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    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching
    1.
    再颁专利
    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching 有权
    使用监督分割和最近邻匹配的消费者财务行为的预测建模

    公开(公告)号：USRE42577E1

    公开(公告)日：2011-07-26

    申请号：US12729215

    申请日：2010-03-22

    申请人： Matthias Blume ,  Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  William R. Caid ,  Ted E. Dunning ,  Gerald S. Russell ,  Kevin L. Sitze

    发明人： Matthias Blume ,  Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  William R. Caid ,  Ted E. Dunning ,  Gerald S. Russell ,  Kevin L. Sitze

    IPC分类号： G06Q10/00

    CPC分类号： G06Q30/02 ,  G06Q30/0202 ,  G06Q30/0207 ,  G06Q30/0241 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0601

    摘要： Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.

    摘要翻译： 通过将消费者交易数据应用于与商家细分相关的预测模型，提供消费者财务行为的预测建模，包括对特定营销努力的可能响应的确定。 商业细分是根据交易序列中商家的共同出现从消费者交易数据中得出的。 商家向量表示特定商家，并且在向量空间中对齐，作为商家与预期频繁相同程度的函数。 监督分割被应用于商家向量以形成商家分段。 商业细分预测模型根据消费者以前的支出，为每个特定消费者的每个商业细分市场提供支出预测。 消费者个人资料描述了每个消费者在商家细分中以及跨商家细分的消费的总体统计。 消费者资料包括作为由消费者光顾的所选商家的汇总向量导出的消费者向量。 消费者行为的预测是通过对消费者向量应用最近邻分析来做出的，从而有助于向最有可能积极响应的消费者定位促销优惠。

    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching
    2.
    发明授权
    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching 有权
    使用监督分割和最近邻匹配的消费者财务行为的预测建模

    公开(公告)号：US07533038B2

    公开(公告)日：2009-05-12

    申请号：US11623266

    申请日：2007-01-15

    申请人： Matthias Blume ,  Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Gerald R. Russell ,  Kevin L. Sitze

    发明人： Matthias Blume ,  Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Gerald R. Russell ,  Kevin L. Sitze

    IPC分类号： G06Q10/00

    CPC分类号： G06Q30/02 ,  G06Q30/0202 ,  G06Q30/0207 ,  G06Q30/0241 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0601

    摘要： Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.

    摘要翻译： 通过将消费者交易数据应用于与商家细分相关的预测模型，提供消费者财务行为的预测建模，包括对特定营销努力的可能响应的确定。 商业细分是根据交易序列中商家的共同出现从消费者交易数据中得出的。 商家向量表示特定商家，并且在向量空间中对齐，作为商家与预期频繁相同程度的函数。 监督分割被应用于商家向量以形成商家分段。 商业细分预测模型根据消费者以前的支出，为每个特定消费者的每个商业细分市场提供支出预测。 消费者个人资料描述了每个消费者在商家细分中以及跨商家细分的消费的总体统计。 消费者资料包括作为由消费者光顾的所选商家的汇总向量导出的消费者向量。 消费者行为的预测是通过对消费者向量应用最近邻分析来做出的，从而有助于向最有可能积极响应的消费者定位促销优惠。

    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching
    4.
    发明授权
    Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching 有权
    使用监督分割和最近邻匹配的消费者财务行为的预测建模

    公开(公告)号：US07165037B2

    公开(公告)日：2007-01-16

    申请号：US11012812

    申请日：2004-12-14

    申请人： Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  A. U. Mattias Blume ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Gerald R. Russell ,  Kevin L. Sitze

    发明人： Michael A. Lazarus ,  Larry S. Peranich ,  Frederique Vernhes ,  A. U. Mattias Blume ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Gerald R. Russell ,  Kevin L. Sitze

    IPC分类号： G06Q10/00

    CPC分类号： G06Q30/02 ,  G06Q30/0202 ,  G06Q30/0207 ,  G06Q30/0241 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0601

    摘要： Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments, which are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur. Supervised segmentation is applied to merchant vectors to form merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. Consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors.

    摘要翻译： 消费者财务行为的预测建模，包括对特定营销努力的可能响应的确定，通过将消费者交易数据应用于与商家分段相关联的预测模型来提供，所述预测模型是根据基于商家的序列顺序的消费者交易数据得出的消费者交易数据 的交易。 商家向量代表特定商家，并且在向量空间中对齐，作为商家共同发生的程度的函数。 监督分割被应用于商家向量以形成商家分段。 商业细分预测模型根据消费者以前的支出，为每个特定消费者的每个商业细分市场提供支出预测。 消费者个人资料描述了每个消费者在商家细分中以及跨商家细分的消费的总体统计。 消费者概况包括作为由消费者光顾的所选商家的汇总向量导出的消费者向量。 消费者行为的预测是通过对消费者向量应用最近邻分析来做出的。

