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1. 发明授权

US07458508B1 System and method for identity-based fraud detection 有权
标题翻译：基于身份的欺诈检测的系统和方法
公开(公告)号：US07458508B1
公开(公告)日：2008-12-02
申请号：US11026566
申请日：2004-12-30
申请人： Xuhui Shao , Jianjun Xie , Tao Hong , Allen Jost
发明人： Xuhui Shao , Jianjun Xie , Tao Hong , Allen Jost
IPC分类号： G06K5/00
CPC分类号： G06Q20/40 , G06Q20/04 , G06Q20/4016
摘要： A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.
摘要翻译：用于识别欺诈性帐户应用的方法包括：接收包括多个身份相关字段的新帐户应用，并且将与新帐户应用相关联的身份相关字段与与多个历史账户应用相关联的身份相关字段链接。链接形成图形模式，可以进行统计分析以确定新帐户应用程序是欺诈性的可能性。统计分析可以包括将图形模式与已知或正常的图形模式进行比较，以便检测与新帐户应用相关联的图形模式中发生的差异或异常。

2. 发明授权

US5819226A Fraud detection using predictive modeling 失效
标题翻译：使用预测建模的欺诈检测
公开(公告)号：US5819226A
公开(公告)日：1998-10-06
申请号：US941971
申请日：1992-09-08
申请人： Krishna M. Gopinathan , Louis S. Biafore , William M. Ferguson , Michael A. Lazarus , Anu K. Pathria , Allen Jost
发明人： Krishna M. Gopinathan , Louis S. Biafore , William M. Ferguson , Michael A. Lazarus , Anu K. Pathria , Allen Jost
IPC分类号： G07F7/12 , G06Q20/00 , G06Q20/40 , G06Q30/02 , G06Q40/00 , G07F7/08 , G06F157/00
CPC分类号： G07F7/08 , G06Q20/00 , G06Q20/40 , G06Q20/4016 , G06Q20/403 , G06Q30/02 , G06Q40/00 , G06Q40/02 , G06Q40/025 , H04M15/47 , H04M2215/0148
摘要： An automated system and method detects fraudulent transactions using a predictive model such as a neural network to evaluate individual customer accounts and identify potentially fraudulent transactions based on learned relationships among known variables. The system may also output reason codes indicating relative contributions of various variables to a particular result. The system periodically monitors its performance and redevelops the model when performance drops below a predetermined level.
摘要翻译：自动化系统和方法使用诸如神经网络的预测模型来检测欺诈交易，以评估个人客户账户并且基于已知变量之间的学习关系来识别潜在的欺诈交易。系统还可以输出指示各种变量对特定结果的相对贡献的原因代码。当性能下降到预定水平以下时，系统会定期监控其性能并重新开发模型。

3. 发明授权

US5361201A Real estate appraisal using predictive modeling 失效
标题翻译：房地产评估使用预测模型
公开(公告)号：US5361201A
公开(公告)日：1994-11-01
申请号：US963908
申请日：1992-10-19
申请人： Allen Jost , Jennifer Nelson , Krishna Gopinathan , Craig Smith
发明人： Allen Jost , Jennifer Nelson , Krishna Gopinathan , Craig Smith
IPC分类号： G06Q40/00 , G06F15/18 , G06F15/40
CPC分类号： G06Q40/02 , G06Q40/00
摘要： An automated real estate appraisal system (100) and method generates estimates of real estate value using a predictive model such as a neural network (908). The predictive model (908) generates these estimates based on learned relationships among variables describing individual property characteristics (905) as well as general neighborhood characteristics at various levels of geographic specificity (906). The system (100) may also output reason codes indicating relative contributions (1009) of various variables to a particular result, and may generate reports (701) describing property valuations, market trend analyses, property conformity information, and recommendations regarding loans based on risk related to a property.
摘要翻译：自动化房地产估价系统（100）和方法使用诸如神经网络（908）的预测模型来生成房地产价值的估计。预测模型（908）基于描述个体特征的变量（905）之间的学习关系以及各种地理特异性的一般邻域特征（906）来生成这些估计。系统（100）还可以输出指示各种变量对特定结果的相对贡献（1009）的原因代码，并且可以生成描述属性评估，市场趋势分析，财产合规信息以及关于基于风险的贷款的建议的报告（701）与物业相关。

