System and Method for Predicting Card Member Spending Using Collaborative Filtering

Abstract

The disclosed method and system allows a credit or charge card issuer to provide its card members with a list of restaurants that might be of interest based on the financial transactions of similar card members. In one instance, this method filters financial transaction data from a plurality of card members that involves a plurality of restaurants to generate a set of candidate restaurant recommendations for a selected card member. This set of candidate restaurant recommendations is processed to yield a list of restaurant recommendations for the selected customer that is prioritized on the basis of the selected card member accepting the recommendation. The list of restaurant recommendations is then reported to the selected card member to enhance card use and marketing.

1 . A method, comprising:
 filtering, by a computer for filtering financial transaction data, a data set to generate a set of candidate merchants for a selected account holder; and   generating, by the computer, for the selected account holder, a probability of acceptance for each of the candidate merchants, wherein the probability of acceptance is based upon a number of account holders having transactions with both the candidate merchant and an identified merchant and based upon a total number of account holder transactions with the identified merchant.   
     
     
         2 . The method of  claim 1 , wherein the filtering further comprises:
 identifying merchants within a plurality of merchants that have at least one financial transaction with the selected account holder over a period of time;   determining, for each non-identified merchant within the plurality of merchants, a strength of association between each identified merchant and each non-identified merchant;   generating the set of candidate merchants based on at least the strengths of association; and   filtering the set of candidate merchants according to at least one of: (i) an average transaction size and (ii) geographic location.   
     
     
         3 . The method of  claim 2 , wherein the filtering the set of candidate merchants according to average transaction size further comprises:
 obtaining an average transaction size for each candidate merchant over the period of time;   determining an average transaction size for the identified merchants over the period of time; and   eliminating merchants from the set of candidate merchants based on at least the average transaction size of the candidate merchant.   
     
     
         4 . The method of  claim 3 , further comprising before the generating of a probability of acceptance, eliminating merchants from the set of candidate merchants whose average transaction size varies from the computed average transaction size by more than a predetermined amount. 
     
     
         5 . The method of  claim 2 , wherein the filtering the set of candidate merchants according to location further comprises:
 obtaining, for each identified merchant, a distance traveled by the selected account holder when visiting the identified merchant;   determining a standard deviation for the obtained travel distances; and   eliminating merchants from the set of candidate merchants based on at least the computed standard deviation of the obtained travel distances.   
     
     
         6 . The method of  claim 5 , further comprising, before the generating of a probability of acceptance, eliminating merchants from the set of candidate merchants based on the distance between the candidate merchant and the account holder billing address exceeding the computed average distance by a predetermined amount. 
     
     
         7 . The method of  claim 1 , wherein the generating further comprises prioritizing each merchant within the set of candidate merchants based on the computed probability of acceptance of the candidate merchant to generate the list of recommended merchants. 
     
     
         8 . The method of  claim 1 , further comprising:
 determining, for each identified merchant, a probability that the selected account holder will have future financial transactions with the identified merchant;   determining, for each identified merchant and for each candidate merchant, a probability that account holders within a plurality of account holders will have financial transactions at both the identified and the candidate merchants; and   determining, for each candidate merchant, the probability that the selected account holder will have multiple financial transactions at the candidate merchant based on: (i) the probability that the selected account holder will have future financial transactions with the identified merchant and (ii) the probability that the other account holders will have financial transactions at both the identified and the candidate merchant,   wherein the probability of acceptance represents the probability that the selected account holder will have multiple future financial transactions involving the candidate merchant.   
     
     
         9 . The method of  claim 8 , wherein the probability that the selected account holder will have a future financial transaction with the identified merchant represents a ratio of a total number of financial transactions involving the selected account holder and the identified merchant to a total number of financial transactions involving the selected account holder. 
     
     
         10 . The method of  claim 8 , wherein the probability that account holders will have financial transactions at both the identified merchant and the candidate merchant represents a ratio of a number of financial transactions involving the identified merchant and the candidate merchant to the total number of financial transactions involving the identified merchant. 
     
     
         11 . The method of  claim 1 , further comprising determining an adventurousness measure of the account holder at least partially based on the determined probability of acceptance for the candidate merchant. 
     
     
         12 . The method of  claim 1 , wherein the data set corresponds to the selected account holder of a plurality of account holders. 
     
     
         13 . The method of  claim 1 , wherein the data set corresponds to financial transactions of a plurality of account holders with a plurality of merchants. 
     
     
         14 . The method of  claim 1 , wherein the probability of acceptance (P) is determined by: P=A+(B*(A−K)), wherein:
 A is a number of account holders having transactions with both the candidate merchant and an identified merchant; 
 K is a constant; 
 B is a value corresponding to a ratio of A to a total number of account holder transactions with the identified merchant; and 
 a value of (A−K) is set to zero if its determined value results in a negative number. 
 
     
     
         15 . A computer readable storage medium comprising a non-transitory, tangible computer useable storage medium having computer executable instructions recorded thereon, when executed by a computer for filtering financial transaction data, cause the computer to perform operations comprising;
 filtering, by the computer, a data set to generate a set of candidate merchants for a selected account holder; and   generating, by the computer, for the selected account holder, a probability of acceptance for each of the candidate merchants, wherein the probability of acceptance is based upon a number of account holders having transactions with both the candidate merchant and an identified merchant and based upon a total number of account holder transactions with the identified merchant.   
     
     
         16 . The medium of  claim 15 , wherein the filtering further comprises:
 identifying merchants within a plurality of merchants that have at least one financial transaction with the selected account holder over a period of time;   determining, for each non-identified merchant within the plurality of merchants, a strength of association between each identified merchant and each non-identified merchant;   generating the set of candidate merchants based on at least the strengths of association; and   filtering the set of candidate merchants according to at least one of: (i) an average transaction size and (ii) geographic location.   
     
     
         17 . The medium of  claim 16 , wherein the filtering the set of candidate merchants according to average transaction size further comprises:
 obtaining an average transaction size for each candidate merchant over the period of time;   determining an average transaction size for the identified merchants over the period of time; and   eliminating merchants from the set of candidate merchants based on at least the average transaction size of the candidate merchant,   
     
     
         18 . The medium of  claim 17 , further comprising before the generating of a probability of acceptance, eliminating merchants from the set of candidate merchants whose average transaction size varies from the computed average transaction size by more than a predetermined amount, 
     
     
         19 . The medium of  claim 16 , wherein the filtering the set of candidate merchants according to location further comprises:
 obtaining, for each identified merchant, a distance traveled by the selected account holder when visiting the identified merchant;   determining a standard deviation for the obtained travel distances; and   eliminating merchants from the set of candidate merchants based on at least the computed standard deviation of the obtained travel distances.   
     
     
         20 . A system comprising:
 a processor for filtering financial transaction data,   a tangible, non-transitory memory configured to communicate with the processor,   the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to he capable of performing operations comprising:
 filtering, by the processor, a data set to generate a set of candidate merchants for a selected account holder; and 
 generating, by the processor, for the selected account holder, a probability of acceptance for each of the candidate merchants, wherein the probability of acceptance is based upon a number of account holders having transactions with both the candidate merchant and an identified merchant and based upon a total number of account holder transactions with the identified merchant.