San Jose, CA, United States
San Jose, CA, United States

FICO is a Software company based in San Jose, California and founded by Bill Fair and Earl Isaac in 1956. Its FICO score, a measure of consumer credit risk, has become a fixture of consumer lending in the United States. In 2013, lenders purchased more than 10 billion FICO scores and about 30 million American consumers accessed their scores themselves. Wikipedia.


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Patent
FICO (Fair Isaac Corporation) | Date: 2015-09-21

A computer-implemented method of fraud detection includes clustering samples on the tree nodes in the decision tree model on the training dataset, calculating the cluster centroids and determining the high fidelity radius for a preset threshold probability for each cluster and determining the left-over class probability for each node. The new transactional data is classified in three steps: first to determine based on the decision tree what leaf node the transaction is associated, second to determine the membership to a cluster of the leaf node using the shortest distance to the cluster centroid and then third to compare the distance with the high fidelity radius and then to determine the eventual class probability for a new data. The new method demonstrates better performance than the decision-tree alone model.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-07-24

Generating optimal strategies for providing offers to a plurality of customers is described. A plurality of categorical attributes (for example, gender and residential status) and ordinal attributes (for example, risk score and credit line utilization) can be determined. Values of one of more categorical attributes can be changed as per a transition probability table. Some probabilities can be varied to determine a first tradeoff, based on which a first updated strategy can be generated. Further, noise can be added to one or more ordinal attributes. Standard deviation of a noise distribution associated with the noise can be varied so as to determine a second tradeoff, based on which a second updated strategy can be generated. The second updated strategy can be an update of the first updated strategy. Offers can be provided to the plurality of customers in accordance with the second updated strategy.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-02-18

Data is received that characterizes at least one of credit, financial, and demographic data for a consumer. Thereafter, estimated income is determined for the user. Using the estimated income and the data, a second income level for the consumer is determined also using a confidcnce interval model and a pre-defined confidence thereshold Ci. The second income level for the consumer is less than the determined estimated income and is determined such that actual income for the consumer is Ci % likely to exceed the second income level. Data can then be provided that characterizes the second income level. Related apparatus, systems, techniques and articles are also described.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-07-10

The subject matter disclosed herein provides methods, apparatus, systems, techniques, and articles for determining the likelihood that a transaction is abnormal. Time-series data associated with active and passive operations of a mobile device and out of band data associated with the user of the mobile device can be collected. The collected data can be processed to generate a set of mobile attribute data that define a behavior of one or more of the user and the mobile device. A profile containing profile variables for selected attributes from the set of mobile attribute data can be generated. The profile can summarize past usage of the user or the mobile device. A set of one or more transactions associated with the mobile device can be monitored. A first score representing a degree to which the transaction is abnormal can be generated. Related apparatus, systems, techniques, and articles are also described.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-11-12

A configuration package receives user-generated input that configures a decision service to generate decision data. The configuration package includes artifacts and the user-generated input selects the artifacts from an artifact library in a configuration database. A configured decision service is generated, where the generating includes receiving, by a decision service factory, the configuration package. Also, the decision service factory receives a decision template including configurable decision elements and non-configurable decision elements. Further, the decision service factory receives a user configuration specifying a parameter in the corresponding artifact. The artifact from the configuration package, the user configuration and the decision template are combined to generate the configured decision service. The configured decision service receives, from a client computer, input for each of the configurable decision elements. Based on the received input, the decision data is generated by the configured decision service. The generated decision data is transmitted to the client computer.


A task worker running on a worker server receives a process specification over a network. The process specification specifies a task to be executed by the task worker. The executed task includes generating an output data object for an output data stream based in part on an input data object from an input data stream. The process specification is accessed to specify the required fields to be read from for executing the task and to specify the generated the fields in the input data object that will be written to during or subsequent to the executing of the task. The task worker executes the task and generates the output data object. The output data object is then transmitted to the output stream based on the stream configuration.


A data object from a data source is received by a distributed process in a data stream. The distributed process has a sequence of categories, each category containing one or more tasks that operate on the data object. The data object includes files that can be processed by the tasks. If the task is able to operate on the data object, then the data object is passed to the task. If the task is unable to operate on the data object, then the files in the data object are passed to a file staging area of the distributed process and stored in memory. The files in the file staging area are passed, in sequence, from the file staging area to the task that was unable to operate on the data object. The data object is outputted to a next category or data sink after being operated on by the task.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-02-03

A biometric measures profiling analytics system and method are presented. The system and method include collecting biometric data associated with a consumer, and determining one or more biometric variables representing a measurable aspect of the biometric data. The system and method further include generating, based on at least one of the one or more biometric variables, at least one biometric profile variable associated with the consumer, the at least one biometric profile variable representing a degree of normality or abnormality of the collected and calibrated biometric data as compared to a biometric history of the consumer. The system and method further include generating a behavioral score for the consumer based on the collected and calibrated biometric data and with at least one biometric profile variable, the behavioral score representing a degree of risk of normality or abnormality of an event associated with the biometric data.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-05-29

The subject matter disclosed herein provides methods, apparatus, systems, techniques, and articles for false positive reduction in abnormality detection models. A date and time of a first transaction by a transaction entity and associated with a transaction characteristic can be stored. Data representing subsequent transactions associated with the transaction characteristic can be stored. A history marker profile specific to the transaction characteristic and transaction entity can be generated and can include the transaction characteristic, the date and time of the first transaction, and maximum and mean abnormality scores. A date and time of a current transaction can be determined. A current abnormality score for the current transaction can be received. A tenure of the observed transaction characteristic can be computed. The current abnormality score can be recalibrated from the transaction entity abnormality detection system according to the maximum, mean, and current abnormality scores and a length of the tenure.


Patent
FICO (Fair Isaac Corporation) | Date: 2015-05-22

The subject matter disclosed herein provides methods for detecting fraud and non-fraud pattern changes based on transaction pathway transversal analysis. A decision tree can be built based on a training dataset from a reference dataset. Pathway transversal information can be recorded along each pathway for the reference dataset. A first mean and a first variance of a class probability can be calculated of all samples over each pathway. A pathway distribution for a new transaction dataset under investigation and a second mean and a second variance of all samples of the new transaction dataset can be obtained. The second mean and the second variance can represent a fraud probability. A first pathway density distribution can be retrieved for the reference dataset. A second pathway density distribution can be generated for the new transaction dataset. Deviation metrics between the first pathway density distribution and the second pathway density distribution can be determined on a global level and on a local level. The deviation metrics between one or more feature statistics of a feature along each pathway for the reference dataset and the new dataset can be determined on a local level. One or more likely feature contributors to one or more pattern changes can be determined by analyzing the deviation metrics along each pathway. One or more of an alert and a report can be generated based on the deviation metrics according to one or more predetermined criteria. Related apparatus, systems, techniques, and articles are also described.

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