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    SYSTEMS AND METHODS FOR IDENTIFYING FRAUDULENT COMMON POINT OF PURCHASES
    31.
    发明申请
    SYSTEMS AND METHODS FOR IDENTIFYING FRAUDULENT COMMON POINT OF PURCHASES 审中-公开

    公开(公告)号：US20190188722A1

    公开(公告)日：2019-06-20

    申请号：US15843454

    申请日：2017-12-15

    Applicant: MASTERCARD INTERNATIONAL INCORPORATED

    Inventor： Joshua A. Allbright ,  Christopher John Merz

    IPC: G06Q20/40 ,  G06Q20/34 ,  G06Q20/36 ,  G06F17/30

    CPC classification number: G06Q20/4016 ,  G06F16/2282 ,  G06F16/951 ,  G06F16/955 ,  G06Q20/34 ,  G06Q20/36

    Abstract: A common point of purchase (CPP) system for identifying a common point of purchases involved in fraudulent or unauthorized payment transactions is provided. The CPP system includes a common point of purchase (CPP) computing device that is configured to receive transaction data, store the transaction data in a database, and perform a look up within the database. The CPP computing device is also configured to build a merchant table, receive a card list, and compare a plurality of flagged account identifiers in the card list to account identifiers in the merchant table. The CPP computing device is further configured to retrieve a unique merchant identifier and/or a merchant name identifier associated with the merchant table account identifiers matched with the flagged account identifiers, aggregate the unique merchant identifier using the merchant name identifier, and determine a first number of the flagged account identifiers associated with the merchant name identifier.

    ENHANCED SMART REFRIGERATOR SYSTEMS AND METHODS
    35.
    发明申请
    ENHANCED SMART REFRIGERATOR SYSTEMS AND METHODS 审中-公开
    增强智能制冷系统和方法

    公开(公告)号：US20170032446A1

    公开(公告)日：2017-02-02

    申请号：US15222533

    申请日：2016-07-28

    Applicant: MasterCard International Incorporated

    Inventor： Christopher John Merz ,  Derek Humphreys ,  Oran Cummins ,  Andrea Rizzini ,  Stephen Elder ,  Stephen Toner

    IPC: G06Q30/06 ,  G06F17/30

    CPC classification number: G06Q30/0633 ,  G06F16/24575 ,  G06F16/2477 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0603 ,  G06Q30/0605 ,  G06Q30/0641

    Abstract: An enhanced smart refrigerator (ESR) for automatically populating a virtual shopping cart is provided. The ESR stores a purchase log including a purchase history of a target product. The ESR determines a current interval between a most recent delivery date and a proposed next delivery date based on the purchase history of the target product, and calculates a purchase propensity for the target product based on the current interval and the purchase history of the target product, and automatically adds the product to the virtual shopping cart for submission to a party for purchase of the target product if the purchase propensity meets a first criteria.

    Abstract translation: 提供用于自动填充虚拟购物车的增强型智能冰箱（ESR）。 ESR存储包含目标产品的购买历史的购买日志。 ESR基于目标产品的购买历史来确定最近交货日期和建议的下一个交货日期之间的当前间隔，并且基于目标产品的当前间隔和购买历史来计算目标产品的购买倾向 ，并且如果购买倾向满足第一标准，则自动将产品添加到虚拟购物车以提交给购买目标产品的一方。

    SYSTEM AND METHODS FOR ENHANCED APPROVAL OF A PAYMENT TRANSACTION
    36.
    发明申请
    SYSTEM AND METHODS FOR ENHANCED APPROVAL OF A PAYMENT TRANSACTION 审中-公开
    用于增强付款交易的系统和方法

    公开(公告)号：US20160335639A1

    公开(公告)日：2016-11-17

    申请号：US14711567

    申请日：2015-05-13

    Applicant: MasterCard International Incorporated

    Inventor： Christopher John Merz ,  Johan Gerber ,  Douglas Van Horn ,  Mark B. Wiesman

    IPC: G06Q20/40

    CPC classification number: G06Q20/4016 ,  G06Q20/12

    Abstract: A computer-implemented method for determining a level of confidence that a payment transaction is not fraudulent is provided. The method is implemented using an assurance exchange (AE) computer device in communication with a memory. The method includes receiving authentication data associated with a candidate payment transaction being conducted by a cardholder via a website associated with a merchant from the merchant, storing the authentication data, receiving an authorization request message for the candidate payment transaction from a payment processor, retrieving the authentication data for the candidate payment transaction based on the authorization request message, and calculating an assurance level score based on the authentication data and the authorization request message. The assurance level score represents a level of confidence that the candidate payment transaction is not fraudulent. The method also includes transmitting the authorization request message including the assurance level score to an issuer processor.

