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

• US 10,089,665 B2
• Filed: 10/13/2015
• Issued: 10/02/2018
• Est. Priority Date: 10/13/2015
• Status: Active Grant

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Dickinson, Bradley Kenneth, Hull, Jason, Mullen, Christopher Eric, Atwood, Kelly Elaine, Hively, Corey M
• Primary Examiner(s): Civan, Ethan D
• Application Number:
  US14/881,248
• Publication Number:
  US 20170103438A1
• Time in Patent Office: 1,085 Days
• Field of Search: 705 261- 272
• CPC Class Codes: G06Q 30/0609 Buyer or seller confidence or verification

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.

Claims

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 identified product, identify a second entity of the one or more entities; and

present, in the secondary window on the client device, data associated with the second entity.

16. The computing device of claim 14, wherein the processor is further configured to execute the computer-executable instructions to:

based on the identified second entity, identify a third entity of the one or more entities, the third entity associated with a third score of the one or more generated scores; and

present, in the secondary window on the client device, the third score.

17. A computer-readable storage device having computer-executable instructions embodied thereon, wherein, upon execution by at least one processor, the computer executable instructions cause the at least one processor to:

based on data associated with one or more entities associated with content currently being presented in a web browser, generate one or more scores associated with the one or more entities;

receive, from a browser extension of the web browser in a client device, a request for a score;

retrieve, from the browser extension of the web browser in the client device, 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 associated with the first entity.

18. The computer-readable storage device of claim 17, wherein, upon execution by the at least one processor, the computer-executable instructions further cause the at least one processor to:

categorize the 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.

19. The computer-readable storage device of claim 17, wherein, upon execution by the at least one processor, the computer-executable instructions further cause the at least one processor to:

determine whether the first score indicative of the projected customer experience satisfies a predetermined threshold; and

on condition that the first score indicative of the projected customer experience does not satisfy the predetermined threshold, identify a second entity of the one or more entities, and transmit, to the client device, data associated with the second entity.

20. The computer-readable storage device of claim 17, wherein, upon execution by the at least one processor, the computer-executable instructions further cause the at least one processor to:

compare a second score of the one or more generated scores with the first score indicative of the projected customer experience; and

on condition that the second score is greater than or equal to the first score indicative of the projected customer experience, identify a second entity of the one or more entities that is associated with the second score as a recommended entity, and transmit, to the client device, data associated with the second entity.