ESG & climate-risk data sourcing for finance and insurance

ESG and climate-risk data has moved from nice-to-have to regulatory necessity for banks, asset managers and insurers. But the market is noisy, methodologies differ, and coverage is uneven. This guide sets out the data types that matter, the EU rules driving demand, and how to source ESG data you can actually rely on.

Available across the EU. DataSupplier sources and delivers this data in all 27 European Union countries — including Germany, France, Spain, Italy, the Netherlands and Poland — and across the EEA, in the format and cadence you need.

Why demand is accelerating

European disclosure and prudential rules increasingly require firms to measure and report environmental and social factors. The Corporate Sustainability Reporting Directive (CSRD), the EU Taxonomy and the Sustainable Finance Disclosure Regulation (SFDR) all create concrete data needs (emissions, taxonomy alignment, principal adverse impacts and more), while supervisors expect climate risk to be embedded in risk management. Reporting obligations are only as good as the underlying data.

The ESG & climate-risk data landscape

• Corporate ESG metrics: emissions (Scope 1, 2 and 3), energy, water, workforce and governance indicators.
• Climate-physical-risk data: flood, drought, heat, wildfire and storm exposure, often geospatial.
• Transition-risk data: carbon intensity, sector pathways and policy exposure.
• Catastrophe and hazard models for insurance underwriting and capital.
• Geospatial and earth-observation layers linking assets to physical hazards.

The data-quality challenge

ESG data is notorious for divergence: different providers score the same company differently, coverage thins for private and smaller entities, and Scope 3 emissions are frequently estimated rather than measured. Sourcing well means understanding methodology, distinguishing reported from modelled values, and being explicit about gaps. Combining multiple sources, and documenting how they were reconciled, usually beats relying on any single score.

Climate risk is geospatial

Physical-risk analysis depends on linking assets to locations and locations to hazards. That requires consistent geospatial referencing and, often, earth-observation inputs such as those from the EU’s Copernicus programme. Harmonising asset registers with hazard layers is a substantial part of the work, and where asset data relates to individuals, privacy rules apply.

Sourcing and delivery considerations

ESG and climate data spans cadences: annual corporate disclosures, periodic model refreshes, and near-real-time hazard alerts. Delivery typically combines analytical formats (Parquet, CSV) for portfolio analysis with APIs for integration into risk systems. Licensing can be restrictive: redistribution and derivative rights matter, especially across group entities, so licence scope should be confirmed before acquisition.

Governance and provenance

Because ESG data feeds regulated disclosures, provenance and auditability are essential. You should be able to evidence where each figure came from, whether it was reported or estimated, and under what licence it is used. Practices aligned with NIS2 and ISO/IEC 27001 principles support the controls supervisors expect.

The main ESG data types in depth

Emissions are reported in three scopes: Scope 1 (direct), Scope 2 (purchased energy) and Scope 3 (value chain). Scope 3 is the hardest, often the largest, and most frequently estimated rather than measured, so always check how a provider derives it. EU Taxonomy data expresses how much of a company’s revenue, capex and opex is aligned with environmentally sustainable activities. SFDR principal adverse impact (PAI) indicators cover a defined set of metrics on emissions, biodiversity, water, waste and social factors. And climate-risk data splits into physical risk (hazard exposure of assets) and transition risk (exposure to policy, technology and market shifts).

Why ESG ratings diverge

It is well documented that ESG ratings from different providers correlate far less than credit ratings do. The reasons are structural: providers disagree on scope (which issues count), measurement (which indicators proxy an issue) and weighting (how issues combine into a score). A company can therefore sit in the top quartile on one provider and the middle on another, with neither being “wrong”. For buyers, the lesson is to treat a single aggregate score with caution, prefer underlying indicators over headline ratings, and document which methodology a decision relied on.

A due-diligence checklist for ESG data

• Coverage: how complete is it for your universe, especially private and smaller entities?
• Reported vs estimated: is each figure disclosed by the company or modelled by the provider?
• Methodology: is it transparent and stable over time?
• Timeliness: how current is it relative to your reporting cycle?
• Licensing: can you use it for the intended disclosure, and redistribute within the group?
• Provenance: can you evidence the source for an audit?

Combining sources beats any single feed

Because no provider is authoritative across every issue and entity, mature ESG sourcing blends sources: a backbone for breadth, specialists for depth on specific issues (emissions, controversies, physical risk), and official or earth-observation data for verification. The work, and the value, is in reconciling them into one defensible view with documented provenance, rather than trusting a single black-box score.

Sources & further reading

• European Commission, Corporate Sustainability Reporting Directive (CSRD) and EU Taxonomy.
• EUR-Lex, Regulation (EU) 2019/2088 (SFDR).
• Copernicus / European Space Agency, Earth observation and climate data services.
• European Environment Agency, climate-risk and hazard data.