公开(公告)号：US20200082413A1

公开(公告)日：2020-03-12

申请号：US16567148

申请日：2019-09-11

申请人： MASTERCARD TECHNOLOGIES CANADA ULC

发明人： Yi Wei Tseng ,  Randy Lukashuk ,  Perry McGee ,  Amiran Gigiberia ,  Andrew Giblin ,  Kenny Wan ,  Andrian Sevastyanov

IPC分类号： G06Q30/00

摘要： Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The retrieval of data from the various data sources is optimized based on data dependencies within the rules. By knowing the data dependencies of each rule and utilizing parallelization of rule execution, the retrievals of data from the data sources is achieved efficiently so the rules can be executed quickly.

公开(公告)号：US11531754B2

公开(公告)日：2022-12-20

申请号：US16567352

申请日：2019-09-11

申请人： MASTERCARD TECHNOLOGIES CANADA ULC

发明人： Yi Wei Tseng ,  Randy Lukashuk ,  Perry McGee ,  Amiran Gigiberia ,  Andrew Giblin ,  Kenny Wan ,  Andrian Sevastyanov

IPC分类号： G06F21/56 ,  G06F21/55 ,  G06F8/51 ,  G06Q30/00

摘要： Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The generated rules with distinct data paths are then converted using a transpiler from the scripting language into native language source code (e.g., PHP, Java, etc.) for deployment in a particular environment. The rules are then executed in real-time in the environment to detect potential fraudulent activity.

公开(公告)号：US11645389B2

公开(公告)日：2023-05-09

申请号：US16567148

申请日：2019-09-11

申请人： MASTERCARD TECHNOLOGIES CANADA ULC

发明人： Yi Wei Tseng ,  Randy Lukashuk ,  Perry McGee ,  Amiran Gigiberia ,  Andrew Giblin ,  Kenny Wan ,  Andrian Sevastyanov

IPC分类号： G06F21/55 ,  G06F8/51 ,  G06Q30/00 ,  G06F21/56 ,  G06Q30/018

CPC分类号： G06F21/564 ,  G06F8/51 ,  G06F21/554 ,  G06F21/561 ,  G06Q30/0185

摘要： Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The retrieval of data from the various data sources is optimized based on data dependencies within the rules. By knowing the data dependencies of each rule and utilizing parallelization of rule execution, the retrievals of data from the data sources is achieved efficiently so the rules can be executed quickly.

公开(公告)号：US20200082079A1

公开(公告)日：2020-03-12

申请号：US16567352

申请日：2019-09-11

申请人： MASTERCARD TECHNOLOGIES CANADA ULC

发明人： Yi Wei Tseng ,  Randy Lukashuk ,  Perry McGee ,  Amiran Gigiberia ,  Andrew Giblin ,  Kenny Wan ,  Andrian Sevastyanov

IPC分类号： G06F21/56 ,  G06F8/51 ,  G06F21/55

摘要： Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The generated rules with distinct data paths are then converted using a transpiler from the scripting language into native language source code (e.g., PHP, Java, etc.) for deployment in a particular environment. The rules are then executed in real-time in the environment to detect potential fraudulent activity.