Credit score simulation

• US 20060004654A1
• Filed: 06/10/2005
• Published: 01/05/2006
• Est. Priority Date: 05/30/2003
• Status: Active Grant

• Current Assignee: Experian Information Solutions Incorporated (Experian plc)
• Original Assignee: Experian Information Solutions Incorporated (Experian plc)
• Inventors: Schwab, Matthew R., Kornegay, Adam T., de Almeida, Marcos C.
• Granted Patent: US 7,593,891 B2
• Time in Patent Office: Days
• US Class Current: 705/39
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Systems and methods are described that simulate a credit score. The system enables a user to modify a credit data element in order to determine its effect on a credit score. The user can modify the element directly or simulate an action that, if performed, would modify the element. Since the number of possible modifications and actions can be overwhelming, in one embodiment, the system suggests modifications and actions to be simulated. These suggestions can be tailored to a user'"'"'s goal, such as increasing a credit score by a particular number of points or allocating a particular sum of money in order to maximize a credit score. In one embodiment, the system obtains credit data from multiple credit bureaus and can determine credit scores using different algorithms, such as the different algorithms used by the different credit bureaus.

Claims

1. A computer-implemented method for simulating a financial risk score, comprising:

determining a first financial risk score based on a first set of data;

modifying the first set of data to create a second set of data; and

determining a second financial risk score based on the second set of data.