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1. 发明申请

US20070061259A1 Mass compromise/point of compromise analytic detection and compromised card portfolio management system 有权
标题翻译：质量妥协/折衷点分析检测和受损卡组合管理系统
公开(公告)号：US20070061259A1
公开(公告)日：2007-03-15
申请号：US11475722
申请日：2006-06-26
申请人： Scott Zoldi , Liang Wang , Li Sun , Steven Wu
发明人： Scott Zoldi , Liang Wang , Li Sun , Steven Wu
IPC分类号： G06Q40/00
CPC分类号： G06Q20/04 , G06Q20/10 , G06Q20/40 , G06Q20/4016 , G06Q30/06 , G06Q40/00 , G06Q40/02 , G06Q40/06
摘要： A system and method for managing mass compromise of financial transaction devices is disclosed. A method includes maintaining a summary of a transaction history for a financial transaction device, and forming a device history profile based on the transaction history, the device history profile including predictive variables indicative of fraud associated with the financial transaction device. A method further includes generating a fraud score based on the predictive variables, the fraud score representing a likelihood that the financial transaction device is compromised will be used fraudulently.
摘要翻译：公开了一种用于管理金融交易设备的大规模妥协的系统和方法。一种方法包括维护金融交易设备的交易历史的摘要，以及基于交易历史形成设备历史简档，设备历史简档包括指示与金融交易设备相关联的欺诈的预测变量。一种方法还包括基于预测变量产生欺诈分数，欺诈分数表示金融交易设备被破坏的可能性将被欺诈地使用。

2. 发明申请

US20070067285A1 Method and apparatus for automatic entity disambiguation 有权
标题翻译：自动实体消歧的方法和装置
公开(公告)号：US20070067285A1
公开(公告)日：2007-03-22
申请号：US11234692
申请日：2005-09-22
申请人： Matthias Blume , Richard Calmbach , Dayne Freitag , Richard Rohwer , Scott Zoldi
发明人： Matthias Blume , Richard Calmbach , Dayne Freitag , Richard Rohwer , Scott Zoldi
IPC分类号： G06F17/30
CPC分类号： G06F17/278 , G06Q10/10
摘要： Entity disambiguation resolves which names, words, or phrases in text correspond to distinct persons, organizations, locations, or other entities in the context of an entire corpus. The invention is based largely on language-independent algorithms. Thus, it is applicable not only to unstructured text from arbitrary human languages, but also to semi-structured data, such as citation databases and the disambiguation of named entities mentioned in wire transfer transaction records for the purpose of detecting money-laundering activity. The system uses multiple types of context as evidence for determining whether two mentions correspond to the same entity and it automatically learns the weight of evidence of each context item via corpus statistics. The invention uses multiple search keys to efficiently find pairs of mentions that correspond to the same entity, while skipping billions of unnecessary comparisons, yielding a system with very high throughput that can be applied to truly massive data.
摘要翻译：实体消歧解决了文本中的哪些名称，单词或短语对应于整个语料库上下文中不同的人，组织，位置或其他实体。本发明主要基于语言无关的算法。因此，它不仅适用于来自任意人类语言的非结构化文本，还适用于半结构化数据，例如引用数据库，以及为了检测洗钱活动而消除电汇交易记录中提到的命名实体。该系统使用多种类型的上下文作为确定两个提及是否对应于相同实体的证据，并通过语料库统计自动学习每个上下文项的证据的权重。本发明使用多个搜索密钥来有效地找到对应于相同实体的提及对，同时跳过数十亿次不必要的比较，产生可以应用于真实海量数据的非常高的吞吐量的系统。

3. 发明授权

US11037229B2 Fraud detection system for the faster payments system 有权
公开(公告)号：US11037229B2
公开(公告)日：2021-06-15
申请号：US12120222
申请日：2008-05-13
申请人： Scott Zoldi , Uwe Mayer
发明人： Scott Zoldi , Uwe Mayer
IPC分类号： G06Q30/00 , G06Q40/02 , G06Q10/10 , G06Q20/40 , G06Q40/00
摘要： A computer-based fraud detection system stores extracts of the payment and other activity of the payer as well as the payee by efficiently profiling their accounts, and also stores extracts of the overall global or segmented payment activities. This profile information is then used to effectively capture fraudulent activity. The fraud detection system accepts messages from the payment processing system or from the associated financial institution, and depending on the nature of the message will update its databases, or assess fraud risk by computing a score, or both. If a score is computed, the higher the score, the greater the likelihood that the transaction is fraudulent. Said score is based on automatically determined risky values of variables and is also be automatically scaled using self-calibrating analytics using the captured profile information. In a typical scenario the fraud detection system client sets a “threshold score” above which the transactions are considered suspect enough to be investigated further or to trigger a payment decline outright. The solution is suitable for being installed at a financial institution, on the network, or some other institutional participant of the Faster Payments System (FPS), such as an access service provider to the FPS for corporate clients.

