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    • 9. 发明授权
    • Financial risk prediction systems and methods therefor
    • 财务风险预测系统及其方法
    • US06658393B1
    • 2003-12-02
    • US09397160
    • 1999-09-15
    • Catherine A. BaschBelva J. BruesewitzKevin SiegelPatrick Faith
    • Catherine A. BaschBelva J. BruesewitzKevin SiegelPatrick Faith
    • G06F1760
    • G07F7/1008G06Q20/341G06Q20/40G06Q20/40145G06Q20/4016G06Q20/403G06Q20/4037G06Q40/00G06Q40/025G06Q40/08G07F7/08
    • A method for predicting financial risk is disclosed. The method includes receiving data inputs on a first computing system. The data inputs includes historical data associated with at least a first account issued to an account owner, and the historical data includes historical transaction information for the first account. The method also includes generating a predictive model based on at least the historical data, receiving a current transaction authorization request associated with the first account on the first computing system, and generating a risk score by applying the predictive model to data associated with the current transaction authorization request. The current transaction authorization request is denied when the risk score indicates an unacceptable level of risk. In one embodiment, the data inputs further include performance data that is at least partially indicative of past fraudulent activities associated with the first account and at least one other account held by the account owner.
    • 披露了一种预测金融风险的方法。 该方法包括在第一计算系统上接收数据输入。 数据输入包括与至少向帐户所有者发行的第一帐户相关联的历史数据,历史数据包括第一帐户的历史交易信息。 该方法还包括基于至少历史数据生成预测模型,接收与第一计算系统上的第一帐户相关联的当前交易授权请求,以及通过将预测模型应用于与当前交易相关联的数据来生成风险分数 授权请求。 当风险分数表示不可接受的风险水平时,当前交易授权请求被拒绝。 在一个实施例中,数据输入还包括性能数据,该性能数据至少部分地指示与第一帐户相关联的过去欺诈活动以及帐户所有者持有的至少一个其他帐户。
    • 10. 发明授权
    • Risk assessment rule set application for fraud prevention
    • 风险评估规则设定防欺诈申请
    • US08924279B2
    • 2014-12-30
    • US12774521
    • 2010-05-05
    • Frederick LiuNancy HilgersMark NelsenKevin SiegelChristopher BrownThomas Dwyer
    • Frederick LiuNancy HilgersMark NelsenKevin SiegelChristopher BrownThomas Dwyer
    • G06Q40/00
    • G06Q20/4016G06Q20/40G06Q20/405
    • Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.
    • 应用于拒绝对可能的欺诈交易的授权的规则来自修改的患者规则诱导方法算法,该算法使用目标变量和与多个输入变量相关联的过去交易的数据集,以及包围多个输入变量的超矩形, 由输入变量值的表示定义的多维空间作为多维空间内的点。 虽然超矩形内的点的计数大于最小支持参数,但是去除超矩形边缘附近的第一多个点,其中每个这样的移除最大化目标变量的平均值,然后 当平均值保持最大时,添加靠近边缘的第二多个点,其中每个添加最大化或维持平均值。 超矩形在定义规则的最小边界框内是有界的。