System and method for matching merchants based on consumer spend behavior
First Claim
1. A method comprising:
- passively collecting, by a computer-based system for using spend behavior to match merchants, spend level data for a transaction of a first entity;
aggregating, by the computer-based system, the collected spend level data for a plurality of entities;
clustering, by the computer-based system, the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity; and
matching, by the computer-based system, a first merchant with a second merchant based on a relationship of first cluster members with the first merchant and a relationship of first cluster members with the second merchant.
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Abstract
The present invention improves upon existing systems and methods by providing a passive profile creation method. The data accessible to a financial processor, such as spend level data, is leveraged using sophisticated data clustering and/or data appending techniques. Associations are established among entities (e.g., consumers), among merchants, and between entities and merchants. In one embodiment, a system and method for passively collecting spend level data for a transaction of a first entity, aggregating the collected spend level data for a plurality of entities; and clustering the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity is provided.
74 Citations
19 Claims
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1. A method comprising:
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passively collecting, by a computer-based system for using spend behavior to match merchants, spend level data for a transaction of a first entity; aggregating, by the computer-based system, the collected spend level data for a plurality of entities; clustering, by the computer-based system, the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity; and matching, by the computer-based system, a first merchant with a second merchant based on a relationship of first cluster members with the first merchant and a relationship of first cluster members with the second merchant. - View Dependent Claims (4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17)
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2. A method comprising:
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passively collecting, by a computer-based system for using spend behavior to match merchants, spend level data for a transaction of a first entity; aggregating, by the computer-based system, the collected spend level data for a plurality of entities; assigning, by the computer-based system, a weighted percentile to the spend level data of the first entity within merchant category codes for a plurality of merchant category codes; selecting, by the computer-based system, a weight percentile across a merchant category codes; grouping, by the computer-based system, a first entity with other entities into clusters based upon the selecting; and matching, by the computer-based system, a first merchant with a second merchant based on the spend level data of cluster members, wherein the first merchant and the second merchant are identified in response to the selecting. - View Dependent Claims (3)
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15. A method comprising:
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passively collecting, by a computer-based system for using spend behavior to match merchants, spend level data for a transaction of a first entity; aggregating, by the computer-based system, the collected spend level data for a plurality of entities; clustering, by the computer-based system, the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity; appending, by the computer-based system, the clustered data with entity characteristic data; analyzing, by the computer-based system, the appended clustered data; drawing, by the computer-based system, inferences about cluster members based on the analyzing, wherein drawing inferences about cluster members from appended clustered data comprises utilizing present and absent data; and matching, by the computer-based system, a first merchant with a second merchant based on the spend level data of cluster members, wherein the first merchant and the second merchant are identified in response to the selecting.
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18. A system comprising:
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a processor for using spend behavior to match population of merchants, 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 perform operations comprising; passively collecting, by the processor, spend level data for a transaction of a first entity; aggregating, by the processor, the collected spend level data for a plurality of entities; assigning, by the processor, a weighted percentile to the spend level data of the first entity within merchant category codes for a plurality of merchant category codes; selecting, by the processor, a weight percentile across a merchant category codes; and grouping, by the processor, a first entity with other entities into clusters based upon the selecting; and matching, by the processor, a first merchant with a second merchant based on a relationship of first cluster members with the first merchant and a relationship of first cluster members with the second merchant.
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19. An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a computer-based system for using spend behavior to match a population of merchants, cause the computer-based system to perform operations comprising
passively collecting, by the computer-based system, spend level data for a transaction of a first entity; -
aggregating, by the computer-based system, the collected spend level data for a plurality of entities; cluster the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity; and matching, by the computer-based system, a first merchant with a second merchant based on a relationship of first cluster members with the first merchant and a relationship of first cluster members with the second merchant.
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Specification