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1. 发明授权

US08175897B2 Score based decisioning 有权
标题翻译：基于分数决策
公开(公告)号：US08175897B2
公开(公告)日：2012-05-08
申请号：US11738362
申请日：2007-04-20
申请人： Walter W. Lee , Daniel Shoham , Wesley K. Wilhelm , Joseph P. Milana , Allen P. Jost
发明人： Walter W. Lee , Daniel Shoham , Wesley K. Wilhelm , Joseph P. Milana , Allen P. Jost
IPC分类号： G06Q40/00
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。

2. 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。

3. 发明授权

US07251624B1 Score based decisioning 有权
标题翻译：基于分数决策
公开(公告)号：US07251624B1
公开(公告)日：2007-07-31
申请号：US09675992
申请日：2000-09-29
申请人： Walter W. Lee , Daniel Shoham , Wesley K. Wilhelm , Joseph P. Milana , Alan P. Jost
发明人： Walter W. Lee , Daniel Shoham , Wesley K. Wilhelm , Joseph P. Milana , Alan P. Jost
IPC分类号： G06Q40/00
CPC分类号： G06Q30/06 , G06Q30/0601 , G06Q30/0609 , G06Q40/00 , G06Q40/025 , G06Q40/08
摘要： The invention aids an entity to selectively request additional data about a user to serve the needs of the entity without causing the user to have an adverse reaction. The invention helps an entity to determine the condition under which 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：本发明有助于实体选择性地请求关于用户的附加数据以满足实体的需要而不会导致用户具有不利的反应。本发明帮助实体确定要求附加数据的条件，以便减少使得用户具有不利反应（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。

4. 发明申请

US20070156557A1 Enhancing Delinquent Debt Collection Using Statistical Models of Debt Historical Information and Account Events 有权
标题翻译：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。

5. 发明授权

US07536348B2 Enhancing delinquent debt collection using statistical models of debt historical information and account events 有权
标题翻译：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。

6. 发明授权

US07191150B1 Enhancing delinquent debt collection using statistical models of debt historical information and account events 有权
标题翻译：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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