Michael A Lazarus

US Patent:

6430539, Aug 6, 2002

Filed:

May 6, 1999

Appl. No.:

09/306237

Inventors:

Michael A. Lazarus - Del Mar CA
A. U. Mattias Blume - San Diego CA
Kenneth B. Brown - San Diego CA
William R. Caid - San Diego CA
Ted E. Dunning - San Diego CA
Larry S. Peranich - San Diego CA
Gerald R. Russell - San Diego CA
Kevin L. Sitze - San Diego CA

Assignee:

HNC Software - San Diego CA

International Classification:

G06F 1760

US Classification:

705 10, 706 6, 705 14, 705 26

Abstract:

Predictive modeling of consumer financial behavior is provided by application of consumer transaction data to predictive models associated with merchant segments. Merchant segments are derived from consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors representing specific merchants are clustered to form merchant segments in a vector space as a function of the degree to which merchants co-occur more or less frequently than expected. Each merchant segment is trained using consumer transaction data in selected past time periods to predict spending in subsequent time periods for a consumer based on previous spending by the consumer. Consumer profiles describe summary statistics of consumer spending in and across merchant segments. Analysis of consumers associated with a segment identifies selected consumers according to predicted spending in the segment or other criteria, and the targeting of promotional offers specific to the segment and its merchants.

US Patent:

6839682, Jan 4, 2005

Filed:

Oct 3, 2000

Appl. No.:

09/679022

Inventors:

Matthias Blume - San Diego CA, US
Michael A. Lazarus - Del Mar CA, US
Larry S. Peranich - San Diego CA, US
Frederique Vernhes - Encinitas CA, US
William R. Caid - San Diego CA, US
Ted E. Dunning - San Diego CA, US
Gerald R. Russell - San Diego CA, US
Kevin L. Sitze - San Diego CA, US

Assignee:

Fair Isaac Corporation - San Diego CA

International Classification:

G06F 1760

US Classification:

705 10, 706 6, 705 14, 705 26

Abstract:

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Consumer vectors are developed within the vector space, to represent interests of particular consumers by virtue of relative vector positions of consumer and merchant vectors. Various techniques, including clustering, supervised segmentation, and nearest-neighbor analysis, are applied separately or in combination to generate improved predictions of consumer behavior.

US Patent:

7165037, Jan 16, 2007

Filed:

Dec 14, 2004

Appl. No.:

11/012812

Inventors:

Michael A. Lazarus - Del Mar CA, US
Larry S. Peranich - San Diego CA, US
Frederique Vernhes - Encinitas CA, US
A. U. Mattias Blume - San Diego CA, US
Kenneth B. Brown - San Diego CA, US
William R. Caid - San Diego CA, US
Ted E. Dunning - San Diego CA, US
Gerald R. Russell - San Diego CA, US
Kevin L. Sitze - San Diego CA, US

Assignee:

Fair Isaac Corporation - San Diego CA

International Classification:

G06Q 10/00

US Classification:

705 10

Abstract:

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments, which are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur. Supervised segmentation is applied to merchant vectors to form merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. Consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.

US Patent:

7533038, May 12, 2009

Filed:

Jan 15, 2007

Appl. No.:

11/623266

Inventors:

Matthias Blume - San Diego CA, US
Michael A. Lazarus - San Diego CA, US
Larry S. Peranich - San Diego CA, US
Frederique Vernhes - Encinitas CA, US
Kenneth B. Brown - San Diego CA, US
William R. Caid - San Diego CA, US
Ted E. Dunning - San Diego CA, US
Gerald R. Russell - San Diego CA, US
Kevin L. Sitze - San Diego CA, US

Assignee:

Fair Isaac Corporation - Minneapolis MN

International Classification:

G06Q 10/00

US Classification:

705 10

Abstract:

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.

US Patent:

7849029, Dec 7, 2010

Filed:

Jun 2, 2006

Appl. No.:

11/421896

Inventors:

Theodore J. Crooks - San Diego CA, US
Uwe F. Mayer - Encinitas CA, US
Michael A. Lazarus - San Diego CA, US

Assignee:

Fair Isaac Corporation - Minneapolis MN

International Classification:

G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00

US Classification:

706 20

Abstract:

A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.

US Patent:

RE42577, Jul 26, 2011

Filed:

Mar 22, 2010

Appl. No.:

12/729215

Inventors:

Matthias Blume - San Diego CA, US
Michael A. Lazarus - Del Mar CA, US
Larry S. Peranich - San Diego CA, US
Frederique Vernhes - Encinitas CA, US
William R. Caid - San Diego CA, US
Ted E. Dunning - San Diego CA, US
Gerald S. Russell - San Diego CA, US
Kevin L. Sitze - San Diego CA, US

Assignee:

Kuhuro Investments AG, L.L.C. - Dover DE

International Classification:

G06Q 10/00

US Classification:

705 731

Abstract:

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.

US Patent:

7991716, Aug 2, 2011

Filed:

Dec 6, 2010

Appl. No.:

12/961478

Inventors:

Theodore J. Crooks - San Diego CA, US
Uwe F. Mayer - Encinitas CA, US
Michael A. Lazarus - San Diego CA, US

Assignee:

Fair Isaac Corporation - Minneapolis MN

International Classification:

G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00

US Classification:

706 20, 706 16, 706 25

Abstract:

A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.

US Patent:

RE42663, Aug 30, 2011

Filed:

Mar 22, 2010

Appl. No.:

12/729218

Inventors:

Michael Lazarus - Del Mar CA, US
Larry S. Peranich - San Diego CA, US
Frederique Vernhes - Encinitas CA, US
A. U. Matthias Blume - San Diego CA, US
William R. Caid - San Diego CA, US
Ted E. Dunning - San Diego CA, US
Gerald R. Russell - San Diego CA, US
Kevin Sitze - San Diego CA, US

Assignee:

Kuhuro Investments AG, L.L.C. - Dover DE

International Classification:

G06Q 10/00

US Classification:

705 10

Abstract:

Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments, which are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur. Supervised segmentation is applied to merchant vectors to form merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. Consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.