UBOs

Our UBO (Ultimate Beneficial Owner) endpoint helps you identify the individuals (or organizations if there are no individuals) who directly or indirectly have ownership in a company.

The default ownership threshold is to include all UBOs with 10% or more ownership, except when the highest ownership is below 10% in which case it is still included.

This endpoint has a limit of 100 UBOs. It will only bring more where there are strictly more than 100 UBOs who are top owners. This is an extremely rare case and it is common to manually review the UBOs in these instances.

How do we do this?

Our algorithms connect ownership across companies within a corporate family to provide a true view of ownership. For example, if Amalie Bates owns 50% of Bricklayers Ltd and Bricklayers Ltd owns 60% of Scaffolding Ltd, then Amalie Bates owns 30% of Scaffolding Ltd.

Data provided from this endpoint includes:

• degreeOfSeparation - the minimum number of steps, between the company and the UBO

• anomalyCount - where problems with the completeness or consistency of UBO data have been identified and their types:

  • ownershipDataConflict - where Persons' of Significant Control (PSC) data and shareholder data do match or when total ownership exceeds 100%
  • ownershipDataIncomplete- where we have not been able to identify the individuals or companies who own a company due to data being unavailable

• detectedCountries - a deduplicated set of countries that have been found along the ownership path between the company and the UBO

Understanding the response

Example response:

{ 
 “countryCode”: “GB”, 
 “companyId”: “06999618", 
 “pagination”: { 
  “offset”: 0, 
  “limit”: 50, 
  “total”: 1 
 }, 
 “ownershipGroupSummary”: { 
  “ownershipDataIncomplete”: false, 
  “ownershipDataConflict”: false, 
  “anomalyCount”: 0 
 }, 
 “ubo”: [ 
  { 
   “Name”: “Peter Damian Kimmelman”, 
   “ownershipSummary”: { 
    “percentageRange”: { 
     “min”: 10, 
     “max”: 15 
    }, 
    “ownershipDataIncomplete”: false, 
    “ownershipDataConflict”: false, 
    “degreeOfSeparation”: 3, 
    “detectedCountries”: [“GB”, “US”] 
   }, 
   “exactMatches”: [ 
    { 
     “type”: “person”, 
     “person”: { 
      “honorific”: “Mr”, 
      “firstName”: “Peter”, 
      “middleName”: “Damian”, 
      “lastName”: “Kimmelman”, 
      “countryOfResidence”: “GB”, 
      “nationalities”: [ 
       { 
        “demonym”: “American”, 
        “countryCode”: “US” 
       } 
      ], 
      “dateOfBirth”: { 
       “year”: 1982, 
       “month”: 10 
      }, 
      “officerId”: “919801033” 
     }, 
     “company”: null 
    } 
   ], 
   “possibleMatches”: [], 
   “notMatched”: null 
  } 
 ] 
} 

The first part of the response is a ownershipGroupSummary. This indicates if there are any anomalies and what types of anomalies they are.

The second part of the response ubo provides the substance of the data. For each UBO identified we provide an owenershipSummary and distinguish between cases where there areexactMatches, possibleMatches and notMatched.

The ownershipSummary provides the ownership percentage as a range. This is because the PSC data we source is provided as a range and that's is sometimes the only available data. Where we can match both the PSC data and Shareholder data, we provide both a range and an exact number. When:

• PSC and Shareholder data does not conflict. e.g. Emma Elliotson owns 25-50% (PSC data) and 32% (shareholder data) then we supply the range as 32% to 32%
• PSC and Shareholder data does conflict e.g. Emma owns 12% rather than 32% (shareholder data) - it will be supplied as 12-50% and will be in the anomaly response.

When the data is complete and the UBO is a person, we match it to an officerID. This enables you to use any of the officer endpoints such as Officer vitals to get richer data on the individual.

What happens if anomalies are detected?

When the anomalyCount is greater than 0, it means that our algorithms have spotted issues in either the completeness or consistency of the data, or both. This typically occurs when the ownership is complex i.e. there are multiple intermediate parents, the group structure goes overseas etc.

If this occurs, then the company needs to be checked against our UBO anomalies endpoint to see the identified anomalous data. This is so that we can clearly mark out cases where we have strong reasons to believe the data we provide is not accurately detecting UBOs, especially in cases where the UBO endpoint is used as part of an automatic process.