Patents by Inventor Shane De Zilwa
Shane De Zilwa has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20210012418Abstract: A request to generate a responsibility score is received that characterizes a likelihood of a change in a level of creditworthiness of an individual in response to at least one unknown financial event. Such responsibility score can provide useful insight into a consumer that is complementary to a credit score. Thereafter, a responsibility score is generated based on historical creditworthiness data for the individual using at least one predictive model. The at least one predictive model was trained using historical creditworthiness data of a plurality of consumers subjected to a plurality of financial events. In addition, the at least one predictive model associates the historical creditworthiness data of the individual with matching states for each of a plurality of pre-defined performance behaviors—with each pre-defined performance behavior having at least two corresponding states. The responsibility score can be later provided to a user (e.g., persisted, transmitted, displayed, etc.).Type: ApplicationFiled: June 22, 2020Publication date: January 14, 2021Inventors: Jeffrey A. Feinstein, Wei Jiang, Ryan Morrison, Shane De Zilwa
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Publication number: 20200381130Abstract: Systems and methods for machine learning of voice and other attributes are provided. The system receives input data, isolates predetermined sounds from isolated speech of a speaker of interest, summarizes the features to generate variables that describe the speaker, and generates a predictive model for detecting a desired feature of a person Also provided are systems and methods for detecting one or more attributes of a speaker based on analysis of audio samples or other types of digitally-stored information (e.g, videos, photos, etc.).Type: ApplicationFiled: June 1, 2020Publication date: December 3, 2020Applicant: Insurance Services Office, Inc.Inventors: Erik Edwards, Shane De Zilwa, Nicholas Irwin, Amir Poorjam, Flavio Avila, Keith L. Lew, Christopher Sirota
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Publication number: 20200380957Abstract: Systems and methods for machine learning of voice and other attributes are provided. The system receives input data, isolates predetermined sounds from isolated speech of a speaker of interest, summarizes the features to generate variables that describe the speaker, and generates a predictive model for detecting a desired feature of a person Also provided are systems and methods for detecting one or more attributes of a speaker based on analysis of audio samples or other types of digitally-stored information (e.g, videos, photos, etc.).Type: ApplicationFiled: June 1, 2020Publication date: December 3, 2020Applicant: Insurance Services Office, Inc.Inventors: Erik Edwards, Shane De Zilwa, Nicholas Irwin, Amir Poorjam, Flavio Avila, Keith L. Lew, Christopher Sirota
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Patent number: 8645301Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: GrantFiled: December 10, 2012Date of Patent: February 4, 2014Assignee: Fair Isaac CorporationInventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott M. Zoldi, Shane De Zilwa
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Publication number: 20130103629Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: ApplicationFiled: December 10, 2012Publication date: April 25, 2013Inventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi, Shane De Zilwa
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Patent number: 8332338Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: GrantFiled: February 17, 2012Date of Patent: December 11, 2012Assignee: Fair Isaac CorporationInventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi, Shane De Zilwa
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Publication number: 20120150779Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: ApplicationFiled: February 17, 2012Publication date: June 14, 2012Inventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi, Shane De Zilwa
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Patent number: 8200595Abstract: Data characterizing a plurality of sensor generated events is received. Thereafter, analysis of the plurality of events is initiated using a decision tree with splits performed on decision keys. A first portion of the decision keys comprising analyst-selected splits can be derived from user-generated domain knowledge regarding a first plurality of historical events. A second portion of the decision keys comprising software-driven splits can be derived from a predictive model trained using a second plurality of historical events. Later, a disposition is determined for each event based on a traversal of at least one of the decision keys in the decision tree and such disposition is later initiated. Related apparatus, systems, techniques and articles are also described.Type: GrantFiled: January 26, 2009Date of Patent: June 12, 2012Assignee: Fair Isaac CorporationInventors: Shane De Zilwa, William P. Groves, Chiung-Chi Wang, Ramya Raghunathan
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Publication number: 20120072334Abstract: A request to generate a responsibility score is received that characterizes a likelihood of a change in a level of creditworthiness of an individual in response to at least one unknown financial event. Such responsibility score can provide useful insight into a consumer that is complementary to a credit score. Thereafter, a responsibility score is generated based on historical creditworthiness data for the individual using at least one predictive model. The at least one predictive model was trained using historical creditworthiness data of a plurality of consumers subjected to a plurality of financial events. In addition, the at least one predictive model associates the historical creditworthiness data of the individual with matching states for each of a plurality of pre-defined performance behaviors—with each pre-defined performance behavior having at least two corresponding states. The responsibility score can be later provided to a user (e.g., persisted, transmitted, displayed, etc.).Type: ApplicationFiled: November 4, 2010Publication date: March 22, 2012Inventors: Jeffrey A. Feinstein, Wei Jiang, Ryan Morrison, Shane De Zilwa
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Patent number: 8121962Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: GrantFiled: April 25, 2008Date of Patent: February 21, 2012Assignee: Fair Isaac CorporationInventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi, Shane De Zilwa
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Patent number: 8027894Abstract: 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.Type: GrantFiled: December 28, 2007Date of Patent: September 27, 2011Assignee: Fair Isaac CorporationInventors: Jeffrey A. Feinstein, Shane De Zilwa
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Publication number: 20100268639Abstract: Data comprising a request to generate a migration score is received (for example, by a first computer system). The migration score characterizes a likelihood of a change in a level of creditworthiness of a consumer subsequent to generation of a current credit score. Thereafter, future credit score migration for the individual is estimated (for example, by the first computer system) using a predictive model trained using historical creditworthiness data derived from a plurality of individuals. The historical creditworthiness data includes, for each individual, a historical credit score and empirical performance data subsequent to a scoring date for the historical credit score. Thereafter, the estimated future credit score migration is associated (for example, by the first computer system) with a migration score. Provision of the migration score can then be initiated. Related apparatus, systems, techniques and articles are also described.Type: ApplicationFiled: April 16, 2009Publication date: October 21, 2010Inventors: Jeffrey A. Feinstein, Shane De Zilwa, Lisa M. Wice, Victor Wykoff, Sheng-Tzu P. Jui
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Publication number: 20090271343Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.Type: ApplicationFiled: April 25, 2008Publication date: October 29, 2009Inventors: Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi, Shane De Zilwa
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Publication number: 20090171757Abstract: 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.Type: ApplicationFiled: December 28, 2007Publication date: July 2, 2009Inventors: Jeffrey A. Feinstein, Shane De Zilwa
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Publication number: 20090171756Abstract: A request to generate a balance attriter risk score that characterizes a likelihood of a change in a level of creditworthiness of an individual following balance attrition is received. Thereafter, one or more creditworthiness indicators such as future credit balance increases (a proxy for the responsibility of the individual) are estimated for the individual using a predictive model trained using historical creditworthiness data of a plurality of balance attriters. These estimated future balance increases are then associated with a balance attriter risk score so that such score can be provided. Related apparatus, systems, techniques, and articles are also described.Type: ApplicationFiled: December 28, 2007Publication date: July 2, 2009Inventors: Shane De Zilwa, Jeffrey A. Feinstein