Climate and Nature Financial Risk
The Global Risks Alliance (GRA)
Climate and nature risks reach insurers, banks and investors through different channels and interact between them. Insurers face higher claims and may withdraw cover; banks then hold uninsured collateral; investors reprice insurers, banks and real assets together. This page sets out how effects differ by sector and feed between them, how they are measured, and who decides.
GRA · In development · service level R0
Climate risk across insurers and banks describes how climate and nature risks reach each financial sector through different channels and feed between them. Insurers reprice annually, banks hold long exposures and investors price expectations. Supervisors, risk functions, boards and governments hold the decisions.
Which places drive loss in a severe year, and how far it reaches into reinsurance. Illustrative design values.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Insurance bank investment effects · Nature-sensitive sectors · LEAP cycle 2
| Agriculture | 3 | High | High | High | High |
| Food processing | 2 | High | Medium | Medium | Medium |
| Mining | 2 | High | Low | Medium | Medium |
| Real estate | 6 | Medium | Low | Low | Low |
Distinct financial-sector transmission. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Insurers renew annually and can raise prices or exit quickly. Their decisions change the risk carried by property owners and lenders.
Mortgages and loans last decades. When insurance becomes unavailable, banks bear physical risk on collateral they cannot easily exit.
Equity and bond prices respond to expected costs and policy. Sudden repricing can affect insurers' and banks' investment portfolios too.
Insurance withdrawal lowers property values, raising bank losses and reducing investor returns. Sector-by-sector analysis misses this loop.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Insurance availability | Whether cover for a risk can be bought in the market at all. |
| Insurance affordability | Whether available cover is priced at a level buyers can pay. |
| Feedback loop | A chain in which an effect in one sector returns to amplify the original change. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Insurance non-renewals in high-risk areas | count | annual | Regulator data | OFFICIAL |
| Mortgages on property without hazard insurance | share of mortgage book | periodic | Bank and supervisory data | REPORTED |
| Insurer investment exposure to carbon-intensive sectors | currency and share | annual | Insurer disclosures | DECLARED |
| Bank exposure to insurers and insured collateral | currency | annual | Supervisory data | OFFICIAL |
| Climate-related losses in investment portfolios under scenarios | percent | per exercise | Scenario analysis | MODELLED |
| Market pricing of climate risk | spread or return difference | periodic | Academic and central bank studies | ESTIMATED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| EIOPA climate stress test reports | Insurer exposure to climate risk | Free, EU reuse terms |
| NAIC climate risk disclosure survey | Insurer climate risk governance and strategy | Free, NAIC terms |
| Federal Insurance Office homeowners insurance data | Premiums, non-renewals and claims by area | Public domain |
| IMF Global Financial Stability Report climate chapters | Cross-sector analysis of climate financial risk | Free, IMF terms |
| NGFS reports on cross-sector transmission | Analysis of interaction between insurance and banking | Free, NGFS terms |
Climate and Nature Financial Risk prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Insurance and banking supervisors | Whether to coordinate monitoring of insurance withdrawal and mortgage risk | Cross-sector data and scenario evidence |
| Bank risk functions | How insurance availability affects collateral risk | Insurance data linked to loan books |
| Insurer boards | How underwriting and investment climate exposures interact | Asset and liability scenario analysis |
| Governments and public pools | Whether to intervene in insurance markets | Availability, affordability and cross-sector evidence |
Property and casualty insurers usually write annual contracts, so they can reprice or withdraw quickly as risk rises; their exposure is to the frequency and severity of claims. Banks hold multi-year loans secured on property and business assets, so falling collateral values and borrower stress accumulate over time. Investors hold securities that reprice as markets reassess risk, sometimes suddenly.
The sectors interact. If insurers withdraw from high-risk areas, uninsured properties may lose value, raising credit risk for banks. Life insurers and pension funds, as long-term investors, face transition risk on the asset side of their balance sheets.
Catastrophe modelling and pricing analysis, with climate and atmospheric science. Models need adjustment for climate change.
Credit risk models incorporating climate effects on probability of default and collateral, using financial economics and macro-finance. Long-horizon effects are hard to fit into existing models.
Portfolio repricing and exposure analysis. Market reactions are hard to predict.
Studying interactions, with scenario design and stress testing. Interaction effects are rarely modelled.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.