    Predictive modeling of consumer financial behavior
    5.
    发明授权
    Predictive modeling of consumer financial behavior 有权
    消费者财务行为的预测建模

    公开(公告)号：US06430539B1

    公开(公告)日：2002-08-06

    申请号：US09306237

    申请日：1999-05-06

    申请人： Michael A. Lazarus ,  A. U. Mattias Blume ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Larry S. Peranich ,  Gerald R. Russell ,  Kevin L. Sitze

    发明人： Michael A. Lazarus ,  A. U. Mattias Blume ,  Kenneth B. Brown ,  William R. Caid ,  Ted E. Dunning ,  Larry S. Peranich ,  Gerald R. Russell ,  Kevin L. Sitze

    IPC分类号： G06F1760

    CPC分类号： G06Q30/02 ,  G06Q30/0202 ,  G06Q30/0207 ,  G06Q30/0241 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0601

    摘要： Predictive modeling of consumer financial behavior is provided by application of consumer transaction data to predictive models associated with merchant segments. Merchant segments are derived from consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors representing specific merchants are clustered to form merchant segments in a vector space as a function of the degree to which merchants co-occur more or less frequently than expected. Each merchant segment is trained using consumer transaction data in selected past time periods to predict spending in subsequent time periods for a consumer based on previous spending by the consumer. Consumer profiles describe summary statistics of consumer spending in and across merchant segments. Analysis of consumers associated with a segment identifies selected consumers according to predicted spending in the segment or other criteria, and the targeting of promotional offers specific to the segment and its merchants.

    摘要翻译： 消费者财务行为的预测建模是通过将消费者交易数据应用于与商家细分相关联的预测模型来提供的。 商家细分来自消费者交易数据，这是根据交易顺序中商家的共同出现。 代表特定商户的商家向量被聚集以在向量空间中形成商家分段，作为商家与预期频繁地共同出现的程度的函数。 在选定的过去时间段内，使用消费者交易数据对每个商业细分进行培训，以根据消费者以前的消费来预测消费者的后续时间段的消费。 消费者个人资料描述了商业细分市场内外的消费支出总结统计。 根据分段或其他标准中的预测支出以及针对细分受众群及其商家的促销优惠的定位，对与细分相关联的消费者的分析识别所选择的消费者。

    Comprehensive identity protection system
    7.
    发明授权
    Comprehensive identity protection system 有权
    综合身份保护制度

    公开(公告)号：US08296250B2

    公开(公告)日：2012-10-23

    申请号：US13195328

    申请日：2011-08-01

    申请人： Theodore J. Crooks ,  Uwe F. Mayer ,  Michael A. Lazarus

    发明人： Theodore J. Crooks ,  Uwe F. Mayer ,  Michael A. Lazarus

    IPC分类号： G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00

    CPC分类号： G06Q50/18 ,  G06Q20/40 ,  G06Q20/4016 ,  G06Q20/403 ,  G06Q50/188

    摘要： A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.

    摘要翻译： 公开了一种保护身份欺诈的系统和方法。 系统包括检测子系统以识别身份欺诈风险的应用和/或帐户，以及处理子系统来处理由检测系统提供的数据并且确定身份欺诈是否存在于应用和/或帐户中。 根据实现，定义一个或多个神经网络模型，每个神经网络模型被配置为处理与主题相关的一类情况以及描述该类的情况的特定数据配置。 运行一个或多个神经网络模型以产生关于受试者身份的数据请求，并且将数据请求传递到监视与对象相关联的事务的检测系统。 请求与事务相关联的附加数据，直到实现阈值确定性或直到可用数据或模型耗尽为止。

    Comprehensive identity protection system
    9.
    发明授权
    Comprehensive identity protection system 有权
    综合身份保护制度

    公开(公告)号：US07849029B2

    公开(公告)日：2010-12-07

    申请号：US11421896

    申请日：2006-06-02

    申请人： Theodore J. Crooks ,  Uwe F. Mayer ,  Michael A. Lazarus

    发明人： Theodore J. Crooks ,  Uwe F. Mayer ,  Michael A. Lazarus

    IPC分类号： G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00

    CPC分类号： G06Q50/18 ,  G06Q20/40 ,  G06Q20/4016 ,  G06Q20/403 ,  G06Q50/188

    摘要： A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.

    摘要翻译： 公开了一种保护身份欺诈的系统和方法。 系统包括检测子系统以识别身份欺诈风险的应用和/或帐户，以及处理子系统来处理由检测系统提供的数据并且确定身份欺诈是否存在于应用和/或帐户中。 根据实现，定义一个或多个神经网络模型，每个神经网络模型被配置为处理与主题相关的一类情况以及描述该类的情况的特定数据配置。 运行一个或多个神经网络模型以产生关于受试者身份的数据请求，并且将数据请求传递到监视与对象相关联的事务的检测系统。 请求与事务相关联的附加数据，直到实现阈值确定性或直到可用数据或模型耗尽为止。