Risk ratings, sanctions lists and sustainability scores arrive under each provider’s own version of a company name. When they don’t join to your supplier records, the warning exists but nobody sees it.
The adverse rating sits on a record nobody buys from, while orders flow to the supplier it describes.
Supplier risk programs combine your own supplier records with outside data: credit and financial risk ratings, sanctions and watchlists, certifications, sustainability and emissions data. Each source names companies its own way, with legal suffixes, abbreviations and old names.
Exact joins miss most of them. Teams fall back on manual lookups for the top suppliers and accept gaps everywhere else, which is exactly where unmanaged risk tends to be. When a supplier has several internal records, a rating may land on one of them while orders go through another.
Reporting suffers too. Sustainability disclosures need supplier-level data across the whole base, and every unmatched supplier is a gap that has to be estimated or explained.
Adverse ratings or list hits never reach the supplier record buyers use.
Analysts match the top suppliers by hand and leave the long tail unchecked.
Sustainability and risk reports have gaps wherever names did not match.
Resolve your own supplier records into one entity per real company first. Then match each external source to those resolved suppliers, using names, addresses and registration numbers together, so every rating, list entry and score attaches to the right company.
Run it continuously. Outside data changes daily and suppliers change names and ownership, so matching has to keep up instead of being refreshed once a year.
The risk rating and ESG score now sit on the supplier you actually pay.
Your own duplicates are merged before outside data is attached.
External records match even when names, suffixes and formats differ.
New ratings, list updates and supplier changes are matched as they arrive.
Zingg runs as a workload inside your data platform and gives every entity one persistent ZINGG_ID. Everything above it reads the same resolved entities.
The same layer powersCustomer Analytics & MarketingFinancial Crime & RiskPrivacy & ComplianceProduct 360Master Data ManagementAI & Data Foundations
Built-in dictionaries handle abbreviations and legal suffixes across sources. Company name matching
Deterministic rules on registration or tax numbers combine with learned matching where numbers are missing.
Reviewers see the evidence behind each link before acting on a risk flag. Explainability
Risk data and supplier data are matched inside your own data platform.
No. Zingg resolves suppliers and matches them to the risk, sanctions and sustainability data you already license or collect.
Providers name companies differently: legal suffixes, abbreviations, transliterations and former names. An exact join only matches when every character agrees.
Yes. Zingg Enterprise shows the evidence behind each match, so reviewers can check it before acting.
It closes the matching gap. More of your suppliers link to the emissions and certification data you have, so fewer values have to be estimated.
Resolve suppliers and join outside data in your own data platform.