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公开(公告)号：US10289938B1
公开(公告)日：2019-05-14
申请号：US15596155
申请日：2017-05-16
Inventor： Elizabeth Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
Abstract: Systems and methods are described for generating an image-based prediction model, where a computing device may obtain a set 3D images from a 3D image data source. Each of the 3D images can have 3D point cloud data and a Distification technique can be applied to the 3D point cloud data of each 3D image to generate output feature vector(s). The output feature vector(s) may then be used to train and generate the image-based prediction model.
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公开(公告)号：US10262226B1
公开(公告)日：2019-04-16
申请号：US15596189
申请日：2017-05-16
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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公开(公告)号：US20250166044A1
公开(公告)日：2025-05-22
申请号：US19026038
申请日：2025-01-16
Inventor： Elizabeth Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
IPC: G06Q30/0601 , G06F40/30 , G06N3/006 , G06N5/01 , G06N5/04 , G06N20/00 , G06Q10/0631 , G06Q20/04 , G06Q20/24 , G06Q20/40 , G06Q30/01 , G06Q30/016 , G06Q30/018 , G06Q40/02 , G06Q40/03 , G06Q40/12 , H04M3/22 , H04M3/51 , H04W12/08
Abstract: A heuristic money laundering detection engine includes capabilities to collect an unstructured data set, such as a transaction record, and detect indications of money laundering activity. By detecting money laundering activity and feeding back indications of money laundering transactions, the heuristic algorithm may continue to learn and improve detection accuracy. Such indications may include correlations to sets of transaction activity among a number of financial accounts and past indications of money laundering activity. Indications of money laundering may allow generation of audit reports for reporting to regulatory authorities.
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公开(公告)号：US12229816B2
公开(公告)日：2025-02-18
申请号：US18071380
申请日：2022-11-29
Inventor： Elizabeth A. Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
IPC: G06Q30/0601 , G06F40/30 , G06N3/006 , G06N5/01 , G06N5/04 , G06N20/00 , G06Q10/0631 , G06Q20/04 , G06Q20/24 , G06Q20/40 , G06Q30/01 , G06Q30/018 , G06Q40/02 , G06Q40/03 , G06Q40/12 , H04M3/22 , H04M3/51 , H04W12/08 , G06Q30/016
Abstract: A heuristic engine includes capabilities to collect an unstructured data set and detect instances of transaction fraud in a financial account. By providing a heuristic algorithm with unstructured transaction sets and indications of particular instances of transactions that correlate with past fraudulent activity allows prevention of future occurrences of fraud. Such heuristic algorithms may learn from past indications of fraudulent activity and improve accuracy of detection of future fraud detections.
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公开(公告)号：US20240370875A1
公开(公告)日：2024-11-07
申请号：US18775926
申请日：2024-07-17
Inventor： Timothy Kramme , Elizabeth Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L. Phillips , Russell Ruestman , Bradley A. Craig
IPC: G06Q20/40 , G06N5/046 , G06N20/00 , G06Q20/10 , G06Q20/20 , G06Q20/24 , G06Q20/32 , G06Q20/34 , G06Q30/018 , G06Q30/0207 , G06Q30/0241
Abstract: A method of detecting whether electronic fraud alerts are false positives includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that determines whether to generate an electronic fraud alert for the financial transaction based upon the data, and, when an electronic fraud alert is generated, inputting the data into a machine learning program trained to identify one or more facts indicated by the data. The method may also include determining whether the identified facts can be verified by customer data and, in response to determining that the facts can be verified, retrieving or receiving first customer data. The method may further include verifying that the electronic fraud alert is not a false positive based upon analysis of the first customer data, and transmitting the verified electronic fraud alert to a mobile device of the customer to alert the customer to fraudulent activity.
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Patent Agency Ranking
公开(公告)号：US20240303664A1
公开(公告)日：2024-09-12
申请号：US18669968
申请日：2024-05-21
Inventor： Timothy Kramme , Elizabeth Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L. Phillips , Russell Ruestman , Bradley A. Craig
IPC: G06Q20/40 , G06Q20/20 , G06V30/194 , G06V30/41
CPC classification number: G06Q20/4016 , G06Q20/20 , G06V30/194 , G06V30/41
Abstract: In a computer-implemented method of facilitating detection of document-related fraud, fraudulent document detection rules may be generated or updated by training a machine learning program using image data corresponding to physical documents, and fraud determinations corresponding to the documents. The documents and fraudulent document detection rules may correspond to a first type of document. Image data corresponding to an image of one of the physical documents may be received, where the physical document corresponds to the first type of document. By applying the fraudulent document detection rules to the image data, it may be determined that the physical document is, or may be, fraudulent. An indication of whether the physical document is, or may be, fraudulent may be displayed to one or more people via one or more respective computing device user interfaces.
