US 8,799,148 B2Granted

Systems and methods of ranking a plurality of credit card offers

OwnerRohan K. K. Chandraninventor

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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.

Claims14

Dependent claims

A method of determining prescreened credit card offers, the method comprising:

receiving, by a ranking computing device, information regarding a borrower;
determining, by the ranking computing device, a plurality of prescreened credit card offers associated with the borrower;
receiving, from a third-party computing device operated by an entity controlling operations of a commercial website, entity-specific ranking criteria indicating one or more attributes for determining a ranking order of prescreened credit card offers presented to borrowers visiting the commercial website, the entity-specific ranking criteria including criteria for one or more attributes selected from the group comprising a bounty, a click-through rate or a conversion rate, wherein the entity-specific criteria are defined by a representative of the entity;
calculating, by the ranking computing device, a plurality of expected monetary values of respective prescreened credit card offers, wherein the expected monetary values are based on at least one of the bounty, the click-through rate or the conversion rate of the respective credit card offer as indicated in the entity-specific ranking criteria
ranking, by the ranking computing device, the plurality of prescreened credit card offers based on the calculated expected monetary values;
determining a plurality of future ranking values of respective prescreened credit card offers indicating probable future rankings of the respective prescreened credit card offers after at least one of the plurality of prescreened credit card offers is presented to one or more additional borrowers, wherein the future ranking values are based on at least trending data of the respective prescreened credit card offers;
adjusting the ranking based at least in part on the determined future ranking values of respective prescreened credit card offers;
and
transmitting, by the ranking computing device, a data file to the third-party computing device, the data file comprising an identifier of a prescreened credit card offer in the plurality of prescreened credit card offers that is ranked highest by the adjusted ranking.

6 more elements

A computing system for determining prescreened credit card offers, the system comprising:

a processor,
a computer readable medium storing machine-executable instructions including one or more modules configured for execution by the processor in order to cause the computing system to:
receive information regarding a borrower;
determine a plurality of prescreened credit card offers associated with the borrower;
receive, from a third-party computing device operated by an entity controlling operations of a commercial website, entity-specific ranking criteria indicating one or more attributes for determining a ranking order of prescreened credit card offers presented to borrowers visiting the commercial website, the entity-specific ranking criteria including criteria for one or more attributes selected from the group comprising a bounty, a click-through rate or a conversion rate, wherein the entity-specific criteria are defined by a representative of the entity;
calculate a plurality of expected monetary values of respective prescreened credit card offers, wherein the expected monetary values are based on a least one of the bounty, the click-through rate or the conversion rate of the respective credit card offer as indicated in the entity-specific ranking criteria;
rank the plurality of prescreened credit card offers based on the calculated expected monetary values;
determine a plurality of future ranking values of respective prescreened credit card offers indicating probable future rankings of the respective prescreened credit card offers after at least one of the plurality of prescreened credit card offers is presented to one or more additional borrowers, wherein the future ranking values are based on at least trending data of the respective prescreened credit card offers;
adjust the ranking based at least in part on the determined future ranking values of respective prescreened credit card offers;
transmit a data file to the third-party computing device the data file comprising an identifier of a prescreened credit card offer in the plurality of prescreened credit card offers that is ranked the highest by the adjusted ranking.

7 more elements

Dependencies are inferred from the claim text.

Facts

Application: 11/848,138Filed 30 Aug 2007 · us provisional application
Priority: 31 Aug 2006
Published: US 2008/0059352 A16 Mar 2008
Granted: 5 Aug 2014
Term ends: Not estimatedThe source records don’t support an estimate.

Classification7 codes

G06Q 40/03
Finance; Insurance; Tax strategies; Processing of corporate or income taxes: credit; Loans; Processing thereof
G06Q 10/10
Administration; Management: office automation; Time management
G06Q 20/354
Using cards, e.g. integrated circuit [IC] cards or magnetic cards: card activation or deactivation
G06Q 30/0246
Determining effectiveness of advertisements: traffic