The Global Risks Alliance (GRA)
Accumulation is the build-up of exposure to one event across many policies. A single hurricane, earthquake, flood or cyber incident can hit thousands of risks that look unrelated. Accumulation control tracks sums insured and modelled losses by peril and zone, and aggregate covers protect against many events in one year. This page sets out how accumulation develops, how it is measured and controlled, and who decides.
GRA · In development · service level R0
Catastrophe accumulation is the build-up of exposure to a single event across many policies and lines. It arises from concentration in hazardous zones, interaction between lines and contingent losses far from the footprint. Boards, underwriters, supervisors and reinsurance buyers decide how it is controlled.
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.
Aggregate accumulation · Cedent C-07 · Peril: tropical cyclone
| Retention | 0 | 77 | n/a | |
| Layer 1 | 47 | 69 | 9 | 1-in-8 |
| Layer 2 | 122 | 150 | 3 | 1-in-52 |
| Layer 3 | 352 | 274 | 0.9 | 1-in-177 |
Concentrations across regions and perils. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Portfolios concentrate where business is written: coastal cities, seismic zones, floodplains. Growth in one profitable area can quietly raise the loss from one event.
Property, business interruption, marine cargo, motor and life policies can all be hit by one event. Accumulation across lines is harder to see than within one.
Supply chain and contingent business interruption losses arise far from the event footprint, connecting exposures that zone-based controls treat as separate.
Several medium events in one year can cost more than one large one. Aggregate exposure depends on frequency, which is harder to model than severity.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Accumulation | The total exposure that could be affected by one event across a portfolio. |
| Aggregate cover | Protection that responds when total losses over a period exceed a threshold. |
| Contingent business interruption | Loss of income from damage at a supplier or customer's premises rather than the insured's own. |
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 |
|---|---|---|---|---|
| Total sum insured by peril zone | currency | quarterly | Insurer exposure data | REPORTED |
| Modelled loss at realistic disaster scenarios | currency | semi-annual | Lloyd's and company scenario returns | MODELLED |
| Aggregate exceedance probability loss | currency | per model run | Catastrophe model output | MODELLED |
| Contingent business interruption claims share | percent of event losses | per event | Loss studies | ESTIMATED |
| Cross-line accumulation | currency by event scenario | annual | Internal models | MODELLED |
| Catastrophe exposure relative to capital | ratio | annual | Supervisory and rating reports | OFFICIAL |
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 |
|---|---|---|
| Lloyd's Realistic Disaster Scenarios specification | Prescribed scenarios for accumulation reporting | Free to read, Lloyd's terms |
| Solvency II catastrophe risk reporting templates | Catastrophe exposure and capital in EU reporting | Public templates, EU reuse terms |
| Cambridge Centre for Risk Studies scenario reports | Scenarios for accumulation in cyber and other perils | Free to read, terms to check |
| Bermuda Monetary Authority catastrophe risk reports | Aggregated catastrophe exposure of the Bermuda market | Free, BMA terms |
| Verisk PCS and PERILS industry loss data | Industry losses per event for accumulation calibration | Proprietary, licensed |
Reinsurance and Catastrophe 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 |
|---|---|---|
| Boards and chief risk officers | What catastrophe risk appetite to set by peril and region | Accumulation data and modelled losses |
| Underwriters | Whether to write new risks in concentrated zones | Zone accumulation and capacity limits |
| Supervisors | Whether catastrophe exposure is controlled relative to capital | Scenario returns and capital data |
| Reinsurance buyers | Whether to buy occurrence or aggregate protection | Frequency and severity evidence |
Accumulation builds because insured value concentrates where people and economic activity concentrate: cities, coasts, industrial clusters and ports. Growth in property values and development in hazard-prone areas increases exposure even if hazards do not change.
Some accumulations are visible in property data; others are hidden. Contingent business interruption, where a firm suffers losses because a supplier is damaged, can create exposure far from the event. Marine cargo, energy installations and infrastructure may accumulate at ports and hubs.
At market level, many institutions may be exposed to the same peak perils and regions. A single large event can therefore affect much of the market at once, which limits diversification.
Geocoding insured values and overlaying hazard footprints. Exposure data quality is variable.
Deterministic events used to estimate losses, using extreme value analysis to choose severities. Scenarios cover only selected events.
Combining exposures across business lines. Dependencies between lines are uncertain.
Estimating contingent losses from supplier networks. Network data are scarce.
Market-level accumulation is hard to observe because exposure data are held by individual institutions and are competitively sensitive.
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.