SYSTEMS AND METHODS FOR IDENTIFYING CORRELATED USERS

    公开(公告)号:US20250028056A1

    公开(公告)日:2025-01-23

    申请号:US18355532

    申请日:2023-07-20

    Abstract: A method for identifying correlated users. The method may include: receiving connection data for each of one or more other users; determining a degree of connection of the one or more other users to the first user; receiving query information from one or more electronic devices associated with the first user; receiving authentication information for each of the one or more other users; determining a destination of the first user based on the query information; determining one or more other user destinations for the one or more other users; identifying one or more correlated other users from the one or more other users by comparing the destination of the first user with user destinations of the one or more other users and further based on the degree of connection of the one or more other users; and providing the identified one or more correlated other users to the first user.

    UPDATING A MACHINE LEARNING FRAUD MODEL BASED ON THIRD PARTY TRANSACTION INFORMATION

    公开(公告)号:US20240257137A1

    公开(公告)日:2024-08-01

    申请号:US18629204

    申请日:2024-04-08

    CPC classification number: G06Q20/4016 G06N20/00

    Abstract: A device receives first transaction information associated with a first transaction, and a first transaction account utilized for the first transaction and associated with a first financial institution. The device determines, based on a fraud model, that the first transaction is to be denied due to potential fraud associated with the first transaction account and receives second transaction information associated with a second transaction, and a second transaction account utilized for the second transaction and associated with a second financial institution. The device processes the first transaction information and the second transaction information, with a matching model, to determine whether the first transaction information matches the second transaction information and determines that the first transaction was incorrectly denied when the first transaction information matches the second transaction information within a predetermined threshold. The device performs one or more actions based on determining that the first transaction was incorrectly denied.

    METHODS AND ARRANGEMENTS FOR A PAYMENT INSTRUMENT WITH A UNIQUE DESIGN

    公开(公告)号:US20240232857A1

    公开(公告)日:2024-07-11

    申请号:US18616950

    申请日:2024-03-26

    CPC classification number: G06Q20/355 G06Q20/20 G06Q20/4016

    Abstract: A payment instrument comprising a bottom layer; one or more intermediate layers, wherein at least one of the one or more intermediate layers comprises: a chip comprising a processor and memory; an antenna coupled with the chip; an absorbent medium; and one or more reservoirs comprising beads, each of the beads comprising dyes of one or more colors, the beads configured to release the dyes onto the absorption medium. The dyes cure on the absorption medium at a rate based on a curing agent applied to the absorbent medium or included in beads of the reservoirs. The payment instrument may also comprise a top layer having at least a partially translucent portion above the absorption medium, wherein the absorption medium is at least partially visible through the at least one partially translucent portion.

    PROACTIVELY DETECTING AND PREDICTING POTENTIAL BREAKAGE OR SUPPORT ISSUES FOR IMPENDING CODE CHANGES

    公开(公告)号:US20240152784A1

    公开(公告)日:2024-05-09

    申请号:US18415833

    申请日:2024-01-18

    CPC classification number: G06N5/04 G06F8/77 G06N5/022 G06F8/65

    Abstract: In some implementations, a regression prediction platform may obtain one or more feature sets related to an impending code change, wherein the one or more feature sets may include one or more features related to historical code quality for a developer associated with the impending code change or a quality of a development session associated with the impending code change. The regression prediction platform may provide the one or more feature sets to a machine learning model trained to predict a risk associated with deploying the impending code change based on a probability that deploying the impending code change will cause breakage after deployment and/or a probability that the impending code change will cause support issues after deployment. The regression prediction platform may generate one or more recommended actions related to the impending code change based on the risk associated with deploying the impending code change.

    STORING AND RETRIEVING DATA BASED ON EXPERIENCE IN CATEGORIES ASSOCIATED WITH HISTORICAL INTERACTIONS

    公开(公告)号:US20240135017A1

    公开(公告)日:2024-04-25

    申请号:US18049126

    申请日:2022-10-23

    CPC classification number: G06F21/6218

    Abstract: In some implementations, a system may receive interaction data corresponding to an interaction associated with a particular user of a plurality of users. The system may determine, based on the interaction data, one or more interaction categories associated with the interaction. The system may store the interaction data as historical interaction data associated with historical interactions of the particular user. The system may determine, based on the historical interaction data, experience statuses associated with the particular user in at least a subset of the plurality of categories. The system may receive, from a user device of the particular user, review data indicating a review associated with a historical interaction of the particular user. The system may store the review as historical review data. The review may be associated with one or more experience statuses of the particular user in the one or more interaction categories associated with the historical interaction.

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