Insurance and actuarial data

Insurance runs on data about risk, and external data increasingly drives pricing, underwriting and capital. This guide covers insurance and actuarial data and how to source it responsibly.

Why insurance data matters

Underwriting, pricing and capital all depend on quantifying risk, which means data: exposure, hazard, behaviour and claims context. External data sharpens each, and climate is reshaping the risk landscape.

The insurance data landscape

• Exposure and asset: what is at risk and where.
• Hazard and catastrophe: peril and climate models.
• Behavioural: telematics and usage data.
• Context: economic, property and health-related data.

Catastrophe and climate

Catastrophe models and climate-risk data are central to pricing and capital, and physical-risk data is increasingly required by regulators. These are geospatial and demand consistent referencing.

Privacy and fairness

Behavioural and health-related data is sensitive, bringing the GDPR (including special-category rules) into scope, and pricing must avoid unfair discrimination. Fairness and explainability are growing expectations.

Sourcing considerations

Model and data methodology vary, and licensing for catastrophe and market data can be restrictive. Personal and sensitive data needs careful handling. Provenance is essential for regulated use.

In a managed model

A managed partner can combine exposure, hazard, behavioural and context data with documented provenance and appropriate privacy safeguards.

Sources & further reading

• EIOPA: insurance data and climate-risk guidance.
• Copernicus and EEA: hazard and climate data.
• EUR-Lex: Regulation (EU) 2016/679 (GDPR).
• Catastrophe-model providers and methodologies.