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Fuzzy Entity Match for KYC Onboarding

Returns the best scoring register candidate with a confidence score when the trading name and the registered name do not match exactly.

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Legal Entity Resolver
Legal Entity Resolvermambalabs/legal-entity-resolver
Domain
Legal Name
Company Number
Company Number Scheme
+23 fields
Text
Number
Boolean
List
Object

Input

Company domain:gong.io
Legal name hint:Monzo Bank Limited
Match strictness:fuzzy

Output fields

Domain
Legal Name
Company Number
Company Number Scheme
Jurisdiction
Entity Status
Entity Type
LEI
LEI Status
VAT Number
VAT Valid
VAT Registered Name
Register Source
Registers Queried
Match Method
Match Confidence
Legal Name Source
Legal Name Candidates
Rejected Candidates
Pages Attempted
Pages Reached
Fetch Status
Fetch Error
Run Date
Row Status
Error Reason
Billable Events

How it works

Sign up on Apify or log in

The Legal Entity Resolver Actor is ready to run with the inputs already set for "Fuzzy Entity Match for KYC Onboarding". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Fuzzy Entity Match for KYC Onboarding" task

The Legal Entity Resolver Actor will start running based on the input automatically. You can also change all the input fields, like company domain, legal name hint, and more, to match your specific use case.

Receive the "Fuzzy Entity Match for KYC Onboarding" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as domain, legal name, company number, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Fuzzy Entity Match for KYC Onboarding" task via API.

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Integrate "Fuzzy Entity Match for KYC Onboarding" into your workflow

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