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公开(公告)号：US07788195B1
公开(公告)日：2010-08-31
申请号：US11691260
申请日：2007-03-26
CPC分类号： G06N99/005
摘要： Systems and methods for performing fraud detection. As an example, a system and method can be configured to build a set of predictive models to predict credit card or debit card fraud. A first predictive model is trained using a set of training data. A partitioning criterion is used to determine how to partition the training data into partitions. Another predictive model is trained using at least one of the partitions of training data in order to generate a second predictive model. The predictive models are combined for use in predicting credit card or debit card fraud.
摘要翻译： 用于执行欺诈检测的系统和方法。 作为示例，系统和方法可以被配置为构建一组预测模型以预测信用卡或借记卡欺诈。 使用一组训练数据训练第一预测模型。 分区标准用于确定如何将训练数据分割成分区。 使用训练数据的至少一个分区来训练另一个预测模型，以便产生第二预测模型。 预测模型合并用于预测信用卡或借记卡欺诈。
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2.发明授权Computer-implemented data storage systems and methods for use with predictive model systems 有权计算机实现的数据存储系统和与预测模型系统一起使用的方法公开(公告)号：US07912773B1
公开(公告)日：2011-03-22
申请号：US11691277
申请日：2007-03-26
IPC分类号： G06Q40/00
CPC分类号： G06Q40/025 , G06Q10/04 , G06Q20/4016 , G06Q30/0185 , G06Q30/0202 , G06Q30/06 , G06Q40/00 , G06Q40/02 , G06Q40/06 , G06Q40/12
摘要： Systems and methods for performing fraud detection. As an example, a system and method can be configured to contain a raw data repository for storing raw data related to financial transactions. A data store contains rules to indicate how many generations or to indicate a time period within which data items are to be stored in the raw data repository. Data items stored in the raw data repository are then accessed by a predictive model in order to perform fraud detection.
摘要翻译： 用于执行欺诈检测的系统和方法。 例如，可以将系统和方法配置为包含用于存储与金融交易相关的原始数据的原始数据存储库。 数据存储包含用于指示多少代或指示将数据项存储在原始数据存储库中的时间段的规则。 然后通过预测模型访问存储在原始数据存储库中的数据项，以执行欺诈检测。
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3.发明授权Enhancing delinquent debt collection using statistical models of debt historical information and account events 有权使用债务历史信息和账户事件的统计模型加强违规收债公开(公告)号：US07536348B2
公开(公告)日：2009-05-19
申请号：US11683976
申请日：2007-03-08
申请人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
发明人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
IPC分类号： G06Q40/00
CPC分类号： G06Q10/10 , G06Q10/06312 , G06Q20/102 , G06Q40/00 , G06Q40/025 , G06Q40/06 , G06Q40/08
摘要： A predictive model, for example, a neural network, evaluates individual debt holder accounts and predicts the amount that will be collected on each account based on learned relationships among known variables. The predictive model is generated using historical data of delinquent debt accounts, the collection methods used to collect the debts in the accounts, and the success of the collection methods. In one embodiment, the predictive model is generated using profiles of delinquent debt accounts summarizing patterns of events in the accounts, and the success of the collection effort in each account. In another embodiment, the predictive model includes a mathematical representation of the collector's notes created during the collection period for each account.
摘要翻译： 预测模型，例如神经网络，评估个人债务持有者帐户，并根据已知变量之间的学习关系预测每个账户上将收集的金额。 预测模型是使用违规债务账户的历史数据，用于收取账户中的债务的收集方法，以及收集方法的成功生成的。 在一个实施例中，使用概述帐户中的事件模式的拖欠债务账户的简档来生成预测模型，以及在每个账户中收集工作的成功。 在另一个实施例中，预测模型包括在每个帐户的收集期间创建的收集者的笔记的数学表示。
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4.发明授权Enhancing delinquent debt collection using statistical models of debt historical information and account events 有权使用债务历史信息和账户事件的统计模型加强违规收债公开(公告)号：US07191150B1
公开(公告)日：2007-03-13
申请号：US09607747
申请日：2000-06-30
申请人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
发明人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
IPC分类号： G06Q40/00
CPC分类号： G06Q10/10 , G06Q10/06312 , G06Q20/102 , G06Q40/00 , G06Q40/025 , G06Q40/06 , G06Q40/08
摘要： A predictive model, for example, a neural network, evaluates individual debt holder accounts and predicts the amount that will be collected on each account based on learned relationships among known variables. The predictive model is generated using historical data of delinquent debt accounts, the collection methods used to collect the debts in the accounts, and the success of the collection methods. In one embodiment, the predictive model is generated using profiles of delinquent debt accounts summarizing patterns of events in the accounts, and the success of the collection effort in each account. In another embodiment, the predictive model includes a mathematical representation of the collector's notes created during the collection period for each account.