4. 发明申请

US20130103629A1 Automated Entity Identification for Efficient Profiling in an Event Probability Prediction System 有权
标题翻译：事件概率预测系统中高效分析的自动实体识别
公开(公告)号：US20130103629A1
公开(公告)日：2013-04-25
申请号：US13710423
申请日：2012-12-10
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06N5/02
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史概况，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

5. 发明授权

US08121962B2 Automated entity identification for efficient profiling in an event probability prediction system 有权
标题翻译：自动实体识别用于事件概率预测系统中的高效分析
公开(公告)号：US08121962B2
公开(公告)日：2012-02-21
申请号：US12110261
申请日：2008-04-25
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06F15/18 , G06E1/00 , G06E3/00 , G06G7/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史简档，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

6. 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。

7. 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。

8. 发明授权

US10115153B2 Detection of compromise of merchants, ATMS, and networks 有权
公开(公告)号：US10115153B2
公开(公告)日：2018-10-30
申请号：US12347559
申请日：2008-12-31
申请人： Scott Zoldi , Michael Urban
发明人： Scott Zoldi , Michael Urban
IPC分类号： G06Q40/00 , G06Q20/40
摘要： A system and method for detecting compromise of financial transaction instruments associated with a merchant or automated teller machine (ATM) are disclosed. Historical data representing a historical aggregate financial transaction instrument behavior history is stored in a computer memory. The historical data is received at the computer from one or more merchants and ATMs via a communications network. Authorization data representing authorization behavior of a plurality of financial transaction cards related to corresponding financial transactions at the same or a different one or more merchants and ATMs is received by the computer. Abnormal activity data representing an abnormal aggregate financial transaction instrument activity based on the authorization data is determined, and the historical data is compared with the abnormal activity data to generate a compromise profile for the plurality of financial transaction instruments.

9. 发明申请

US20120150779A1 Automated Entity Identification for Efficient Profiling in an Event Probability Prediction System 有权
标题翻译：事件概率预测系统中高效分析的自动实体识别
公开(公告)号：US20120150779A1
公开(公告)日：2012-06-14
申请号：US13399067
申请日：2012-02-17
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06F15/18 , G06N7/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史简档，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

10. 发明申请

US20100169192A1 Detection Of Compromise Of Merchants, ATMS, And Networks 审中-公开
标题翻译：检测商人，ATMS和网络的妥协
公开(公告)号：US20100169192A1
公开(公告)日：2010-07-01
申请号：US12347559
申请日：2008-12-31
申请人： Scott Zoldi , Michael Urban
发明人： Scott Zoldi , Michael Urban
IPC分类号： G06Q10/00 , G06N5/02 , G06Q40/00
CPC分类号： G06Q40/00 , G06Q20/4016 , G06Q40/12
摘要： A system and method for detecting compromise of financial transaction instruments associated with a merchant or automated teller machine (ATM) are disclosed. Historical data representing a historical aggregate financial transaction instrument behavior history is stored in a computer memory. The historical data is received at the computer from one or more merchants and ATMs via a communications network. Authorization data representing authorization behavior of a plurality of financial transaction cards related to corresponding financial transactions at the same or a different one or more merchants and ATMs is received by the computer. Abnormal activity data representing an abnormal aggregate financial transaction instrument activity based on the authorization data is determined, and the historical data is compared with the abnormal activity data to generate a compromise profile for the plurality of financial transaction instruments.
摘要翻译：公开了一种用于检测与商家或自动取款机（ATM）相关联的金融交易工具的妥协的系统和方法。表示历史汇总金融交易工具行为历史的历史数据存储在计算机存储器中。历史数据通过通信网络从一个或多个商户和ATM在计算机处接收。计算机接收表示与相同或不同的一个或多个商户和ATM相应的金融交易相关的多个金融交易卡的授权行为的授权数据。确定代表基于授权数据的异常总计金融交易工具活动的异常活动数据，并将历史数据与异常活动数据进行比较，以生成多个金融交易工具的折中简档。

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