Predictive modeling of consumer financial behavior

US6430539B1 · kind B1 · utility

Assignee

• HNC Software · US

Inventors

• Michael A. Lazarus · San Diego, US
• A. U. Mattias Blume · San Diego, US
• Kenneth B. Brown · San Diego, US
• William R. Caid · San Diego, US
• Ted E. Dunning · San Diego, US
• Larry Peranich · San Diego, US
• Gerald R. Russell · San Diego, US
• Kevin Sitze · San Diego, US

Key dates

• Filing date: May 6, 1999
• Grant date: Aug 6, 2002
• Expiry date: May 6, 2019

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/0601
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

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.