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公开(公告)号：US20240265405A1
公开(公告)日：2024-08-08
申请号：US18636886
申请日：2024-04-16
Inventor： Timothy Kramme , Elizabeth A. Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L. Phillips , Russell Ruestman , Bradley A. Craig
IPC: G06Q30/018 , G06N5/046 , G06N20/00 , G06Q20/10 , G06Q20/20 , G06Q20/24 , G06Q20/32 , G06Q20/34 , G06Q20/40 , G06Q30/0207 , G06Q30/0241
CPC classification number: G06Q30/0185 , G06N5/046 , G06N20/00 , G06Q20/102 , G06Q20/20 , G06Q20/24 , G06Q20/3224 , G06Q20/34 , G06Q20/401 , G06Q20/4016 , G06Q20/407 , G06Q20/409 , G06Q30/0225 , G06Q30/0248
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：US12020307B2
公开(公告)日：2024-06-25
申请号：US17900795
申请日：2022-08-31
Inventor： Elizabeth A. Flowers , Puneit Dua , Eric Balota , Shanna L. Phillips
IPC: G06Q30/0601 , G06F40/30 , G06N3/006 , G06N5/01 , G06N5/04 , G06N20/00 , G06Q10/0631 , G06Q20/04 , G06Q20/24 , G06Q20/40 , G06Q30/01 , G06Q30/018 , G06Q40/02 , G06Q40/03 , G06Q40/12 , H04M3/22 , H04M3/51 , H04W12/08 , G06Q30/016
CPC classification number: G06Q30/0631 , G06F40/30 , G06N3/006 , G06N5/01 , G06N5/04 , G06N20/00 , G06Q10/06315 , G06Q10/06316 , G06Q20/042 , G06Q20/24 , G06Q20/4016 , G06Q30/01 , G06Q30/018 , G06Q40/02 , G06Q40/03 , G06Q40/12 , H04M3/2218 , H04M3/5175 , H04M3/5191 , H04W12/08 , G06Q30/016 , H04M2203/403
Abstract: A heuristic engine includes capabilities to collect an unstructured data set, including document image data and correlate the image data with known valid data to detect document fraud. Notifications of fraud detection may include particular signature images, or characteristics of a document image. By feeding back indications of document fraud with correlations to past instances of fraud into the heuristic algorithm, the algorithm may learn and improve in fraud detection accuracy.
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公开(公告)号：US11978064B2
公开(公告)日：2024-05-07
申请号：US17745541
申请日：2022-05-16
Inventor： Timothy Kramme , Elizabeth A. Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L. Phillips , Russell Ruestman , Bradley A. Craig
IPC: G06Q30/018 , G06N5/046 , G06N20/00 , G06Q20/10 , G06Q20/20 , G06Q20/24 , G06Q20/32 , G06Q20/34 , G06Q20/40 , G06Q30/0207 , G06Q30/0241
CPC classification number: G06Q30/0185 , G06N5/046 , G06N20/00 , G06Q20/102 , G06Q20/20 , G06Q20/24 , G06Q20/3224 , G06Q20/34 , G06Q20/401 , G06Q20/4016 , G06Q20/407 , G06Q20/409 , G06Q30/0225 , G06Q30/0248
Abstract: In a computer-implemented method of using customer data to determine that geolocation-based fraud alerts are false positives, it may be determined that an electronic fraud alert is a geolocation-based alert generated based upon an unexpected or abnormal transaction location. In response, customer data may be obtained from two or more sources via radio frequency links. It may then be determined that the customer data from the sources indicates that a customer is traveling. In response, it may be determined that a customer location indicated by the customer data corresponds to the transaction location. In response to determining that the customer location corresponds to the transaction location, the electronic fraud alert may be marked as a false positive, and the electronic fraud alert may be prevented from being transmitted to a mobile device of the customer, in order to reduce an amount of false positives that are transmitted to customers.
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公开(公告)号：US20230394500A1
公开(公告)日：2023-12-07
申请号：US18222199
申请日：2023-07-14
Inventor： Timothy Kramme , Elizabeth Flowers , Reena Batra , Miriam Valero , Puneit Dua , Shanna L. Phillips , Russell Ruestman , Bradley A. Craig
IPC: G06Q30/018 , G06N5/046 , G06N20/00 , G06Q20/10 , G06Q20/20 , G06Q20/24 , G06Q20/34 , G06Q20/40 , G06Q30/0207 , G06Q20/32
CPC classification number: G06Q30/0185 , G06N5/046 , G06N20/00 , G06Q20/102 , G06Q20/20 , G06Q20/24 , G06Q20/34 , G06Q20/401 , G06Q20/407 , G06Q20/409 , G06Q20/4016 , G06Q30/0225 , G06Q20/3224 , G06Q30/0248
Abstract: A method of using browsing activity to identify fraudulent online or virtual applications includes receiving a virtual application over one or more radio frequency links, determining an applicant name on the virtual application, determining an IP address of a source computer from which the virtual application originated, determining an online browsing or search history associated with the IP address, determining whether the online browsing or search history indicates recent Internet searches for the applicant name, and, in response to determining that the online browsing or search history does indicate recent Internet searches for the applicant name, flagging the virtual application as fraudulent and generating an electronic alert indicating that the virtual application is fraudulent to facilitate identifying fraudulent virtual applications for goods or services.
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