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Patent Agency Ranking
公开(公告)号：US10949854B1
公开(公告)日：2021-03-16
申请号：US16540505
申请日：2019-08-14
Inventor： Timothy Kramme , Elizabeth Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L Phillips , Russell Ruestman , Bradley A Craig
Abstract: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.
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公开(公告)号：US10891655B1
公开(公告)日：2021-01-12
申请号：US15498872
申请日：2017-04-27
Inventor： Elizabeth Flowers , Puneit Dua , Alan Zwilling , Adam Mattingly , Melissa Attig , Reena Batra
Abstract: Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) and location may be monitored to predict when a user is near a retail store and the user has not used a particular account in a predetermined amount of time. The techniques disclosed include receiving a location for a user's mobile device, and determining when the mobile device is within a predetermined threshold distance of a retail store. The techniques include building a shopping profile for the user based upon shopping habits for the user. The shopping profile may be used to determine what commercial communications should be transmitted to the user to encourage them to utilize an inactive account to make a purchase at the retail store when the user is within the threshold distance of the retail store.
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公开(公告)号：US10769722B1
公开(公告)日：2020-09-08
申请号：US15495621
申请日：2017-04-24
Inventor： Elizabeth Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
Abstract: A heuristic engine includes capabilities to collect an unstructured data set and a current business context to calculate a credit worthiness score. Providing a heuristic algorithm, executing within the engine, with the data set and the context may allow determination of predicted future contexts and recommend subsequent actions, such as assessing a credit risk of a customer transaction and reducing the risk of customer transactions by processing the available data. Such heuristic algorithms may learn from past data transactions and appropriate correlations with events and available data.
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94.发明授权公开(公告)号：US10733631B2
公开(公告)日：2020-08-04
申请号：US15498828
申请日：2017-04-27
Inventor： Elizabeth Flowers , Puneit Dua , Alan Zwilling , Adam Mattingly , Melissa Attig , Reena Batra
Abstract: Techniques are disclosed utilizing cognitive computing to improve commercial communications from vendors to users. A user's financial account(s) and location may be monitored to determine when a user is within a threshold distance of a vendor. If the user is within the threshold distance the methods and systems disclosed may determine which targeted commercial communications to transmit to the user based upon a shopping profile for the user. The shopping profile may include a dataset indicative of the shopping habits of the user.
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公开(公告)号：US10366300B1
公开(公告)日：2019-07-30
申请号：US16269226
申请日：2019-02-06
Inventor： Elizabeth Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
Abstract: Systems and methods are described for generating an enhanced prediction from a 2D and 3D image-based ensemble model. In various embodiments, a computing device can be configured to obtain one or more sets of 2D and 3D images and to standardize each of the 2D and 3D images to allow for comparison and interoperability. Corresponding 2D3D image pairs can be determined from the standardized 2D and 3D pairs where the 2D and 3D images correspond based on a common attribute, such as a similar timestamp or time value. The enhanced prediction can use separate underlying 2D and 3D prediction models where the 2D and 3D images of a 2D3D pair are each input to the respective underlying 2D and 3D prediction models to generate respective 2D and 3D predict actions.
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