FAIR ISAAC CORPORATION Patent applications |
Patent application number | Title | Published |
20150348202 | Insurance Claim Outlier Detection with Kernel Density Estimation - Data is received that comprises a data set characterizing a plurality of insurance claims. Thereafter, a density function of the data set is estimated using kernel density estimation. At least one claim having at least one outlier variable is then identified using the density function. Data is then provided (e.g., displayed, stored, loaded into memory, transmitted to a remote computing system, etc.) that characterizes the at least one identified claim as likely being fraudulent or erroneous. Related apparatus, systems, techniques and articles are also described. | 12-03-2015 |
20150293750 | Efficiently Representing Complex Score Models - Data is received that characterizes a score model. Thereafter, the score model is normalized by transforming it into a directed acyclic graph. The directed acyclic graph is then transformed into a structured rules language program. The structured rules language program is then transformed into a program using a concurrent, class-based, object-oriented computer programming language (e.g., JAVA, C, COBOL, etc.). Related apparatus, systems, techniques and articles are also described. | 10-15-2015 |
20150254568 | Boosted Ensemble of Segmented Scorecard Models - Data is received that include values that correspond to a plurality of variables. A score is then generated based on the received data and using a boosted ensemble of segmented scorecard models. The boosted ensemble of segmented scorecard models includes two or more segmented scorecard models. Subsequently, data including the score can be provided (e.g., displayed, transmitted, loaded, stored, etc.). Related apparatus, systems, techniques and articles are also described. | 09-10-2015 |
20150195299 | CYBER SECURITY ADAPTIVE ANALYTICS THREAT MONITORING SYSTEM AND METHOD - A system and method of detecting command and control behavior of malware on a client computer is disclosed. One or more DNS messages are monitored from one or more client computers to a DNS server to determine a risk that one or more client computers is communicating with a botnet. Real-time entity profiles are generated for at least one of each of the one or more client computers, DNS domain query names, resolved IP addresses of query domain names, client computer-query domain name pairs, pairs of query domain name and corresponding resolved IP address, or query domain name-IP address cliques based on each of the one or more DNS messages. Using the real-time entity profiles, a risk that any of the one or more client computers is infected by malware that utilizes DNS messages for command and control or illegitimate data transmission purposes is determined. One or more scores are generated representing probabilities that one or more client computers is infected by malware. | 07-09-2015 |
20150161623 | GENERATING CUSTOMER PROFILES USING TEMPORAL BEHAVIOR MAPS - A customer profile is generated for a customer performing one or more transactions using temporal behavior maps in order to determine a score that can be used by an entity to determine offers for the customer. The temporal behavior maps can characterize a purchase behavior of the customer. Related apparatus, systems, techniques and articles are also described. | 06-11-2015 |
20150081606 | Reduction of Computation Complexity of Neural Network Sensitivity Analysis - As part of neural network sensitivity analysis, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described. | 03-19-2015 |
20150046317 | Customer Income Estimator With Confidence Intervals - 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 confidence interval model and a pre-defined confidence threshold 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. | 02-12-2015 |
20140324522 | Detecting Fraud In Internet-Based Lead Generation Utilizing Neural Networks - Artificial neural network models trained using historical lead data are used to identify leads that are likely to be fraudulent or inaccurate and to additionally identify lead sources that provide leads likely to be fraudulent or inaccurate. Related apparatus, systems, techniques and articles are also described. | 10-30-2014 |
20140310159 | REDUCED FRAUD CUSTOMER IMPACT THROUGH PURCHASE PROPENSITY - A method, system and computer program product for reduced fraud customer impact through purchase propensity is disclosed. A probability estimate of spending by a consumer in a merchant transaction category is computed based on historical transaction data and consumer profile data, and a propensity score for the merchant transaction is generated. The propensity score represents a propensity for the consumer to conduct the merchant transaction. The propensity score is combined in a fraud model operating in a real-time transaction stream. The fraud score can be adjusted in accordance with the propensity score. | 10-16-2014 |
20140222506 | CONSUMER FINANCIAL BEHAVIOR MODEL GENERATED BASED ON HISTORICAL TEMPORAL SPENDING DATA TO PREDICT FUTURE SPENDING BY INDIVIDUALS - A method for selecting a next action includes reading transaction data, determining insights and relationships between a first entity and a second entity from the collected transaction data. Once these relationships and insights have been determined, the possibility of a future event occurring in one of a number of selected time periods can be determined using a predictive time-to-event component. A system for selecting a next action includes a memory for storing transaction data, an insight/relationship determination module, and a predictive time-to-event module. The memory, the insight/relationship determination module and the predictive time-to-event module carry out the above method. A programmable media having an instruction set can also cause a machine to carry out the above method. | 08-07-2014 |
