance Supervisors (2025)Application Paper (PDF):https://www.iais.org/uploads/2025/04/Application-Paper-on-the-supervision-of-climate-related-risks-in-the-insurance-sector.pdf

Bank for International Settlements (2023) Too hot to insure– insurability tipping point (PDF): https://www.bis.org/fsi/publ/insights54.pdf

Lloyd’s (2022) Thematic Review: Catastrophe Modelling &Climate Change (PDF):https://assets.lloyds.com/media/7fc3779d-53cd-4e63-86fb-64238c5525cb/thematic-review-catastrophe-modelling-and-climate-change.pdf

The Geneva Association (2025) Safeguarding Home Insurance(PDF):https://www.genevaassociation.org/sites/default/files/2025-05/safeguarding_home_insurance_140525.pdf

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