Predictive modeling of consumer financial behavior

Details Predictive modeling of consumer financial behavior Predictive modeling of consumer financial behavior

G - Physics

06

F

G06F 7/02 (2006.01) G06Q 30/02 (2012.01)

Patent

CA 2619667

Predictive modeling of consumer financial behavior 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. Merchant vectors are clustered to form the merchant segments. Analysis of merchant segments details transaction rates, volumes and amounts for the segment and its individual merchants. For each merchant segment a predictive model is trained using consumer transaction data in selected past time periods to predict spending in subsequent time periods. The 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. Membership functions associate each consumer with one or more merchant segments. Analysis of the consumers associated with a segment allows for identification of 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.

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