Resolving Securitizations to the Companies Worth Rating

Many of the names on the agency's input list weren't operating companies at all; they were the deals themselves: securitization trusts and SPVs, which standard matching has nothing to resolve. Veridion resolved each instrument to the operating entities behind it, classified every one by its role, enriched the records, and verified the result against public filings.

1. 1
   Solved for names that aren't companies

   securitization trusts and SPVs that standard matching can't resolve, across 7 asset classes

2. 2
   Mapped 1:many relationships

   each deal resolved to the full network of operating entities behind it in the company knowledge graph

3. 3
   Identified every role

   ~13 role types per structure: parent, investment manager, sponsor, originator, SPV, depositor, loan-seller

4. 4
   Enriched the records

   62 firmographic attributes per entity, across 21 countries and 327 NAICS codes

5. 5
   Verified against filings

   every mapping justified and checked against SEC filings and rating-agency reports

6. 6
   Pinpointed the data source

   for each deal, the one public company whose disclosures you'd pull firmographics and ESG from

When the names on the list aren't companies

The agency rates and surveils structured-finance deals, and its data workflows begin where most do: with a list of entities to match against a reference dataset and enrich. The list arrived looking ordinary: names to be resolved to companies.

But many of those names were not companies. They were the deals themselves: securitization trusts and special-purpose vehicles behind everything from Non-QM RMBS and multi-bank CMBS conduits to aviation and auto ABS, CRE CLOs, and even a stadium-backed French securitization fund. Each is a legal box created to hold assets and issue securities, deliberately ring-fenced from the institutions that built it, so standard company matching has nothing to grab onto, and the instrument either fails to resolve or matches to the wrong thing.

Resolving it is only half the job: to act on a deal, the agency also needs to know which entity behind it carries the disclosures worth pulling credit and ESG data from.

Resolved to the entities behind the deal, by role

Veridion resolved each instrument against its company knowledge graph to the full network of entities behind it, classifying every one by its role, with the taxonomy adapting to the structure rather than forcing a fixed template.

A multi-bank CMBS conduit unrolls into several originating banks, each of their loan-seller subsidiaries, and a separate depositor. A private-equity-owned auto ABS has no single ultimate parent at all, so the mapping separates ownership from advice: the funds that own the originator, the manager that administers them, and the sub-adviser that directs investment yet owns nothing, a distinction naive matching gets wrong.

Each resolved entity was enriched with 62 firmographic attributes, spanning 21 countries and 327 NAICS codes. And for every deal, Veridion flagged the single public company whose disclosures the agency would actually pull firmographic and ESG data from, typically the listed parent or REIT, since the SPV itself discloses nothing.

Every mapping carries a written justification and was verified against SEC filings and rating-agency reports, corrections included, where an unchecked assumption would have named the wrong entity.

Start from a deal, get the companies behind it

The agency can start from a deal name and get back the operating companies behind it: each classified by role, enriched, filing-verified, and with the one to source data from flagged.

Entity resolution no longer breaks at the point where an input stops being a company and becomes a financial instrument, and because every mapping arrives with its reasoning attached, an analyst can audit the structure rather than take it on faith.

The same approach extends to any workflow that begins with a deal or instrument name: rating and surveillance, counterparty diligence, and beneficial-ownership mapping in structured finance.