Fair Isaac Corporation

Other

Lexisnexis Risk Solutions Fl Inc.

Lexisnexis Risk Solutions, Inc.

Jeffrey Allen Feinstein

Shane De Zilwa

James Christiansen

Gary J Sullivan

Fang Yuan

Michael Raymond Cohen

Brent Wayne Sorenson

Michael James Woodberry

Eric Graves

Chenyang Lian

Jennifer Elizabeth Jack

Sharon Barnard

Jesse C P B Shaw

Lara D Mercurio

Jesse Cpb Shaw

An apparatus for grooming an animal is disclosed herein. The apparatus for grooming the animal includes a handle and a grooming-head. In a preferred embodiment, the handle is ergonomically shaped to aid in grip-ability of the handle. In one embodiment, the grooming-head includes a first grooming-side having a first grooming-tool. In another embodiment, the grooming-head further includes a second grooming-side opposite the first grooming-side and including a second grooming-tool. Further, in the preferred embodiment, the first grooming-tool and the second grooming-tool are dissimilar. The apparatus is useful for providing effective multifunctional grooming of horses, canines, livestock, etc., saving time and effort while currying.

Animal grooming apparatus

The disclosed technology includes systems and methods for identifying synthetic identities among a population of entity representations in an electronic database. The method includes include selecting a first entity representation, and for the selected first entity representation, identifying one or more network chains formed by one or more connections between the first entity representation, a second entity representation, and zero or more intervening entity representations; and determining a number of connections per connection degree for a predetermined number of degrees in at least one of the identified one or more network chains; determining, based on the number of connections per connection degree, an indication that one or more of the first entity representation, the second entity representation, and zero or more of the intervening entity representations is a synthetic identity; and outputting entity representation information of one or more entities in the population that are indicated as a synthetic identity.

Systems and methods for entity network analytics using geometric growth rate analysis

Input characterizing one or more economic indicators and a portfolio of accounts can be used to estimate a portfolio level effect of the economic indicators on the portfolio of accounts is estimated. Based on this estimation, an account level effect of the economic indicators is simulated for each of the accounts. The overall affect of the simulated account level effects approximates the portfolio level effect. Simulated account level effects can thereafter be aggregated in order to characterize future risk for the portfolio of accounts. Related apparatus, systems, techniques and articles are also described.

Account portfolio risk characterization

Certain embodiments of the invention may include systems, methods, and apparatus for determining fraud risk associated with a credit application. According to an exemplary embodiment of the invention, a method is provided for receiving applicant information associated with the application; searching one or more consumer identity repositories for prior usage of the applicant information; generating a plurality of identity characteristics corresponding to the prior usage of the applicant information; assigning the application to one of a plurality of segments based at least in part on the searching; scoring the application with a predictive scoring model to determine a risk score based at least in part on the identity characteristics; determining identity fraud risk types associated with the application; and outputting the risk score and one or more indicators of the determined identity fraud risk types.

Systems and methods for segmented risk scoring of identity fraud

Predicting impact of future actions on subsequent creditworthiness involves developing a prediction model that predicts a statistical interaction of performance expectation with likely post-scoring behavior. Including sensitivity to new, post-scoring date credit behaviors in the analytic solution greatly improves snapshot score predictions. The modeling approach involves multiple snapshots: predictive and performance snapshots, plus an intermediate snapshot shortly after the predictive snapshot to quantify interim consumer behavior post-scoring date. Predictive interaction variables are calculated on the predictive data using simulated consumer profiles before and after assuming a sizeable simulated balance to infer the consumer's tolerance for incremental future debt. Using an adjustor approach in predicting capacity allows isolation of the confounding effect of risk from the capacity determination. A resulting capacity index can be used to rank order originations and line increases according to capacity in consumer, bankcard, automobile and mortgage lending.

Method and apparatus system for modeling consumer capacity for future incremental debt in credit scoring

A request to generate a consolidation risk score that characterizes a likelihood of a change in a level of creditworthiness of an individual following a consolidation of debt of the individual using a secured line of credit is received. Thereafter, future credit balance increases are estimated for the individual using a predictive model trained using historical creditworthiness data of a plurality of consolidators. These estimated future balance increases are then associated with a consolidation risk score so that such score can be provided. Related apparatus, systems, techniques, and articles are also described.

Modeling responsible consumer debt consolidation behavior

A method and system for predicting impact of future actions on subsequent performance involves developing a prediction model that predicts a statistical interaction of performance expectation with likely behavior. In one embodiment, sensitivity to new, post-scoring date credit behaviors in the analytic solution greatly improves snapshot score predictions. The modeling approach involves multiple snapshots: predictive and performance snapshots, plus an intermediate snapshot shortly after the predictive snapshot to quantify interim behavior. Predictive interaction variables are calculated on the predictive data using simulated profiles before and after an action.

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Roswell, GA, United States of America

Jeffrey Allen Feinstein