What is entity matching in emissions data?

Without it a Scope 3 total carries duplicates and gaps at the same time: the same company counted three times under three spellings, and a fourth company missed because nobody recognised the trading name. It is the step that has to work before any emissions figure can be attached to anything.

Why is matching companies harder than it sounds?

Because the name in your system was never meant to identify a legal entity. A procurement record holds whatever the person raising the purchase order typed. A holdings file holds the name the custodian uses. Neither matches the name on the annual report that carries the emissions figures. Add the usual complications and a plain name match fails often:

• Trading names, brand names and legal names differ, and emissions get reported under the legal one.
• Large groups have hundreds of subsidiaries, and the one you buy from or lend to may report nothing itself.
• Punctuation, suffixes and abbreviations vary: Ltd, Limited, GmbH, Inc, and every combination of full stops.
• Mergers, renames and divestments mean the correct answer changes over time.
• The same organisation appears in your systems several times, in different regions, spelled differently each time.

Which identifiers help most?

Any stable identifier beats a name. The ones organisations usually already hold, in rough order of how often they resolve cleanly:

• DUNS number, which most procurement and vendor master systems already carry.
• LEI, for counterparties in financial data.
• ISIN, for listed holdings.
• Companies House number or the local registry equivalent.
• Tax ID or VAT number, which finance systems hold even when procurement does not.
• Website domain or email domain, which often resolves the long tail where no registry identifier exists.

Headquarters region and industry are worth sending too. They rarely resolve a match on their own and they break ties, and where no emissions data exists they determine which industry factor gets used.

What happens when there is no identifier?

Matching falls back to a fuzzy match against the reference dataset, scored for confidence. Where confidence is high enough the request resolves to the organisation. Where it is not, the honest answer is to stop rather than guess: the request moves to a waiting state and asks for more input. A wrong match is worse than no match, because a wrong match produces a plausible number that nobody questions.

How are parent and subsidiary organisations handled?

By mapping requests onto the legal entity tree, then letting data cascade down it. If the subsidiary you buy from or hold has disclosed emissions, targets or initiative participation, those are the figures used. If it has not, but a parent in its tree has, the parent's data cascades down to the subsidiary. Data cascades down only, from parent to subsidiary, since one subsidiary's disclosure cannot stand in for a parent's footprint.

An example. A request resolves to a subsidiary that holds no emissions data or revenue of its own, while its ultimate parent holds both. The parent's Scope 1 to 3 upstream emission factor, targets and initiative participation cascade to the request, and the ultimate parent relationship between the two entities is displayed alongside the figure.

Why does matching matter at audit?

Because a reviewer will ask which company a number actually belongs to. Each resolved request shows the requested organisation's legal name, the matching organisation's legal name, and the relationship between the two, such as L2 parent or ultimate parent. A third-party auditor can then see that a subsidiary's figure came from its parent, and decide whether they accept that, rather than discovering it later. A match that is not shown cannot be checked by a reviewer, which is what makes shown matching part of handing over something audit-ready, verified to ISO 14064-3, limited assurance, by UL Solutions.

Is entity matching the same as entity resolution?

The same job under two names. Procurement and data teams tend to say entity matching; methodology and engineering documents tend to say entity resolution. Both describe resolving records from multiple sources to one canonical organisation.

Where does DitchCarbon fit?

DitchCarbon provides verified emissions data for over 2 million organisations, so procurement, sustainability and finance teams can measure and act on supply chain and portfolio emissions from one source. Matching runs as entity resolution against DUNS, LEI and ISIN identifiers, alongside company name, website and email, with a team of 15 analysts behind it.

It is built to take the list you already have, in whichever identifiers you already hold, rather than asking you to clean the data first. Send a supplier list, a vendor master extract or a holdings file, through the web app or the API, and the matched result comes back into the procurement, sustainability or risk systems already in use. Every figure carries its source and change history, and coverage gaps are shown rather than hidden, so the unmatched rows arrive as a work list. See how matching and the calculation work.

Related

• How do you match suppliers to the right legal entity?
• How do legal entity hierarchies affect emissions reporting?
• What is a corporate emissions database?
• What is Scope 3 Category 1 (purchased goods and services)?

Keep getting matched to the wrong entity in someone else's system? Claim your company profile so requests resolve to you rather than to a parent or a namesake. Or send a supplier list or holdings file and see the match rate.

Last reviewed July 2026.