Patents by Inventor Eugenia Ho
Eugenia Ho has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10643216Abstract: Systems and methods include: receiving digital event type data that define attributes of a digital event type; receiving digital fraud policy that defines a plurality of digital processing protocols; transmitting via a network the digital event data and the digital fraud policy to a remote digital fraud mitigation platform; using the digital event data to configure a first computing node comprising an events data application program interface or an events data computing server to detect digital events that classify as the digital event type; using digital fraud policy to configure a second computing node comprising a decisioning API or a decisioning computing server to automatically evaluate and automatically select one digital event processing outcome of a plurality of digital event processing outcomes that indicates a disposal of the digital events classified as the digital event type; and implementing a digital threat mitigation application process flow that evaluates digital event data.Type: GrantFiled: March 19, 2019Date of Patent: May 5, 2020Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Micah Wylde, Keren Gu, Eugenia Ho, Noah Grant
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Patent number: 10402828Abstract: Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.Type: GrantFiled: April 10, 2019Date of Patent: September 3, 2019Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Publication number: 20190236610Abstract: Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.Type: ApplicationFiled: April 10, 2019Publication date: August 1, 2019Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Publication number: 20190213595Abstract: Systems and methods include: receiving digital event type data that define attributes of a digital event type; receiving digital fraud policy that defines a plurality of digital processing protocols; transmitting via a network the digital event data and the digital fraud policy to a remote digital fraud mitigation platform; using the digital event data to configure a first computing node comprising an events data application program interface or an events data computing server to detect digital events that classify as the digital event type; using digital fraud policy to configure a second computing node comprising a decisioning API or a decisioning computing server to automatically evaluate and automatically select one digital event processing outcome of a plurality of digital event processing outcomes that indicates a disposal of the digital events classified as the digital event type; and implementing a digital threat mitigation application process flow that evaluates digital event data.Type: ApplicationFiled: March 19, 2019Publication date: July 11, 2019Inventors: Fred Sadaghiani, Micah Wylde, Keren Gu, Eugenia Ho, Noah Grant
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Patent number: 10296912Abstract: Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.Type: GrantFiled: September 21, 2018Date of Patent: May 21, 2019Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Patent number: 10284582Abstract: Systems and methods include: receiving digital event type data that define attributes of a digital event type; receiving digital fraud policy that defines a plurality of digital processing protocols; transmitting via a network the digital event data and the digital fraud policy to a remote digital fraud mitigation platform; using the digital event data to configure a first computing node comprising an events data application program interface or an events data computing server to detect digital events that classify as the digital event type; using digital fraud policy to configure a second computing node comprising a decisioning API or a decisioning computing server to automatically evaluate and automatically select one digital event processing outcome of a plurality of digital event processing outcomes that indicates a disposal of the digital events classified as the digital event type; and implementing a digital threat mitigation application process flow that evaluates digital event data.Type: GrantFiled: March 15, 2018Date of Patent: May 7, 2019Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Micah Wylde, Keren Gu, Eugenia Ho, Noah Grant
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Publication number: 20190034932Abstract: Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.Type: ApplicationFiled: September 21, 2018Publication date: January 31, 2019Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Publication number: 20190020668Abstract: Systems and methods include: receiving digital event type data that define attributes of a digital event type; receiving digital fraud policy that defines a plurality of digital processing protocols; transmitting via a network the digital event data and the digital fraud policy to a remote digital fraud mitigation platform; using the digital event data to configure a first computing node comprising an events data application program interface or an events data computing server to detect digital events that classify as the digital event type; using digital fraud policy to configure a second computing node comprising a decisioning API or a decisioning computing server to automatically evaluate and automatically select one digital event processing outcome of a plurality of digital event processing outcomes that indicates a disposal of the digital events classified as the digital event type; and implementing a digital threat mitigation application process flow that evaluates digital event data.Type: ApplicationFiled: March 15, 2018Publication date: January 17, 2019Inventors: Fred Sadaghiani, Micah Wylde, Keren Gu, Eugenia Ho, Noah Grant
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Patent number: 10108962Abstract: Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.Type: GrantFiled: April 19, 2018Date of Patent: October 23, 2018Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Patent number: 9978067Abstract: Systems and methods include: collecting digital event data from at least one remote source of digital event data; using the collected digital event data as input into primary machine learning ensemble that predicts the likelihood of digital fraud and/or digital abuse; generating by the machine learning system the global digital threat score; identifying a sub-request for a specific digital threat score for a digital abuse type; in response to identifying the sub-request, providing the input of the collected digital event data to a secondary machine learning model ensemble of the machine learning system that predicts a likelihood of the identified digital abuse type; generating by the secondary machine learning ensemble the specific digital threat score for the digital abuse type based on the input of the collected digital event data; and transmitting the global digital threat score and the specific digital threat score for the identified digital abuse type.Type: GrantFiled: July 18, 2017Date of Patent: May 22, 2018Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Keren Gu, Gary Lee, Noah Grant, Eugenia Ho, Doug Beeferman
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Patent number: 9954879Abstract: Systems and methods include: receiving digital event type data that define attributes of a digital event type; receiving digital fraud policy that defines a plurality of digital processing protocols; transmitting via a network the digital event data and the digital fraud policy to a remote digital fraud mitigation platform; using the digital event data to configure a first computing node comprising an events data application program interface or an events data computing server to detect digital events that classify as the digital event type; using digital fraud policy to configure a second computing node comprising a decisioning API or a decisioning computing server to automatically evaluate and automatically select one digital event processing outcome of a plurality of digital event processing outcomes that indicates a disposal of the digital events classified as the digital event type; and implementing a digital threat mitigation application process flow that evaluates digital event data.Type: GrantFiled: July 18, 2017Date of Patent: April 24, 2018Assignee: Sift Science, Inc.Inventors: Fred Sadaghiani, Micah Wylde, Keren Gu, Eugenia Ho, Noah Grant