公开(公告)号：US20150095146A1

公开(公告)日：2015-04-02

申请号：US14243097

申请日：2014-04-02

Applicant: Brighterion, Inc.

Inventor： Akli Adjaoute

IPC: G06Q30/02

CPC classification number: G06Q30/0269 ,  G06Q30/0255 ,  G06Q30/0276

Abstract: A real-time fraud prevention system enables merchants and commercial organizations on-line to assess and protect themselves from high-risk users. A centralized database is configured to build and store dossiers of user devices and behaviors collected from subscriber websites in real-time. Real, low-risk users have webpage click navigation behaviors that are assumed to be very different than those of fraudsters. Individual user devices are distinguished from others by hundreds of points of user-device configuration data each independently maintains. A client agent provokes user devices to volunteer configuration data when a user visits respective webpages at independent websites. A collection of comprehensive dossiers of user devices is organized by their identifying information, and used calculating a fraud score in real-time. Each corresponding website is thereby assisted in deciding whether to allow a proposed transaction to be concluded with the particular user and their device.

Abstract translation: 实时欺诈预防系统使商家和商业机构能够在线评估和保护自己免受高风险的用户的伤害。 集中式数据库被配置为实时地构建和存储从用户网站收集的用户设备和行为的卷宗。 真实的，低风险的用户有网页点击导航行为，假设与欺诈者的行为非常不同。 通过数百个用户设备配置数据点独立维护，个别用户设备与其他用户设备区分开来。 当用户访问独立网站上的相应网页时，客户端代理会引起用户设备自愿配置数据。 用户设备的综合卷宗集合由其识别信息组织，并实时计算欺诈分数。 从而有助于每个相应的网站决定是否允许与特定用户及其设备结束提议的交易。

公开(公告)号：US20150046181A1

公开(公告)日：2015-02-12

申请号：US14517872

申请日：2014-10-19

Applicant: BRIGHTERION, INC.

Inventor： Akli Adjaoute

IPC: G06F19/00 ,  G06N5/04 ,  G06N99/00

CPC classification number: G06F19/328 ,  G06N5/04

Abstract: Real-time fraud prevention software-as-a-service (SaaS) products include computer instruction sets to enable a network server to receive medical histories, enrollments, diagnosis, prescription, treatment, follow up, billings, and other data as they occur. The SaaS includes software instruction sets to combine, correlate, categorize, track, normalize, and compare the data sorted by patient, healthcare provider, institution, seasonal, and regional norms. Fraud reveals itself in the ways data points deviate from norms in nonsensical or inexplicable conduct. The individual behaviors of each healthcare provider are independently monitored, characterized, and followed by self-spawning smart agents that can adapt and change their rules as the healthcare providers evolve. Such smart agents will issue flags when their particular surveillance target is acting out of character, outside normal parameters for them. Fraud controls can therefore be much tighter than those that have to accommodate those of a diverse group.

Abstract translation: 实时欺诈预防软件即服务（SaaS）产品包括计算机指令集，使网络服务器能够在发生病历，入学，诊断，处方，治疗，跟进，账单和其他数据时收到。 SaaS包括软件指令集，用于组合，关联，分类，跟踪，规范化和比较患者，医疗保健提供者，机构，季节和区域规范排序的数据。 欺诈行为显示出数据点偏离荒谬或莫名其妙的行为规范。 每个医疗保健提供者的个人行为是独立监控，特征化，并且随后是自我产卵的智能代理，随着医疗保健提供者的发展，可以适应和改变其规则。 当他们的特定监视目标超出性格时，这些智能代理将发出标志，超出正常参数。 因此，欺诈控制可以比那些不同于不同群体的控制措施更加紧密。

公开(公告)号：US20150039512A1

公开(公告)日：2015-02-05

申请号：US14517771

申请日：2014-10-17

Applicant: Brighterion, Inc.

Inventor： Akli Adjaoute

IPC: G06Q20/40 ,  G06N99/00

CPC classification number: G06Q20/4016 ,  G06N20/00

Abstract: An artificial intelligence cross-channel fraud management system comprises a parallel arrangement of single-channel, fully trained fraud models that each integrate several artificial intelligence classifiers like neural networks, case based reasoning, decision trees, genetic algorithms, fuzzy logic, and rules and constraints. These are further integrated by the expert programmers and development system with smart agents and associated real-time profiling, recursive profiles, and long-term profiles. The trainable general payment fraud models are trained into channel specialists with channel-filtered supervised and unsupervised data to produce each channels payment fraud model. This then is applied by a commercial client to process real-time cross-channel transactions and authorization requests for fraud scores. A detection of fraud in one channel is used to immediately sensitize all the other fraud channel models to the involved accountholder. Low level, but broad spectrum fraud can be used to trigger all the accounts of a compromised accountholder or merchant data breach.

Abstract translation: 人工智能跨渠道欺诈管理系统包括单通道，经过充分训练的欺诈模型的并行布置，每个模型集成了几个人工智能分类器，如神经网络，基于案例的推理，决策树，遗传算法，模糊逻辑以及规则和约束 。 这些由专家程序员和开发系统与智能代理和相关的实时分析，递归配置文件和长期配置文件进一步集成。 可培训的一般付款欺诈模式经过频道专家培训，具有频道过滤的监督和无监督数据，以产生每个频道支付欺诈模式。 然后由商业客户端应用来处理实时跨渠道交易和欺诈分数的授权请求。 使用一个通道中的欺诈检测来立即使所有其他欺诈渠道模型对所涉及的帐户持有人敏感。 低级别，但广泛的欺诈行为可用于触发受损的客户或商户数据泄露的所有帐户。

公开(公告)号：US20150032589A1

公开(公告)日：2015-01-29

申请号：US14514381

申请日：2014-10-15

Applicant: BRIGHTERION, INC.

Inventor： Akli Adjaoute

IPC: G06Q20/40 ,  G06Q10/06

CPC classification number: G06Q20/4016 ,  G06Q10/0635 ,  G06Q40/025

Abstract: An artificial intelligence fraud management solution comprises an expert programmer development system to build trainable general payment fraud models that integrate several artificial intelligence classifiers like neural networks, case based reasoning, decision trees, genetic algorithms, fuzzy logic, and rules and constraints. These are further integrated by the expert programmers and development system with smart agents and associated real-time profiling, recursive profiles, and long-term profiles. The trainable general payment fraud models are trained with supervised and unsupervised data to produce an applied payment fraud model. This then is applied by a commercial client to process real-time transactions and authorization requests for fraud scores.

Abstract translation: 人工智能欺诈管理解决方案包括专家程序员开发系统，构建可训练的一般支付欺诈模型，将诸如神经网络，基于案例的推理，决策树，遗传算法，模糊逻辑以及规则和约束之类的人工智能分类器集成起来。 这些由专家程序员和开发系统与智能代理和相关的实时分析，递归配置文件和长期配置文件进一步集成。 可培训的一般付款欺诈模型接受了监督和无监督的数据培训，以产生应用的付款欺诈模型。 然后由商业客户应用来处理欺诈分数的实时交易和授权请求。