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公开(公告)号：US11727407B2
公开(公告)日：2023-08-15
申请号：US17151523
申请日：2021-01-18
CPC分类号： G06Q20/4016 , G06Q20/10
摘要： An inverse recommender system for detecting out-of-pattern payment transactions includes a memory device and a processor programmed to receive transaction data. The transaction data corresponds to historical payment transactions between account holders and merchants. The processor is programmed to generate a merchant correspondence matrix including the merchants and counters indicating the number of historical payment transactions between merchant pairs of the merchants and the account holders. The processor is programmed to store the merchant correspondence matrix in a memory device linking the merchant pairs to each account holder. The processor receives additional transaction data associated with a new payment transaction between an account holder and a merchant, and to generate an inverse recommender score for the new payment transaction based on the account holder's historical payment transaction data. The account holder's historical payment transaction data includes historical payment transaction data associated with the merchants visited by the account holder.
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公开(公告)号：US11715106B2
公开(公告)日：2023-08-01
申请号：US16837838
申请日：2020-04-01
发明人： Joshua A. Allbright
IPC分类号： G06Q20/40 , G06F7/08 , G06F16/23 , G06N20/00 , G06N5/04 , G06Q30/0204 , G06Q30/018
CPC分类号： G06Q20/4016 , G06F7/08 , G06F16/2379 , G06N5/04 , G06N20/00 , G06Q30/0204 , G06Q30/018
摘要： A message tracking computing device for identifying anomalous activity in real-time is provided. The message tracking computing device is programmed to receive real-time transaction data including a plurality of transaction records. Each transaction record associated with a payment transaction. The message tracking computing device is also programmed to sort the plurality of transaction records into a plurality of channels. The message tracking computing device is further programmed to compute, for each channel, a normalized velocity score by computing a streaming mean, computing a streaming standard deviation, and computing the normalized velocity score based on the streaming mean, the streaming standard deviation, and a transaction ratio. In addition, the message tracking computing device is programmed to analyze the computed normalized velocity score for each channel to detect anomalous activity, automatically generate an alert message identifying the anomalous activity, and transmit the alert message to a remote computing device.
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公开(公告)号：US11521211B2
公开(公告)日：2022-12-06
申请号：US16235529
申请日：2018-12-28
摘要： 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.
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公开(公告)号：US20210312451A1
公开(公告)日：2021-10-07
申请号：US16837686
申请日：2020-04-01
摘要： Described herein are systems and methods for classifying incoming payment transactions. A fraud classification computing system includes a historical transaction database for storing a plurality of transaction records associated with a respective plurality of historical transactions. The fraud classification computing system receives a current transaction request message associated with a current payment transaction. The fraud classification computing system applies a multi-class fraud prediction model to the current transaction request message to generate scores indicating a relative likelihood that the current payment transaction is each of a plurality of fraudulent transaction types. The fraud classification computing system identifies a most likely transaction classification identifier and generates a transaction classification message for the current payment transaction.
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公开(公告)号：US20200211020A1
公开(公告)日：2020-07-02
申请号：US16235074
申请日：2018-12-28
摘要： A method and system for detecting fraudulent network events in a payment card network are provided. A plurality of scored payment card transaction authorization requests are received, originating from a plurality of merchants, and data structures for each of a plurality of merchant groups are generated. Each data structure sorts the scored authorization requests into fraud score range stripes. The data structures are parsed over a plurality of time periods, and at least one cumulative metric is calculated for each merchant group for each of the time periods in each fraud score range stripe. A plurality of ratio striping values is determined for each merchant group, and a set of feature inputs is generated using the ratio striping values. A second fraud detection model is applied to the scored authorization requests. Parameters of the second fraud detection model are configured to change based on the generated set of feature inputs.
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公开(公告)号：US20190130403A1
公开(公告)日：2019-05-02
申请号：US15794768
申请日：2017-10-26
摘要： An inverse recommender system for detecting out-of-pattern payment transactions includes a memory device and a processor programmed to receive transaction data. The transaction data corresponds to historical payment transactions between account holders and merchants. The processor is programmed to generate a merchant correspondence matrix including the merchants and counters indicating the number of historical payment transactions between merchant pairs of the merchants and the account holders. The processor is programmed to store the merchant correspondence matrix in a memory device linking the merchant pairs to each account holder. The processor receives additional transaction data associated with a new payment transaction between an account holder and a merchant, and to generate an inverse recommender score for the new payment transaction based on the account holder's historical payment transaction data. The account holder's historical payment transaction data includes historical payment transaction data associated with the merchants visited by the account holder.
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公开(公告)号：US20240095745A1
公开(公告)日：2024-03-21
申请号：US18519877
申请日：2023-11-27
CPC分类号： G06Q20/4016 , G06Q20/4093 , H04L63/10
摘要： 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.
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公开(公告)号：US11631083B2
公开(公告)日：2023-04-18
申请号：US17328832
申请日：2021-05-24
IPC分类号： G06Q20/40 , G06Q20/34 , G06Q20/36 , G06F16/951 , G06F16/955 , G06F16/22 , G06F16/903
摘要： 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.
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公开(公告)号：US20230101117A1
公开(公告)日：2023-03-30
申请号：US18061813
申请日：2022-12-05
摘要： 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.
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公开(公告)号：US11151569B2
公开(公告)日：2021-10-19
申请号：US16235041
申请日：2018-12-28
摘要： A method and system for detecting fraudulent network events in a payment card network are provided. A plurality of scored payment card transaction authorization requests are received, originating from a plurality of merchants, and at least one data structure is generated. The data structure sorts the scored authorization requests 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 is determined, and a set of feature inputs is generated using the ratio striping values. A second fraud detection model is applied to the scored authorization requests. Parameters of the second fraud detection model are configured to change based on the generated set of feature inputs.
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