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公开(公告)号：US11900383B2
公开(公告)日：2024-02-13
申请号：US17686607
申请日：2022-03-04
发明人： Youxing Qu , Yiwei Cai , Dan Wang , Harishkumar Sundarji Majithiya , Roshni Ann Samuel , Susan Finnegan , Claudia Barcenas , Himanshu Chauhan
CPC分类号： G06Q20/4016 , G06N5/01 , G06Q40/02
摘要： Methods for generating fraud detection rules based on transaction data may include receiving historical transaction data, associating tags with each transaction, generating decision trees having root nodes and child nodes operably connected to the respective root nodes, determining at least one primary rule and at least one set of secondary rules associated with the at least one primary rule based on relationships between features of the transactions, assigning primary rules and sets of secondary rules to the at least one decision tree to populate the tree, extracting a plurality of rule sets including at least one primary rule and one or more secondary rules, determining an ordering of the plurality of rule sets; and determining a subset of rule sets from the ordered plurality of rule sets against which subsequently received transactions are compared against to determine if the subsequent transactions are fraudulent.
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公开(公告)号：US11288674B2
公开(公告)日：2022-03-29
申请号：US16960593
申请日：2019-01-08
发明人： Youxing Qu , Yiwei Cai , Dan Wang , Harishkumar Sundarji Majithiya , Roshni Ann Samuel , Susan Finnegan , Claudia Barcenas , Himanshu Chauhan
摘要： Methods for generating fraud detection rules based on transaction data may include receiving historical transaction data, associating tags with each transaction, generating decision trees having root nodes and child nodes operably connected to the respective root nodes, determining at least one primary rule and at least one set of secondary rules associated with the at least one primary rule based on relationships between features of the transactions, assigning primary rules and sets of secondary rules to the at least one decision tree to populate the tree, extracting a plurality of rule sets including at least one primary rule and one or more secondary rules, determining an ordering of the plurality of rule sets; and determining a subset of rule sets from the ordered plurality of rule sets against which subsequently received transactions are compared against to determine if the subsequent transactions are fraudulent.
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公开(公告)号：US20210209604A1
公开(公告)日：2021-07-08
申请号：US17137524
申请日：2020-12-30
发明人： Liang Wang , Junpeng Wang , Chiranjeet Chetia , Shi Cao , Harishkumar Sundarji Majithiya , Roshni Ann Samuel , Minghua Xu , Wei Zhang , Hao Yang
摘要： Provided is a method for detecting group activities in a network. The method may include receiving interaction data associated with a plurality of interactions. For each account identifier associated with at least one interaction, a value may be determined for each of a first set of categories, and a vector may be generated based on the value for each category. The length of each vector may be determined. At least one relational graph may be generated based on the interaction data. Each relational graph may be associated with a respective category of a second set of categories. At least one cluster of nodes may be determined based on the relational graph(s). A score for each cluster may be determined based on the length of the vector associated with the account identifier of each node of the cluster of nodes. A system and computer program product are also disclosed.
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公开(公告)号：US12118557B2
公开(公告)日：2024-10-15
申请号：US17137524
申请日：2020-12-30
发明人： Liang Wang , Junpeng Wang , Chiranjeet Chetia , Shi Cao , Harishkumar Sundarji Majithiya , Roshni Ann Samuel , Minghua Xu , Wei Zhang , Hao Yang
CPC分类号： G06Q20/4016 , G06F21/552
摘要： Provided is a method for detecting group activities in a network. The method may include receiving interaction data associated with a plurality of interactions. For each account identifier associated with at least one interaction, a value may be determined for each of a first set of categories, and a vector may be generated based on the value for each category. The length of each vector may be determined. At least one relational graph may be generated based on the interaction data. Each relational graph may be associated with a respective category of a second set of categories. At least one cluster of nodes may be determined based on the relational graph(s). A score for each cluster may be determined based on the length of the vector associated with the account identifier of each node of the cluster of nodes. A system and computer program product are also disclosed.
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公开(公告)号：US20220391911A1
公开(公告)日：2022-12-08
申请号：US17686607
申请日：2022-03-04
发明人： Youxing Qu , Yiwei Cai , Dan Wang , Harishkumar Sundarji Majithiya , Roshni Ann Samuel , Susan Finnegan , Claudia Barcenas , Himanshu Chauhan
摘要： Methods for generating fraud detection rules based on transaction data may include receiving historical transaction data, associating tags with each transaction, generating decision trees having root nodes and child nodes operably connected to the respective root nodes, determining at least one primary rule and at least one set of secondary rules associated with the at least one primary rule based on relationships between features of the transactions, assigning primary rules and sets of secondary rules to the at least one decision tree to populate the tree, extracting a plurality of rule sets including at least one primary rule and one or more secondary rules, determining an ordering of the plurality of rule sets; and determining a subset of rule sets from the ordered plurality of rule sets against which subsequently received transactions are compared against to determine if the subsequent transactions are fraudulent.
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