摘要翻译： 预测模型，例如神经网络，评估个人债务持有者帐户，并根据已知变量之间的学习关系预测每个账户上将收集的金额。 预测模型是使用违规债务账户的历史数据，用于收取账户中的债务的收集方法，以及收集方法的成功生成的。 在一个实施例中，使用概述帐户中的事件模式的拖欠债务账户的简档来生成预测模型，以及在每个账户中收集工作的成功。 在另一个实施例中，预测模型包括在每个帐户的收集期间创建的收集者的笔记的数学表示。
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5.发明申请公开(公告)号：US20090192957A1
公开(公告)日：2009-07-30
申请号：US12418174
申请日：2009-04-03
CPC分类号： G06Q40/025 , G06Q10/04 , G06Q20/4016 , G06Q30/0185 , G06Q30/0202 , G06Q30/06 , G06Q40/00 , G06Q40/02 , G06Q40/06 , G06Q40/12
摘要： Systems and methods for performing fraud detection. As an example, a system and method can be configured to contain a raw data repository for storing raw data related to financial transactions. A data store contains rules to indicate how many generations or to indicate a time period within which data items are to be stored in the raw data repository. Data items stored in the raw data repository are then accessed by a predictive model in order to perform fraud detection.
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6.发明申请Computer-Implemented Data Storage Systems And Methods For Use With Predictive Model Systems 审中-公开计算机实现的数据存储系统和使用预测模型系统的方法公开(公告)号：US20090192855A1
公开(公告)日：2009-07-30
申请号：US12418186
申请日：2009-04-03
CPC分类号： G06Q40/025 , G06Q10/04 , G06Q20/4016 , G06Q30/0185 , G06Q30/0202 , G06Q30/06 , G06Q40/00 , G06Q40/02 , G06Q40/06 , G06Q40/12
摘要： Systems and methods for performing fraud detection. As an example, a system and method can be configured to contain a raw data repository for storing raw data related to financial transactions. A data store contains rules to indicate how many generations or to indicate a time period within which data items are to be stored in the raw data repository. Data items stored in the raw data repository are then accessed by a predictive model in order to perform fraud detection.
摘要翻译： 用于执行欺诈检测的系统和方法。 例如，可以将系统和方法配置为包含用于存储与金融交易相关的原始数据的原始数据存储库。 数据存储包含用于指示多少代或指示将数据项存储在原始数据存储库中的时间段的规则。 然后通过预测模型访问存储在原始数据存储库中的数据项，以执行欺诈检测。
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7.发明申请Enhancing Delinquent Debt Collection Using Statistical Models of Debt Historical Information and Account Events 有权使用债务历史信息和账户事件的统计模型加强拖欠债务收集公开(公告)号：US20070156557A1
公开(公告)日：2007-07-05
申请号：US11683976
申请日：2007-03-08
申请人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
发明人： Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
IPC分类号： G06Q40/00
CPC分类号： G06Q10/10 , G06Q10/06312 , G06Q20/102 , G06Q40/00 , G06Q40/025 , G06Q40/06 , G06Q40/08
摘要： A predictive model, for example, a neural network, evaluates individual debt holder accounts and predicts the amount that will be collected on each account based on learned relationships among known variables. The predictive model is generated using historical data of delinquent debt accounts, the collection methods used to collect the debts in the accounts, and the success of the collection methods. In one embodiment, the predictive model is generated using profiles of delinquent debt accounts summarizing patterns of events in the accounts, and the success of the collection effort in each account. In another embodiment, the predictive model includes a mathematical representation of the collector's notes created during the collection period for each account.
摘要翻译： 预测模型，例如神经网络，评估个人债务持有者帐户，并根据已知变量之间的学习关系预测每个账户上将收集的金额。 预测模型是使用违规债务账户的历史数据，用于收取账户中的债务的收集方法，以及收集方法的成功生成的。 在一个实施例中，使用概述帐户中的事件模式的拖欠债务账户的简档来生成预测模型，以及在每个账户中收集工作的成功。 在另一个实施例中，预测模型包括在每个帐户的收集期间创建的收集者的笔记的数学表示。
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