Spatial Finance Hierarchy

Definition

The Spatial Finance Hierarchy is an organizational scheme of data used in Spatial Finance, introduced in and using the concept of nested tiers for spatial finance data.

It comprises of five tiers (Figure 1), running from Tier 0, large scale results (i.e. national scores for sovereign debt insights) to Tier 4, the hyper-detailed results within a specific asset (i.e. smart power meters for specific project finance insights).

Tier 0

Provides insights at a defined geographic area, often at a national level. Aggregating Tier 3 climate and environmental observational data to a defined geographic area, i.e. countries boundaries and associated exclusive economic zones (EEZ).

Tier 1

Provides insights at a portfolio level. An aggregation of Tier 2 data to provide portfolio overviews, allowing users to filter for ‘red flags’, such as any companies within the portfolio with links to deforestation.

Tier 2

Provides insights at a parent company level. An aggregation of Tier 3 and 4 data of the parent company assets and their suppliers assets providing a parent company level analysis and highlighting any red flags attached to any of the company’s assets nd operations.

Tier 3

Provides insights at the asset level. Defined as high-level insights covering the full extent of specific assets, such as an overlap with Protected Areas, species, indigenous areas or insights into the water risk of the site, deforestation, carbon emissions, methane emissions, etc. Tier 4 datasets can be aggregated to provide further insights.

Tier 4

Provides insights at the sub-asset level. Defined as ‘sub-asset measurements’, readings taken from nearby (≤100m) or within the asset itself, often at a high temporal frequency. Examples include air pollution monitors, power smart meters and industry specific measurements such as the genetic profile of timber logs.

See Also

• Credit Risk Hierarchy