Patents Assigned to Fair Isaac Corporation
  • Patent number: 11373190
    Abstract: 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.
    Type: Grant
    Filed: December 23, 2019
    Date of Patent: June 28, 2022
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott M. Zoldi, David Griegel
  • Patent number: 11367074
    Abstract: A system and method are disclosed, to distinguish fraudulent transactions from a legitimate transaction, predicated on the notion that the card is considered likely to be in state of fraud. The disclosed system and method can be activated as soon as an account has suspicious activity that causes a high score for potential fraud, but before a bank either can or needs to confirm fraud. The system or method is able to pinpoint the actual fraudulent transactions inside a window of potential fraudulent activity, using a specialized model referred to as the pinpoint model.
    Type: Grant
    Filed: October 28, 2016
    Date of Patent: June 21, 2022
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott M. Zoldi, Hila Hashemi, Todd Alan Smith
  • Patent number: 11354292
    Abstract: A system and method for analyzing coverage, bias and model explanations in large dimensional modeling data includes discretizing three or more variables of a dataset to generate a discretized phase space represented as a grid of a plurality of cells, the dataset comprising a plurality of records, each record of the plurality of records having a value and a unique identifier (ID). A grid transformation is applied to each record in the dataset to assign each record to a cell of the plurality of cells of the grid according to the grid transformation. A grid index is generated to reference each cell using a discretized feature vector. A grid storage for storing the records assigned to each cell of the grid is then created. The grid storage using the ID of each record as a reference to each record and the discretized feature vector as a key to each cell.
    Type: Grant
    Filed: May 16, 2018
    Date of Patent: June 7, 2022
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Shafi Rahman
  • Patent number: 11341449
    Abstract: Computer-implemented methods, systems and products for analytics and discovery of patterns or signals. The method includes a set of operations or steps, including collecting data from a plurality of data sources, the data having a plurality of associated data types, and filtering the collected data based on identifying viable data sources from which the data is collected. The method further includes prioritizing discovery objectives based on analyzing the filtering results, and enriching the filtered collected data from viable data sources according to the prioritized discovery objectives. The method further includes extracting one or more signals from the enriched data using one or more machine learning mechanisms in combination with qualified subject matter expertise input, and graphically displaying the extracted signals in a meaningful way to a human operator such that the human operator is enabled to understand importance of extracted signals.
    Type: Grant
    Filed: August 30, 2019
    Date of Patent: May 24, 2022
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Mary Krone, Ryan Weber, Ana Paula Azevedo Travassos, Laura Waterbury, Paulo Mei, Mayumi Assato, Shubham Kedia, Nitin Basant, Chisoo Lyons
  • Patent number: 11250499
    Abstract: Optimal strategies for providing offers to a plurality of customers are generated. 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 generate 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.
    Type: Grant
    Filed: July 24, 2015
    Date of Patent: February 15, 2022
    Assignee: Fair Isaac Corporation
    Inventor: Gerald Fahner
  • Patent number: 11210271
    Abstract: In one aspect, there is provided a system. The system may store instructions that result in operations when executed by the at least one data processor. The operations may include receiving raw transactional data, collating, and reading the raw transactional data from the plurality of data sources. The operations may further include randomly sampling the raw transactional data. The operations may further include transforming the raw transactional data into at least one resilient distributed dataset. The operations may further include mapping the at least one resilient distributed dataset with a corresponding unique key. The operations may further include aggregating the at least one resilient distributed dataset on a key field. The operations may further include iterating over a lookup table. The operations may further include aggregating the data lines corresponding to the unique key associated with the at least one resilient distributed dataset.
    Type: Grant
    Filed: August 20, 2020
    Date of Patent: December 28, 2021
    Assignee: Fair Isaac Corporation
    Inventors: Amit Vishnoi, Sourav Das
  • Patent number: 11164110
    Abstract: A testing framework associated with a decision metaphor model tool reads table profile files to generate requests for a test of a decision metaphor. The testing framework sends the requests for the test to a decision engine and receives responses for the requests for comparison against expected values and possible errors. The testing framework also outputs an output file that includes a result of the test, where the output file is formatted in a computer-displayable and user-readable graphical format.
    Type: Grant
    Filed: November 25, 2019
    Date of Patent: November 2, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventor: Pradeep Niranjan Ballal
  • Patent number: 11151450
    Abstract: Systems and methods that use a neural network architecture for extracting interpretable relationships among predictive input variables. This leads to neural network models that are interpretable and explainable. More importantly, these systems and methods lead to discovering new interpretable variables that are functions of predictive input variables, which in turn can be extracted as new features and utilized in other types of interpretable models, like scorecards (fraud score, etc.), but with higher predictive power than conventional systems and methods.
    Type: Grant
    Filed: May 21, 2018
    Date of Patent: October 19, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Shafi Rahman
  • Patent number: 11144834
    Abstract: A predictive analytics system and method in the setting of multi-class classification are disclosed, for identifying systematic changes in an evaluation dataset processed by a fraud-detection model by examining the time series histories of an ensemble of entities such as accounts. The ensemble of entities is examined and processed both individually and in aggregate, via a set of features determined previously using a distinct training dataset. The specific set of features in question may be calculated from the entity's time series history, and may or may not be used by the model to perform the classification. Certain properties of the detected changes are measured and used to improve the efficacy of the predictive model.