    Abstract translation: 提供了一种用于确定支付交易不是欺诈的置信水平的计算机实现的方法。 该方法使用与存储器通信的保证交换（AE）计算机设备来实现。 所述方法包括接收与由持卡人通过与商户相关联的网站从商家进行的候选支付交易相关联的认证数据，存储认证数据，从支付处理器接收候选支付交易的授权请求消息，检索 基于所述授权请求消息的所述候选支付交易的认证数据，以及基于所述认证数据和所述授权请求消息来计算保证级别得分。 保证水平分数表示候选人支付交易不是欺诈性的信心水平。 该方法还包括向发行者处理器发送包括保证等级得分的授权请求消息。

    SYSTEMS AND METHODS FOR DYNAMICALLY UPDATING MODELS USING MACHINE LEARNING
    37.
    发明申请
    SYSTEMS AND METHODS FOR DYNAMICALLY UPDATING MODELS USING MACHINE LEARNING 有权

    公开(公告)号：US20250148470A1

    公开(公告)日：2025-05-08

    申请号：US18501752

    申请日：2023-11-03

    Applicant: MASTERCARD INTERNATIONAL INCORPORATED

    Inventor： Joshua A. Allbright ,  Christopher John Merz

    IPC: G06Q20/40 ,  G06N20/00

    Abstract: A computing system for detecting patterns in data transmitted over a network is provided. The computing system includes a model engine configured to receive an initial dataset including historical data for a first time period, and segment the initial dataset into a plurality of subsets, each subset associated with a second time period smaller than the first time period. The model engine is further configured to train a machine learning model on each subset separately, receive a candidate dataset, analyze the candidate dataset using the trained machine learning model, and assign a score to the candidate dataset based on the analysis. The computing system further includes a rules engine configured to receive the candidate dataset and the corresponding score from the model engine, and generate and output, based at least in part on the score, a decision regarding the candidate dataset.

    GENERATIVE ARTIFICIAL INTELLIGENCE BASED SYSTEMS AND METHODS FOR MERGING NETWORKS OF HETEROGENEOUS DATA WHILE MAINTAINING DATA SECURITY
    38.
    发明申请
    GENERATIVE ARTIFICIAL INTELLIGENCE BASED SYSTEMS AND METHODS FOR MERGING NETWORKS OF HETEROGENEOUS DATA WHILE MAINTAINING DATA SECURITY 有权

    公开(公告)号：US20250045778A1

    公开(公告)日：2025-02-06

    申请号：US18920645

    申请日：2024-10-18

    Applicant: MASTERCARD INTERNATIONAL INCORPORATED

    Inventor： Christopher John Merz

    IPC: G06Q30/02 ,  G06Q30/0251 ,  G06Q30/0601

    Abstract: An artificial intelligence (AI)-based prediction recommender system is provided. The system includes a processor configured to generate a first matrix using a large language merchant transaction model including transaction data associated with a first plurality of users; generate a second matrix using a large language product transaction model including transaction data associated with a second plurality of users; generate a third matrix including transaction data associated with a third plurality of users; generate a preference vector associated with at least one accountholder wherein the preference vector representing historical purchases initiated by the accountholder with a second plurality of merchants; iteratively calculate a propagated activation vector by mathematically combining the first matrix, the second matrix, the third matrix and the preference vector; and output a recommendation associated with the at least one accountholder using the propagated activation vector.

    SYSTEMS AND METHODS FOR INCORPORATING BREACH VELOCITIES INTO FRAUD SCORING MODELS
    39.
    发明公开
    SYSTEMS AND METHODS FOR INCORPORATING BREACH VELOCITIES INTO FRAUD SCORING MODELS 审中-公开

    公开(公告)号：US20240095745A1

    公开(公告)日：2024-03-21

    申请号：US18519877

    申请日：2023-11-27

    Applicant: MASTERCARD INTERNATIONAL INCORPORATED

    Inventor： Joshua A. Allbright ,  Amudhan Venkatesan ,  Felix Johannes Flory ,  Christopher John Merz

    IPC: G06Q20/40 ,  H04L9/40

    CPC classification number: G06Q20/4016 ,  G06Q20/4093 ,  H04L63/10

    Abstract: A method and system for detecting fraudulent network events in a payment card network by incorporating breach velocities into fraud scoring models are provided. A potential compromise event is detected, and payment cards that transacted at a compromised entity associated with the potential compromise event are identified. Subsequent transaction activity for the payment cards is reviewed, and a data structure for the payment cards are generated. The data structure sorts subsequent transaction activity into fraud score range stripes. The data structure is parsed over a plurality of time periods, and at least one cumulative metric is calculated for each of the time periods in each fraud score range stripe. A plurality of ratio striping values are determined, and a set of feature inputs is generated using the ratio striping values. The feature inputs are applied to a scoring model used to score future real-time transactions initiated using the payment cards.

    SYSTEMS AND METHODS FOR GENERATING RECOMMENDATIONS USING A CORPUS OF DATA
    40.
    发明公开
    SYSTEMS AND METHODS FOR GENERATING RECOMMENDATIONS USING A CORPUS OF DATA 审中-公开

    公开(公告)号：US20240037633A1

    公开(公告)日：2024-02-01

    申请号：US18486923

    申请日：2023-10-13

    Applicant: MASTERCARD INTERNATIONAL INCORPORATED

    Inventor： Christopher John Merz ,  Walter F. Lo Faro ,  Peng Yang

    IPC: G06Q30/0601 ,  G06Q30/0251 ,  G06Q30/0282 ,  G06F7/08

    CPC classification number: G06Q30/0631 ,  G06Q30/0255 ,  G06Q30/0282 ,  G06F7/08 ,  G06Q30/0625

    Abstract: A method and system for recommending a merchant are provided. The method includes receiving financial transaction data documenting financial transactions between a plurality of account holders and a plurality of merchants and generating a merchant correspondence matrix that includes the plurality of merchants and a plurality of indicators of interactions associated with pairs of the plurality of merchants. The plurality of indicators of interactions tallying financial transactions conducted by the plurality of account holders at both of the merchants in a pair of the plurality of merchants. The method further includes receiving a query for a recommendation of a merchant from an account holder and generating a ranked list of merchants based on a recommender algorithm. The recommender algorithm inferring user preferences from attributes of the plurality of merchants that were visited by the cardholder.

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