Difference between revisions of "Sift (Q1899)"
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(Merged Item from Q2271: merge.js) |
(Removed claim: e-mail address (P17): mailto:privacy@shift.com) |
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(One intermediate revision by the same user not shown) | |||
aliases / en / 0 | aliases / en / 0 | ||
+ | Sift Science | ||
Property / uses | |||
+ | |||
Property / uses: note / rank | |||
+ | Normal rank | ||
Property / uses | |||
+ | |||
Property / uses: score / rank | |||
+ | Normal rank | ||
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 | ||
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 | |||
+ | Normal rank | ||
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) | ||
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 | |||
+ | Normal rank | ||
Property / official website | |||
+ | |||
Property / official website: https://sift.com / rank | |||
+ | Normal rank | ||
Property / has | |||
+ | |||
Property / has: privacy policy / rank | |||
+ | Normal rank | ||
Property / has: privacy policy / qualifier | |||
+ |
Latest revision as of 20:43, 8 August 2021
data broker
- Sift Science
Language | Label | Description | Also known as |
---|---|---|---|
English |
Sift
|
data broker
|
|
Statements
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