20140180974 | Transaction Risk Detection - The current subject matter describes scoring of transactions associated with a profiling entity so as to determine risk associated with the transactions. Data characterizing at least one new transaction can be received. A latent dirichlet allocation (LDA) model trained on historical data can be obtained. Based on new words in the received data, the LDA model can update a topic probability mixture vector. Based on the updated topic probability mixture vector, numerical values of one or more predictive features can be calculated. Based on the numerical values of the one or more predicted features, the at least one transaction in the received data can be scored. Related apparatus, systems, techniques and articles are also described. | 06-26-2014 |
20140180649 | Scorecard Models with Measured Variable Interactions - Data is received that characterizes a transaction and includes a plurality of values corresponding to variables. Thereafter, a score is determined for the transaction based on the received data and using a scoring model. The scoring model only uses variables pairs having a divergence residual above a pre-defined threshold. Thereafter, data is provided that characterizes the determined score. Related apparatus, systems, techniques and computer program products are also described. | 06-26-2014 |
20140156347 | Enhanced Market Basket Analysis - The current subject matter describes a generation of a score based on an enhanced market basket analysis (eMBA). An eMBA model can receive historical data characterizing historical purchases of a plurality of products over a specified time-period. In response, the eMBA model can generate baskets, which can include data that is causal and predictive. The generated baskets can be provided as an input to a group generator. The group generator can then generate product groups and confidence values. The product groups and confidence values can be provided to a score generator. In run-time, the score generator can receive current product data, and in return, can use the product groups and confidence values to generate a score. The score can characterize a likelihood of a purchase of the product by a corresponding customer associated with the product group. Related methods, apparatuses, systems, techniques and articles are also described. | 06-05-2014 |
20140149142 | Detection of Healthcare Insurance Claim Fraud in Connection with Multiple Patient Admissions - A scoring model is provided that is trained using historical patient readmission data. The scoring model is used to analyze patient insurance claim data for which patients were readmitted to a healthcare facility in order to characterize whether the corresponding insurance claims are potentially fraudulent or erroneous. Related techniques, apparatus, systems, and articles are also described. | 05-29-2014 |
20140044248 | NETWORK ASSURANCE ANALYTIC SYSTEM - A network assurance analytics (NAA) system and method is disclosed. The NAA can be part of a risk analytic for telecom (RAFT) program. The NAA system is configured to monitor telecommunications networks, detect errors or fraud in those telecommunications networks, and provide solutions to resolve the errors or reduce the fraud. Traffic of a telecommunications network is electronically monitored for at least one pattern that is indicative of a telecommunications anomaly. Based on a set of a set of telecommunications profiles stored in a database, a model score representing a value of the telecommunications anomaly is generated. A solution for the telecommunications network to reduce the model score associated with the telecommunications anomaly is then generated for execution on the telecommunications network. | 02-13-2014 |
20140032333 | Scoring Consumer Transaction Consistency and Diversity - A time interval during which to present an offering to a consumer is determined using a cadence consistency score calculated for the consumer. In addition, it is determined which of a plurality of items to offer to the consumer is determined using an item diversity score calculated for the consumer. Thereafter, provision an offering for the determined item during the determined time interval is initiated. Related apparatus, systems, techniques and articles are also described. | 01-30-2014 |
20130117081 | Lead Fraud Detection - Data is received that characterizes one or more leads. Thereafter, it is determined, for each of the one or more leads, whether the lead is likely to be fraudulent and/or inaccurate using at least one predictive model. In some implementations, one or more of the utilized predictive models can be trained using a plurality of historical leads with known fraud or accuracy data. Data can be later provided that identifies and/or includes one or more of (i) those leads that are determined to be fraudulent and/or inaccurate and (ii) those leads that are determined not to be fraudulent and/or inaccurate. Related apparatus, systems, techniques and articles are also described. | 05-09-2013 |
20120173465 | Automatic Variable Creation For Adaptive Analytical Models - A system and method for automated variable creation for adaptive fraud analytics are disclosed. A data structure for creation of rules is generated. The data structure represents nodes and associations between nodes from inputs for fraud/non-fraud conditions, and is generated from fraud and non-fraud data collected in an adaptive modeling process from past transactions. All unique paths between nodes of the data structure are determined to define a rule for each path. Each rule is then converted to a binary indicator variable to generate a set of binary indicator variables, and one or more complex variables is derived from the set of binary indicator variables. The one or more binary indicator variables and one or more complex variables can be provided to an adaptive scoring engine to score new transactions or to predict future behaviors. | 07-05-2012 |