    Type: Grant
    Filed: October 9, 2015
    Date of Patent: October 12, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Jim Coggeshall, Yuting Jia
  • Publication number: 20210295175
    Abstract: Systems and methods for training a machine learning model implemented over a network configured to represent the machine learning model are provided. At least one or more directed edges connect the one or more nodes an edge representing a connection between a first node and a second node, the second node computing an activation depending on the values of activations on first nodes and values associated with the connections, the connection being either conforming or non-conforming. The machine learning model may be trained by iteratively adjusting parameters w and b, respectively associated with weights and biases associated with edges connecting computational nodes. Connections between nodes may be sparsified by adjusting the parameter w to a first value for non-conforming connections during the training phase to reduce complexity of the connections among the plurality of nodes, or to ensure the input-output function of the network adheres to additional constraints.
    Type: Application
    Filed: March 18, 2020
    Publication date: September 23, 2021
    Applicant: FAIR ISAAC CORPORATION
    Inventors: Matthew Bochner Kennel, Scott Michael Zoldi
  • Patent number: 11100506
    Abstract: A system and method for programmatically revealing misleading confidence values in Fraud Score is presented to protect artificial intelligence models from adversarial neural networks. The method is used to reduce an adversarial learning neural network model effectiveness. With the score manipulation implemented, the adversary models are shown to systematically become less successful in predicting the true behavior of the Fraud detection artificial intelligence model and what it will flag as fraudulent transactions, thus reducing the true fraud dollars penetrated or taken by adversaries.
    Type: Grant
    Filed: May 9, 2017
    Date of Patent: August 24, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Qing Liu
  • Patent number: 11100392
    Abstract: As part of neural network sensitivity analyses, 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.
    Type: Grant
    Filed: October 31, 2016
    Date of Patent: August 24, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Patent number: 11093988
    Abstract: 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.
    Type: Grant
    Filed: February 3, 2015
    Date of Patent: August 17, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott M. Zoldi, Stuart C. Wells
  • Patent number: 11093845
    Abstract: A method for detecting fraud and non-fraud pattern changes can be 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. 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. Feature contributors to pattern changes can be determined by analyzing the deviation metrics.
    Type: Grant
    Filed: May 22, 2015
    Date of Patent: August 17, 2021
    Assignee: Fair Isaac Corporation
    Inventors: Scott Zoldi, Yuting Jia, Heming Xu
  • Patent number: 11087339
    Abstract: Data for a plurality of entities that can be offered a plurality of products can be obtained. The data can include categorical data and numeric data. Based on business constraints, some of all of the data can be selected. The selected data can be converted to another set of numeric data, wherein the categorical values are converted to numeric values. Dimensions of the converted data can be reduced to generate another set of data. Based on this another set of data, clusters of entities can be formed. The products can be grouped by assigning a unique product identifier of each product to a corresponding cluster. This grouping of products can be used by a predictive model to predict a likelihood of an entity to purchase a particular product in a future time period. Related methods, apparatus, systems, techniques and articles are also described.
    Type: Grant
    Filed: October 9, 2017
    Date of Patent: August 10, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Amit Kiran Sowani, Eeshan Malhotra, Shafi Ur Rahman
  • Patent number: 11080722
    Abstract: Various systems and methods for managing multichannel content delivery are presented. A multichannel content server system may use an application programming interface (API) for interfacing with a plurality of end-user communication channels. An end-user interaction database may store interaction data for a plurality of end-users. An end-user-specific preference profile may be created based on a first end-user interaction received via a first end-user communication channel stored to the end-user interaction database for a particular end user. A request may be received originating from an end-user computing device of the end-user via a second end-user communication channel. A client-specific engagement profile may be loaded and evaluated based on the created end-user-specific preference profile. Based on the client-specific engagement profile evaluated based on the end-user-specific preference profile, content may be selected then transmission to an end-user system.
    Type: Grant
    Filed: September 21, 2016
    Date of Patent: August 3, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Benjamin Robert Werner, Charles Edward McDaniel, Jeanette Ann Groustra
  • Patent number: 11049012
    Abstract: A system and method to explain model behavior, which can benefit not only those seeking to meet regulatory requirements when using machine learning models but also help guide users of the model to assess and increase robustness associated with model governance processes. The method described utilizes changes in behavior of a time series to identify the latent factors that drive explanation.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: June 29, 2021
    Assignee: Fair Isaac Corporation
    Inventors: Scott Michael Zoldi, Chahm An
  • Patent number: 11042551
    Abstract: Systems and methods for generating concise explanations of scored observations that strike good, and computationally efficient, trade-offs between rank-ordering performance and explainability of scored observations are disclosed. The systems and methods described herein for explaining scored observations are based on a framework of partial dependence functions (PDFs), multi-layered neural networks (MNNs), and Latent Explanations Neural Network Scoring (LENNS).
    Type: Grant
    Filed: December 2, 2016
    Date of Patent: June 22, 2021
    Assignee: Fair Isaac Corporation
    Inventors: Gerald Fahner, Scott Michael Zoldi
  • Patent number: 11030222
    Abstract: In one aspect, a method for similarity sharding of datatype items is provided. The method includes a set of operations or steps, including parsing a datatype item into one or more tokens, extracting at least one selected token from the parsed datatype item, the at least one selected token comprising a character string including one or more characters. The method further includes standardizing the character string of the at least one selected token, extracting a first character from the one or more characters included in the at least one standardized selected token, and assigning the datatype item to a select shard of a plurality of shards via character distribution lookup based on the extracted first character.
    Type: Grant
    Filed: April 9, 2019
    Date of Patent: June 8, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Girish Kunjur, John R. Ripley
  • Patent number: 11023963
    Abstract: 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.
    Type: Grant
    Filed: October 29, 2018
    Date of Patent: June 1, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Michael Urban