Difference between revisions of "Sift (Q1899)"

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(‎Created claim: instance of (P3): data broker (Q522))
(‎Removed claim: e-mail address (P17): mailto:privacy@shift.com)
 
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aliases / en / 0aliases / en / 0
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Sift Science
Property / instance of
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Property / instance of: company / rank
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Normal rank
Property / instance of
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Property / instance of: data controller / rank
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Normal rank
Property / e-mail address
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Property / e-mail address: mailto:privacy@sift.com / rank
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Normal rank
Property / uses
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Property / uses: note / rank
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Normal rank
Property / uses
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Property / uses: score / rank
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Normal rank
Property / comment
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A Sift Score is a number between 0 and 100 that indicates the riskiness of an action. The lower the score, the less likely the event is high risk
Property / comment: A Sift Score is a number between 0 and 100 that indicates the riskiness of an action. The lower the score, the less likely the event is high risk / rank
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Normal rank
Property / comment
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We then process the Customer Data through our cloud-based machine learning platform to return a relative fraud score which is a numerical indicator of the likelihood of fraud or illegal activity for a particular event on the Customer Site (e.g., a purchase transaction, the posting of content, creation of a profile)
Property / comment: We then process the Customer Data through our cloud-based machine learning platform to return a relative fraud score which is a numerical indicator of the likelihood of fraud or illegal activity for a particular event on the Customer Site (e.g., a purchase transaction, the posting of content, creation of a profile) / rank
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Normal rank
Property / official website
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Property / official website: https://sift.com / rank
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Normal rank
Property / has
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Property / has: privacy policy / rank
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Normal rank
Property / has: privacy policy / qualifier
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Latest revision as of 20:43, 8 August 2021

data broker
  • Sift Science
Language Label Description Also known as
English
Sift
data broker
  • Sift Science

Statements

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A Sift Score is a number between 0 and 100 that indicates the riskiness of an action. The lower the score, the less likely the event is high risk
0 references
We then process the Customer Data through our cloud-based machine learning platform to return a relative fraud score which is a numerical indicator of the likelihood of fraud or illegal activity for a particular event on the Customer Site (e.g., a purchase transaction, the posting of content, creation of a profile)
0 references