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Case Studies

note

The scenarios below are illustrative walkthroughs built from the catalog's real layers and use-case data — not documented client engagements. They're meant to show how the workflows on the Insurance and Logistics pages play out in practice, not to represent an actual case study.

The Insurance and Logistics pages list the workflows the catalog supports. This page walks through a few of them in more detail — what a real session in the catalog looks like, which layers get combined, and why.

Insurance​

Assessing multi-peril exposure across a property portfolio​

Scenario. A portfolio risk manager needs a consolidated view of hazard exposure for a book of European properties, covering flood, seismic, fire, lightning, and heat risk in one pass rather than sourcing each peril separately.

In the catalog. Starting from Browse Layers, filter by the Hazard category and the countries the portfolio covers. Each of the five perils has its own layer with a consistent technical profile (coverage, resolution, projection), so they can be evaluated side by side before deciding which to pull into a model:

Why it matters. Because every layer follows the same page structure — technical table, interactive map, source — comparing five different perils from five different providers takes minutes, not a separate metadata request per dataset.

Pricing flood risk with authoritative, country-specific data​

Scenario. An underwriter needs flood zone data that matches what a national regulator recognizes, not a generic global model, because pricing and triage decisions have to hold up to regulatory scrutiny.

In the catalog. This is where filtering by country matters more than by peril: official flood zone layers are published per-country, so the right starting point is filtering Browse Layers to the country in question rather than searching by "flood."

Why it matters. The catalog makes the source of each flood layer explicit on its page — which is the difference between a modelled estimate and a nationally-authoritative one, and that distinction is often the whole point when a pricing decision needs to be defensible.

Logistics​

Siting a facility for multi-hazard resilience​

Scenario. Before committing capital to a new warehouse or distribution centre, a logistics team needs to rule out sites with unacceptable exposure to flood, seismic, fire, or landslide risk — ideally by overlaying candidate locations against several hazard layers at once.

In the catalog. Filter to Hazard and the relevant country, then open each candidate layer's map preview to check the site against the hazard extent directly, rather than reasoning from the written description alone:

Why it matters. A site that clears one hazard can still fail on another — the point of pulling all four layers into the same evaluation is catching that before the investment decision, not after.

Assessing critical infrastructure dependencies​

Scenario. A resilience planning team needs to understand what a supply chain actually depends on beyond its own facilities — power, shipping routes, and the physical network beneath both — to evaluate business continuity risk.

In the catalog. This case pulls from Infrastructure rather than Hazard, since the goal is mapping dependencies, not hazard exposure:

Cross-referenced against Global Lightning Hazard to identify where physical infrastructure and hazard exposure overlap.

Why it matters. Supply chain risk isn't only about a company's own sites — it's also about the shared infrastructure everyone's operations quietly depend on, which is easy to overlook without a layer that shows it explicitly.

Looking for the full list of workflows rather than a walkthrough? See the Insurance and Logistics pages. For how to read any individual layer's page, see How to Read a Layer Page.