Supplemental address verification

• US 20040215579A1
• Filed: 04/24/2003
• Published: 10/28/2004
• Est. Priority Date: 04/24/2003
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Xu, Juanjuan, Redenbaugh, George
• Application Number:
  US10/422,337
• Publication Number:
  US 20040215579A1
• Time in Patent Office: Days
• US Class Current: 705/78
• CPC Class Codes: G06Q 20/0855 involving a third party
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

In an embodiment, an apparatus for supplemental address verification for fraud prevention, includes: a validation tool configured to receive an incoming order from a customer and to validating a credit card of the customer with an issuing financial institution; a fraud shield tool configured to compare information related to the incoming order with negative files; an electronic commerce rule-based fraud detection tool configured to compare information related to the incoming order with general fraud patterns; and a third-party service configured to further analyze the incoming order for potential fraud, if an outsort rule fires.

Claims

1. A method for supplemental address verification for fraud prevention, the method comprising:

receiving an incoming order from a customer;

validating a credit card of the customer with an issuing financial institution;

comparing information related to the incoming order with negative files;

comparing information related to the incoming order with general fraud patterns; and

if an outsort rule fires, then using a third-party service to further analyze the incoming order for potential fraud.

2. The method of claim 1, wherein the action of using the third-party comprises:

providing a variance value that is indicative of the variance between information provided by the customer and information in a database of the third-party service.

3. The method of claim 2, wherein the variance value is small in value if a name provided by the customer is similar to a name of the customer in the database.

4. The method of claim 2, wherein the variance value is higher in value if a name provided by the customer does not match a name of the customer in the database.

5. The method of claim 2, wherein the variance value is higher in value if a phone number of the shipping address provided by the customer is a mobile phone number.

6. The method of claim 2, further comprising:

using the variance value, along with information provided by the customer, to further check the order for potential fraud.

7. The method of claim 6, further comprising:

using the variance value and the information of the customer to determine if the order will require evaluation by a fraud analyst.

8. The method of claim 1, wherein the order is received via an online shopping website.

9. The method of claim 1, wherein the order is received via a call center.

10. An apparatus for supplemental address verification for fraud prevention, the apparatus comprising:

validation tool configured to receive an incoming order from a customer and to validating a credit card of the customer with an issuing financial institution;

a fraud shield tool configured to compare information related to the incoming order with negative files;

an electronic commerce rule-based fraud detection tool configured to compare information related to the incoming order with general fraud patterns; and

a third-party service configured to further analyze the incoming order for potential fraud, if an outsort rule fires.

11. The apparatus of claim 10, wherein the third-party provides a variance value that is indicative of the variance between information provided by the customer and information in a database of the third-party service.

12. The apparatus of claim 11, wherein the variance value is small in value if a name provided by the customer is similar to a name of the customer in the database.

13. The apparatus of claim 11, wherein the variance value is higher in value if a name provided by the customer does not match a name of the customer in the database.

14. The apparatus of claim 11, wherein the variance value is higher in value if a phone number of the shipping address provided by the customer is a mobile phone number.

15. The apparatus of claim 10, wherein the electronic commerce rule-based fraud detection tool is configured to use the variance value, along with information provided by the customer, to further check the order for potential fraud.

16. The apparatus of claim 15, wherein the electronic commerce rule-based fraud detection tool is configured to use the variance value and the information of the customer to determine if the order will require evaluation by a fraud analyst.

17. The apparatus of claim 10, wherein the order is received via an online shopping website.

18. The apparatus of claim 10, wherein the order is received via a call center.

19. An apparatus for supplemental address verification for fraud prevention, the apparatus comprising:

means for receiving an incoming order from a customer;

means for validating a credit card of the customer with an issuing financial institution;

means for comparing information related to the incoming order with negative files;

means for comparing information related to the incoming order with general fraud patterns; and

means for using a third-party service to further analyze the incoming order for potential fraud, if an outsort rule fires.

20. The apparatus of claim 19, wherein the means for using the third-party is configured to provide a variance value that is indicative of the variance between information provided by the customer and information in a database of the third-party service.

21. An article of manufacture, comprising:

a machine-readable medium having stored thereon instructions to;

receive an incoming order from a customer;

validate a credit card of the customer with an issuing financial institution;

compare information related to the incoming order with negative files;

compare information related to the incoming order with general fraud patterns; and

use a third-party service to further analyze the incoming order for potential fraud, if an outsort rule fires.