SYSTEMS AND METHODS OF RANKING A PLURALITY OF CREDIT CARD OFFERS
First Claim
1. A computerized system for presenting prescreened credit card offers to a borrower, the system comprising:
- a prescreen module configured to receive an indication of one or more prescreened credit card offers for a borrower, wherein the borrower has at least about a 90% likelihood of being issued a credit card associated with each of the prescreened credit card offers after completing a corresponding full credit card application;
a ranking module configured to assign a unique rank to at least some of the prescreened credit card offers, wherein determination of respective ranks for the prescreened credit card offers is based on at least a bounty and a click-thru-rate associated with respective prescreened credit card offers;
a presentation module configured to generate a data structure comprising information regarding at least a highest ranked credit card offer.
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0 Petitions
Accused Products
Abstract
Prescreened credit card offers, such as offers for credit cards that a particular potential borrower is likely to be granted upon completion of a full application, are ranked based on expected values of respective prescreened offers. The expected value of a prescreened credit card offer may represent an expected monetary value to one or more referrers involved in providing the prescreened offer to the borrower. Thus, the referrer may present a highest ranked credit card offer to a potential borrower first in order to increase the likelihood that borrower applies for the credit card offer with the highest expected value to the referrer. Depending on the embodiment, the expected value of a credit card offer may be based on a combination of a bounty associated with the offer, a click-through-rate for the offer, and/or a conversion rate for the offer, for example.
272 Citations
24 Claims
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1. A computerized system for presenting prescreened credit card offers to a borrower, the system comprising:
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a prescreen module configured to receive an indication of one or more prescreened credit card offers for a borrower, wherein the borrower has at least about a 90% likelihood of being issued a credit card associated with each of the prescreened credit card offers after completing a corresponding full credit card application;
a ranking module configured to assign a unique rank to at least some of the prescreened credit card offers, wherein determination of respective ranks for the prescreened credit card offers is based on at least a bounty and a click-thru-rate associated with respective prescreened credit card offers;
a presentation module configured to generate a data structure comprising information regarding at least a highest ranked credit card offer. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method of determining an expected value for each of a plurality of credit card offers, the method comprising:
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receiving an indication of a plurality of prescreened credit card offers associated with an individual;
receiving an indication of a plurality of attributes associated with each of the prescreened credit card offers; and
calculating an expected value for each of the prescreened credit card offers using at least two of the plurality of attributes for each respective prescreened credit card offer. - View Dependent Claims (10, 11, 12, 13, 14)
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15. A method of determining prescreened credit card offers, the method comprising:
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receiving information regarding a borrower from a referring website;
determining two or more prescreened credit card offers associated with the borrower;
determining ranking criteria associated with the referring website, the ranking criteria comprising an indication of attributes associated with one or more of the borrower and respective prescreened credit card offers;
calculating an expected value of the two or more prescreened credit card offers based at least on the attributes indicated in the ranking criteria; and
transmitting a data file to the referring website, the data file comprising an identifier of one of the prescreened credit card offers having an expected value higher than the expected values of the other prescreened credit card offers. - View Dependent Claims (16, 17, 18, 19)
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20. A method of ranking a plurality of credit card offers that have been prescreened for presentation to a potential borrower, the method comprising:
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receiving information regarding each of a plurality of prescreened credit card offers;
determining an expected value of each of the prescreened credit card offers, wherein the expected value for a particular credit card offer is based on at least (1) a money amount payable to a referrer if the potential borrower is issued a particular credit card associated with the particular credit card offer, (2) an expected ratio of potential borrowers that will apply for the particular credit card offer in response to being presented with the particular credit card offer, and (3) an expected ratio of potential borrowers that will be issued the particular credit card associated with the particular credit card offer; and
ranking the plurality of credit card offers based on the expected values for the respective credit card offers. - View Dependent Claims (21, 22, 23, 24)
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Specification