20120078681 | MULTI-HIERARCHICAL CUSTOMER AND PRODUCT PROFILING FOR ENHANCED RETAIL OFFERINGS - The current subject matter provides the ability to infer a richer customer profile using purchase transaction data in conjunction with various hierarchical groupings of products as well as an ability to characterize products such that they can be used to enrich customer profiles. Related apparatus, systems, techniques and articles are also described. | 03-29-2012 |
20110288989 | TIME-EFFICIENT AND DETERMINISTIC ADAPTIVE SCORE CALIBRATION TECHNIQUES FOR MAINTAINING A PREDEFINED SCORE DISTRIBUTION - A system and method for maintaining a pre-defined score distribution for financial transactions are disclosed. A number of memory spaces are defined for a memory structure. Transaction data for the financial transactions is received by the system. Each of the financial transactions is scored based on the transaction data to generate a batch of scores for the financial transactions. A score range is divided into k bins, where each of the k bins representing one memory space of the memory spaces of the memory structure. The batch of scores are aggregated by storing a count of each score of the batch of scores in an associated memory space of the plurality of memory spaces, and a percentile is computed for each score in the batch of scores based on a set of values associated with the count of each score. Each new financial transaction is scored to generate a new score, and a new percentile is assigned to the new score according to the set of values. The percentile of the new score is translated to a calibration score with fixed percentile characteristics according to a fixed reference curve. | 11-24-2011 |
20110264459 | HEALTHCARE INSURANCE CLAIM FRAUD DETECTION USING DATASETS DERIVED FROM MULTIPLE INSURERS - Various techniques are described that enable a smaller insurer (or an insurer with a less developed dataset) to be able to characterize whether certain healthcare insurance claim elements are potentially fraudulent or erroneous. Datasets from larger insurers (with well developed datasets) and/or datasets from a consortium of insurers can be leverage by the smaller insurer. Related techniques, apparatus, systems, and articles are also described. | 10-27-2011 |
20110137847 | CAUSAL MODELING FOR ESTIMATING OUTCOMES ASSOCIATED WITH DECISION ALTERNATIVES - A method and system for estimating potential future outcomes resulting from decision alternatives is presented to enable lenders to make lending related decisions. The estimation is based on a propensity score variable that encompasses an effect of multiple covariates associated with one or more individuals for whom the estimation is being performed. For consistency with empirical testing, the estimation approach assumes conditions of unconfoundedness and localized common support. According to the unconfoundedness assumption, for a given variable, the potential outcomes are conditionally independent of the decision alternatives. According to the localized common support assumption, an overlap is ensured between individual accounts that are categorized together as potentially having the same future outcome. The outcomes and an effect (e.g. comparison) of the outcomes may be displayed graphically. | 06-09-2011 |
20090148833 | DEVICES FOR GENERATING DETECTABLE POLYMERS - This document provides systems, devices, and methods involved in generating detectable polymers. For example, diagnostic systems, diagnostic devices, primer systems, and collections of primer systems are provided. | 06-11-2009 |
20090044279 | Systems and methods for fraud detection via interactive link analysis - Fraud detection is facilitated by developing account cluster membership rules and converting them to database queries via an examination of clusters of linked accounts abstracted from the customer database. The cluster membership rules are based upon certain observed data patterns associated with potentially fraudulent activity. In one embodiment, account clusters are grouped around behavior patterns exhibited by imposters. The system then identifies those clusters exhibiting a high probability of fraud and builds cluster membership rules for identifying subsequent accounts that match those rules. The rules are designed to define the parameters of the identified clusters. When the rules are deployed in a transaction blocking system, when a rule pertaining to an identified fraudulent cluster is triggered, the transaction blocking system blocks the transaction with respect to new users who enter the website. | 02-12-2009 |
20080208719 | Expert system for optimization of retail shelf space - A business rules engine works with an optimization engine through various user interfaces to facilitate increased efficiency in retail space planning. Rules and models are built from templates that are stored in a repository. Business analysts and retail space planners both have access to the repository to develop models and rules. A project consists of a selection of rules and models from the repository along with selected data from various data sources. A scenario is created for the project by specifying constraints, parameters, and optimization objectives. The optimization engine processes the scenario and attempts to find an optimum solution. when a perfect solution (100%) cannot be found, the optimization engine evaluates the various criteria in the scenario and relaxes requirements until an acceptable solution is found. The output of the optimization engine can automatically be provided as graphical visualizations such as plan-o-grams, graphs, charts, and other forms. | 08-28-2008 |