4. 发明授权

US07686214B1 System and method for identity-based fraud detection using a plurality of historical identity records 有权
标题翻译：使用多个历史身份记录的基于身份的欺诈检测的系统和方法
公开(公告)号：US07686214B1
公开(公告)日：2010-03-30
申请号：US11026552
申请日：2004-12-30
申请人： Xuhui Shao , Tao Hong , Alan Tsang , Allen Jost , Christer J. DiChiara , Mike Cook , Stephen Coggeshall
发明人： Xuhui Shao , Tao Hong , Alan Tsang , Allen Jost , Christer J. DiChiara , Mike Cook , Stephen Coggeshall
IPC分类号： G06K5/00
CPC分类号： G06Q40/02 , G06Q20/382 , G06Q20/40 , G06Q20/401 , G06Q40/025 , G06Q40/08
摘要： A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.
摘要翻译：用于识别欺诈性帐户应用的方法包括：接收包括多个身份相关字段的新帐户应用，并且将与新帐户应用相关联的身份相关字段与与多个历史账户应用相关联的身份相关字段链接。链接形成图形模式，可以进行统计分析以确定新帐户应用程序是欺诈性的可能性。统计分析可以包括将图形模式与已知或正常的图形模式进行比较，以便检测与新帐户应用相关联的图形模式中发生的差异或异常。

5. 发明授权

US07793835B1 System and method for identity-based fraud detection for transactions using a plurality of historical identity records 有权
标题翻译：使用多个历史身份记录的交易的基于身份的欺诈检测的系统和方法
公开(公告)号：US07793835B1
公开(公告)日：2010-09-14
申请号：US12499048
申请日：2009-07-07
申请人： Stephen Coggeshall , Allen Jost , Joseph Blue , Christer J. Dichiara , Mike Cook , Xuhul Shao
发明人： Stephen Coggeshall , Allen Jost , Joseph Blue , Christer J. Dichiara , Mike Cook , Xuhul Shao
IPC分类号： G06K5/00
CPC分类号： G06Q40/00 , G06F21/552 , G06Q20/40 , G06Q20/4016
摘要： A method for using transaction records to detect fraud, including receiving a plurality of identity records comprising identity related information; receiving a plurality of transaction records comprising transaction information from a plurality of client institutions; linking the plurality of identity records with each other based on the identity related information; linking the plurality of transaction records with the identity records, wherein a link between a transaction record and an identity record is created when a characteristic of the transaction information of the transaction record is similar to a characteristic of the identity related information of the identity record, the links forming a graphical pattern; and performing statistical analysis of the graphical pattern to detect fraud, wherein the statistical analysis comprises analyzing the graphical pattern to determine whether the graphical pattern is anomalous when considered in relation to a normal graphical pattern.
摘要翻译：一种使用交易记录来检测欺诈的方法，包括接收包括身份相关信息的多个身份记录; 从多个客户机构接收包括交易信息的多个交易记录; 基于所述身份相关信息将所述多个身份记录彼此链接; 将所述多个交易记录与所述身份记录相关联，其中当所述交易记录的交易信息的特征与所述身份记录的身份相关信息的特征相似时，创建交易记录与身份记录之间的链接，链接形成图形模式; 以及执行所述图形模式的统计分析以检测欺诈，其中所述统计分析包括分析所述图形模式以确定在考虑相对于正常图形模式时所述图形模式是否是异常的。

6. 发明授权

US06330546B1 Risk determination and management using predictive modeling and transaction profiles for individual transacting entities 有权
标题翻译：风险确定和管理使用个人交易实体的预测模型和交易简档
公开(公告)号：US06330546B1
公开(公告)日：2001-12-11
申请号：US09167102
申请日：1998-10-05
申请人： Krishna M. Gopinathan , Allen Jost , Louis S. Biafore , William M. Ferguson , Michael A. Lazarus , Anu K. Pathria
发明人： Krishna M. Gopinathan , Allen Jost , Louis S. Biafore , William M. Ferguson , Michael A. Lazarus , Anu K. Pathria
IPC分类号： G06F1760
CPC分类号： G07F7/08 , G06Q20/00 , G06Q20/40 , G06Q20/4016 , G06Q20/403 , G06Q30/02 , G06Q40/00 , G06Q40/02 , G06Q40/025 , H04M15/47 , H04M2215/0148
摘要： An automated system and method detects fraudulent transactions using a predictive model such as a neural network to evaluate individual customer accounts and identify potentially fraudulent transactions based on learned relationships among known variables. The system may also output reason codes indicating relative contributions of various variables to a particular result. The system periodically monitors its performance and redevelops the model when performance drops below a predetermined level.
摘要翻译：自动化系统和方法使用诸如神经网络的预测模型来检测欺诈交易，以评估个人客户账户并且基于已知变量之间的学习关系来识别潜在的欺诈交易。系统还可以输出指示各种变量对特定结果的相对贡献的原因代码。当性能下降到预定水平以下时，系统会定期监控其性能并重新开发模型。

