The Global Risks Alliance (GRA)
Underwriting decides which risks an insurer accepts and on what terms; pricing sets the premium that should cover expected losses, expenses, the cost of capital and uncertainty. Both depend on risk factors that predict loss, on data that is often incomplete, and on boundaries set by law and professional standards on what may be used. This page sets out how pricing risk arises, how it is measured, and who holds the decisions.
GRA · Established · service level R0
Underwriting and pricing risk is the risk that the terms and premiums an insurer accepts do not cover the losses, expenses and cost of capital that follow. It arises from rating factors that predict loss imperfectly, incomplete or drifting data, market pressure on price and limits that law and professional standards set on what may be used.
Where a portfolio's assets sit, and how much of its value is most exposed. Hypothetical assets, not an assessment.
Risk factors, data limits and role boundaries. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Rating variables group policyholders by expected loss. A variable can predict well yet be unlawful, unfair or a proxy for a protected characteristic, so classification is a legal and ethical question as well as a statistical one.
Pricing relies on past claims for exposures that change: inflation in repair and medical costs, new building stock, litigation trends, a changing climate. Experience that is too old or too thin misprices the next year.
Competition, distribution costs and the underwriting cycle push charged premiums away from the technical price. The gap between the two is itself a risk, and it becomes visible only when the losses arrive.
Rate filings, prior approval regimes, unfair discrimination rules and fair value obligations constrain what may be charged. Actuaries, underwriters, boards and supervisors each hold a distinct part of the judgment.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Loss ratio | Incurred claims divided by earned premium for a period or a line of business. |
| Combined ratio | The loss ratio plus the expense ratio; below one hundred percent means underwriting income exceeds claims and expenses before investment income. |
| Technical price | The premium that would cover expected loss, expenses, the cost of capital and a margin for uncertainty, before commercial adjustment. |
| Claims inflation | The rise in the average cost of claims over time from prices, wages, repair costs, medical costs and legal awards. |
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 |
|---|---|---|---|---|
| Loss ratio | incurred losses as a percent of earned premium | quarterly | Statutory financial statements | OFFICIAL |
| Combined ratio | losses and expenses as a percent of earned premium | quarterly | Statutory financial statements | OFFICIAL |
| Commercial rate change index | index of renewal rate movement | quarterly | Broker market surveys | REPORTED |
| Technical price adequacy | charged premium over technical premium, ratio | annual, by portfolio | Insurer pricing systems | MODELLED |
| Claims inflation | annual change in average claim cost, percent | annual | Claims records and price indices | ESTIMATED |
| Rate filing outcomes | count of filings approved, modified or withdrawn | annual | Supervisory filing systems | OFFICIAL |
| Actual-to-expected claims ratio | ratio | annual | Experience 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 |
|---|---|---|
| NAIC System for Electronic Rates and Forms Filing (SERFF) public access | Rate and rule filings with supporting actuarial memoranda, by state | Public records, terms per state |
| Marsh Global Insurance Market Index | Commercial insurance rate movement by region and line | Proprietary, published summary free to read |
| Gallagher Re 1st View | Reinsurance renewal pricing and terms at the main renewal dates | Proprietary, published report free to read |
| EIOPA consumer trends report | Pricing practices, fair value and conduct concerns across EU markets | Public, EU reuse terms |
| National statistics offices | Price indices for repair, construction, medical and legal costs | Public, terms per office |
| Casualty Actuarial Society and Society of Actuaries research | Ratemaking methods, experience studies and practice notes | Public research, terms per society |
Insurance Nexus 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 |
|---|---|---|
| Appointed and pricing actuaries | Whether proposed rates are adequate, not excessive and not unfairly discriminatory | Experience data, trend selection and the effect of each rating variable, with the assumptions behind each |
| Insurance supervisors and rate regulators | Whether to approve, modify or disapprove a filing, and how to supervise fair value | Filing evidence read against actuarial standards and conduct rules |
| Underwriting committees | Which risks to accept, at what price and with what terms and exclusions | Technical price against market price, exposure data quality and model limits |
| Legislators and equality bodies | Which rating factors are lawful to use | Evidence on predictive power, proxy effects and the distributional impact of each factor |
Traditional pricing relies on historical loss experience, adjusted for trends and exposures. Actuarial methods estimate expected losses and add loadings for expenses, uncertainty and the cost of capital. For catastrophe risks, where history is short and events rare, insurers use catastrophe models that simulate many possible events. When climate, technology or social change alters risk, historical data becomes less reliable and model uncertainty grows.
Better data allows more granular pricing, which can reward risk reduction but can also make cover unaffordable for high-risk groups and raise concerns about discrimination. Many jurisdictions regulate which factors may be used. Where data is scarce, as in many developing markets, uncertainty leads to higher prices or no cover at all, contributing to protection gaps.
Loss experience studies and pricing methods from actuarial mathematics.
Simulation of hazard, exposure and vulnerability, drawing on extreme value theory and tail risk and climate and atmospheric science.
Comparing models and testing sensitivity to assumptions.
Models embed assumptions about hazards and behaviour, data quality varies widely, and no model captures every source of loss.
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.