Systems and methods for evaluating a credibility of a website in a remote financial transaction

Patent metadata

Field	Value
Publication number	US-10089665-B2
Application number	US-201514881248-A
Country	US
Kind code	B2
Filing date	Oct 13, 2015
Priority date	Oct 13, 2015
Publication date	Oct 2, 2018
Grant date	Oct 2, 2018

Abstract

Examples of the disclosure enable a user to evaluate a credibility of a website and/or a merchant in a remote financial transaction. In some embodiments, a request for a score is received from a client device. The request includes usage data associated with the client device. A website and/or merchant is identified based on the usage data, and customer experience-related data associated with the website and/or the merchant are retrieved from one or more sources. A first score is generated at a score generator based on the retrieved customer experience-related data, and the first score is transmitted to the client device for presentation at the client device.

First claim

What is claimed is:

1. A computer-implemented method comprising:
receiving, by a processor, from a browser extension of a web browser in a client device, usage data associated with the client device;
based on the usage data, identifying, by the processor, a website currently being presented on the web browser and a merchant associated with the web site;
retrieving, by the processor, from one or more sources, customer experience-related data associated with the website and the merchant associated with the web site;
aggregating, by the processor, the retrieved customer experience-related data;
based on the aggregated customer experience-related data, generating, at a score generator, a first score associated with the website and the merchant associated with the web site; and
presenting, by the browser extension, the generated first score in a secondary window on the client device, the generated first score being indicative of a projected customer experience relating to the website and the merchant associated with the website.

2. The computer-implemented method of claim 1 , further comprising categorizing the generated first score as positive when a first portion of the retrieved customer experience-related data associated with a positive customer experience is valued more than a second portion of the retrieved customer experience-related data associated with a negative customer experience.

3. The computer-implemented method of claim 1 , wherein generating a first score comprises:
associating a first weight with a first portion of the customer experience-related data, the first portion corresponding to a first source of the one or more sources; and
associating a second weight with a second portion of the customer experience-related data, the second portion corresponding to a second source of the one or more sources, the first score generated based on the association of the first weight with the first portion and the association of the second weight with the second portion.

4. The computer-implemented method of claim 1 , wherein the first score is configured for presentation in the secondary window in a first color when the first score is positive, a second color when the first score is neutral, and a third color when the first score is negative.

5. The computer-implemented method of claim 1 , wherein generating a first score comprises identifying that a portion of the customer experience-related data is associated with a blacklist, wherein the first score is generated to be a negative score based on the association of the portion with the blacklist.

6. The computer-implemented method of claim 1 , wherein generating a first score comprises biasing the first score to be a neutral score.

7. The computer-implemented method of claim 1 , further comprising:
based on the website and the merchant associated with the website, identifying another website and another merchant associated with the another website; and
transmitting a recommendation for presentation in the secondary window at the client device, the recommendation associated with the another website and the another merchant.

8. The computer-implemented method of claim 1 , further comprising:
based on the usage data, identifying a product;
based on the identified product, identifying one or more other websites and merchants associated with the one or more other websites; and
transmitting a recommendation for presentation at the client device, the recommendation associated with the one or more other websites and the merchants associated with the one or more of other websites.

9. The computer-implemented method of claim 1 , further comprising:
determining whether the first score satisfies a predetermined threshold; and
on condition that the first score does not satisfy the predetermined threshold, identifying one or more additional websites and merchants associated with the one or more additional websites, and transmitting a recommendation for presentation in the secondary window at the client device, the recommendation associated with the one or more additional websites and the merchants associated with the one or more additional websites.

10. The computer-implemented method of claim 1 , further comprising:
based on the website and the merchant associated with the website, identifying one or more other websites and merchants associated with the one or more other websites;
retrieving, from the one or more sources, other customer experience-related data associated with the one or more other websites and the merchants associated with the one or more other websites;
based on the retrieved other customer experience-related data, generating another score associated with the one or more other websites and the merchants associated with the one or more of the other websites; and
transmitting the another score for presentation in the secondary window at the client device.

11. A computing device comprising:
a memory storing data associated with one or more entities, and computer-executable instructions, the one or more entities including a website and a merchant; and
a processor configured to execute the computer-executable instructions to:
based on the data associated with the one or more entities associated with content currently being presented in a web browser, generate one or more scores;
receive, from a browser extension of the web browser in a client device, a request for a score, the request including usage data associated with the client device;
based on the usage data, retrieve from one or more sources, customer experience-related data associated with the one or more entities;
aggregate, the retrieved customer experience-related data;
based on the aggregated customer experience-related data, identify a first entity of the one or more entities;
on condition that the one or more generated scores include a first score that corresponds to the identified first entity, present, by the browser extension, the first score in a secondary window on the client device, the first score being indicative of a projected customer experience relating to the identified first entity.

12. The computing device of claim 11 , wherein the processor is further configured to categorize the generated first score as positive when a first portion of the retrieved customer experience-related data associated with a positive customer experience is valued more than a second portion of the retrieved customer experience-related data associated with a negative customer experience.

13. The computing device of claim 11 , wherein the processor is further configured to execute the computer-executable instructions to:
associate a first weight with a first portion of the data; and
associate a second weight with a second portion of the data, the one or more scores generated based on the association of the first weight with the first portion and the association of the second weight with the second portion.

14. The computing device of claim 11 , wherein the processor is further configured to execute the computer-executable instructions to:
determine whether the first score satisfies a predetermined threshold; and
on condition that the first score does not satisfy the predetermined threshold, identify a second entity of the one or more entities based on the identified first entity, and present, in the secondary window on the client device, data associated with the second entity.

15. The computing device of claim 11 , wherein the processor is further configured to execute the computer-executable instructions to:
based on the usage data, identify a product;
based on the identif

Assignees

• Mastercard International Inc

Inventors

• Dickinson Bradley Kenneth
• Hull Jason
• Mullen Christopher Eric
• Atwood Kelly Elaine
• Hively Corey M

Classifications

• G06Q30/0609 Primary

  Qualifying participants for shopping transactions (payment transaction verification G06Q20/401) · CPC title