7. 发明授权

US07562814B1 System and method for identity-based fraud detection through graph anomaly detection 有权
标题翻译：通过图形异常检测进行身份欺诈检测的系统和方法
公开(公告)号：US07562814B1
公开(公告)日：2009-07-21
申请号：US11026556
申请日：2004-12-30
申请人： Xuhui Shao , Jianjun Xie , Tao Hong , Allen Jost
发明人： Xuhui Shao , Jianjun Xie , Tao Hong , Allen Jost
IPC分类号： G06K5/00
CPC分类号： G06Q40/00 , G06F21/552 , G06Q20/40 , G06Q20/4016
摘要： A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.
摘要翻译：用于识别欺诈性帐户应用的方法包括：接收包括多个身份相关字段的新帐户应用，并且将与新帐户应用相关联的身份相关字段与与多个历史账户应用相关联的身份相关字段链接。链接形成图形模式，可以进行统计分析以确定新帐户应用程序是欺诈性的可能性。统计分析可以包括将图形模式与已知或正常的图形模式进行比较，以便检测与新帐户应用相关联的图形模式中发生的差异或异常。

8. 发明申请

US20070288641A1 SCORE BASED DECISIONING 有权
标题翻译：基于分数决策
公开(公告)号：US20070288641A1
公开(公告)日：2007-12-13
申请号：US11738362
申请日：2007-04-20
申请人： Walter LEE , Daniel Shoham , Wesley Wilhelm , Joseph Milana , Allen Jost
发明人： Walter LEE , Daniel Shoham , Wesley Wilhelm , Joseph Milana , Allen Jost
IPC分类号： G06F15/16
CPC分类号： G06Q30/06 , G06Q30/0601 , G06Q30/0609 , G06Q40/00 , G06Q40/025 , G06Q40/08
摘要： The invention aids an entity operating on the Internet or on another network to selectively request additional data about a user who has made a request for an interaction with the entity. The invention helps an entity to determine when and how to request additional data so as to reduce the likelihood of causing the user to have an adverse reaction, e.g., terminate the interaction. One embodiment of the invention concerns customers requesting transactions with on-line merchants. More specifically, this embodiment aids merchants by detecting Internet credit card transactions that are likely to be fraudulent, and providing the merchants with mechanisms for managing a suspected transaction as it occurs to obtain additional information that can be useful to reducing the likelihood of fraud.
摘要翻译：本发明有助于在因特网或另一网络上操作的实体选择性地请求关于已经做出与该实体进行交互的请求的用户的附加数据。本发明有助于实体确定何时以及如何请求附加数据，以便减少使用户产生不利反应（例如终止交互）的可能性。本发明的一个实施例涉及请求与在线商户交易的客户。更具体地，该实施例通过检测可能是欺诈性的互联网信用卡交易来帮助商家，并且为商家提供用于管理可疑交易的机制，以获得可用于减少欺诈可能性的附加信息。

9. 发明申请

US20130085769A1 CHARACTERIZING HEALTHCARE PROVIDER, CLAIM, BENEFICIARY AND HEALTHCARE MERCHANT NORMAL BEHAVIOR USING NON-PARAMETRIC STATISTICAL OUTLIER DETECTION SCORING TECHNIQUES 审中-公开
标题翻译：表征健康保险提供者，索赔，受益和健康商品正常行为使用非参数统计出口检测分选技术
公开(公告)号：US20130085769A1
公开(公告)日：2013-04-04
申请号：US13617085
申请日：2012-09-14
申请人： Allen Jost , Rudolph John Freese , Walter Allan Klindworth
发明人： Allen Jost , Rudolph John Freese , Walter Allan Klindworth
IPC分类号： G06Q50/22
CPC分类号： G06F19/328 , G06Q50/22 , G16H10/60
摘要： This invention uses non-parametric statistical measures and probability mathematical techniques to calculate deviations of variable values, on both the high and low side of a data distribution, from the midpoint of the data distribution. It transforms the data values and then combines all of the individual variable values into a single scalar value that is a “good-ness” score. This “good-ness” behavior score model characterizes “normal” or typical behavior, rather than predicting fraudulent, abusive, or “bad”, behavior. The “good” score is a measure of how likely it is that the subject's behavior characteristics are from a population representing a “good” or “normal” provider, claim, beneficiary or healthcare merchant behavior. The “good” score can replace or compliment a score model that predicts “bad” behavior in order to reduce false positive rates. The optimal risk management prevention program should include both a “good” behavior score model and a “bad” behavior score model.
摘要翻译：本发明使用非参数统计量度和概率数学技术从数据分布的中点计算数据分布的高低侧的变量值的偏差。它转换数据值，然后将所有单个变量值组合为一个良好评分的单个标量值。这种良性行为评分模型描绘了正常或典型的行为，而不是预测欺诈，辱骂或坏行为。良好的分数是衡量受试者的行为特征来自代表良好或正常提供者，索赔，受益人或医疗保健商人行为的人群的可能性。良好的分数可以取代或补充一个预测不良行为的分数模型，以减少假阳性率。最佳风险管理预防计划应包括良好行为评分模型和不良行为评分模型。

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