Systems and methods associated with targeted leading indicators

• US 20030212618A1
• Filed: 05/07/2002
• Published: 11/13/2003
• Est. Priority Date: 05/07/2002
• Status: Abandoned Application

• Current Assignee: General Electric Capital Corporation (General Electric Company)
• Original Assignee: General Electric Capital Corporation (General Electric Company)
• Inventors: Keyes, Jennifer M., Litty, Charles J.
• Application Number:
  US10/063,663
• Publication Number:
  US 20030212618A1
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

Systems and methods associated with targeted leading indicators are provided. According to one embodiment, at least one condition associated with a target business segment is determined. A series of indicator input items is selected, and a forecast model for the target business segment is automatically generated based on historic information associated with the series of indicator input items and the condition.

Claims

1. A method of facilitating use of targeted indicators, comprising:

determining at least one condition associated with a target business segment;

selecting a series of indicator input items; and

automatically generating a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.

2. The method of claim 1, wherein at least one indicator input item include at least one of:

(i) economic information, (ii) employment information, (iii) inflation information, (iv) equity information, (v) debt information, (vi) construction information, (vii) backlog information, (viii) new order information, (ix) vacancy information, (x) interest rate information, (xi) money supply information, (xii) payment information, and (xiii) delinquency information.

3. The method of claim 1, wherein said selecting further comprises:

identifying the target business segment;

identifying a series of potential indicator input items; and

evaluating the potential indicator input items.

4. The method of claim 3, wherein said evaluation is associated with at least one of:

(i) seasonally adjusted information, (ii) rolling median information, (iii) standardized values, (iv) correlation coefficients, (v) weighted averages, and (vi) graphical analysis.

5. The method of claim 1, wherein the target business segment is associated with at least one of:

(i) an industry, (ii) an industry segment, (iii) a market, (iv) a market segment, (v) a customer, and (vi) a group of customers.

6. The method of claim 5, wherein the target business segment is further associated with at least one of:

(i) a collateral type, (ii) a geographic location, and (iii) a customer type.

7. The method of claim 5, wherein the target business segment is associated with at least one of:

(i) manufacturing, (ii) construction, (iii) retail trade, (iv) services, (v) wholesale trade, (vi) agriculture, (vii) forestry, (viii) fishing, (ix) mining, (x) transportation, (xi) communication, (xii) utility, (xiii) electric, (xiv) gas, (xv) sanitary services, (xvi) finance, (xvii) insurance, (xviii) real estate, and (xix) public administration.

8. The method of claim 1, wherein the condition is associated with at least one of:

(i) an economic condition, (ii) a payment information, (iii) a business cycle, and (iv) an industry behavior.

9. The method of claim 1, wherein the condition is associated with a plurality of bins.

10. The method of claim 9, wherein at least one bin is associated with at least one of:

(i) an above trend business level, (ii) a trend business level, and (iii) a below trend business level.

11. The method of claim 1, wherein said automatic generation is associated with a linear optimization technique.

12. The method of claim 1, wherein the forecast model is associated with weighing factors applied to each indicator input item.

13. The method of claim 1, wherein the forecast model is associated with at least one of:

(i) leading indicator information, (ii) lagging indicator information, and (iii) coincident indicator information.

14. The method of claim 1, further comprising

predicting future conditions based on current indicator input items and the forecast model.

15. The method of claim 14, further comprising:

adjusting a adjusting a score associated with an existing credit account based on said prediction.

16. The method of claim 14, further comprising:

adjusting a potential credit deal based on said prediction.

17. The method of claim 16, wherein said adjusting is associated with at least one of:

(i) a loan amount, (ii) a loan spread, (iii) a loan duration, (iv) a loan term, and (v) a lease.

18. The method of claim 14, wherein said predicting is associated with a long term performance forecast in accordance with a time series model.

19. An apparatus, comprising:

a processor; and

a storage device in communication with said processor and storing instructions adapted to be executed by said processor to;

determine at least one condition associated with a target business segment;

select a series of indicator input items; and

automatically generate a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.

20. The apparatus of claim 19, wherein said storage device further stores at least one of:

(i) a customer database, (ii) an account database, (iii) an indicator input database, (iv) a condition database, (v) a forecast model database, and (vi) a risk information database.

21. The apparatus of claim 19, further comprising:

a communication device coupled to said processor and adapted to communicate with at least one of;

(i) a risk manager device, (ii) an underwriter device, (iii) a third party service, (iv) a risk score controller, and (v) a leading indicator system.

22. A medium storing instructions adapted to be executed by a processor to perform a method of facilitating use of targeted indicators, said method comprising:

determining at least one condition associated with a target business segment;

selecting a series of indicator input items; and

automatically generating a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.

23. A method of facilitating use of targeted indicators, comprising:

retrieving a forecast model for a target business segment associated with an existing credit account;

determining a series of indicator input values;

predicting a future condition based on the forecast model and the series of indicator input values; and

adjusting a score associated with the credit account based on said prediction.

24. A method of facilitating use of targeted indicators, comprising:

retrieving a forecast model for a target business segment associated with a potential credit deal;

determining a series of indicator input values;

predicting a future condition based on the forecast model and the series of indicator input values; and

adjusting the potential credit deal based on said prediction.

25. The method of claim 24, wherein said adjusting is associated with at least one of:

(i) a loan amount, (ii) a loan spread, (iii) a loan duration, (iv) a loan term, and (v) a lease.