Vintage maturation analytics for predicting behavior and projecting cash flow for customer communities and their responses to economic, competitive, or management changes

• US 7,702,555 B1
• Filed: 02/13/2001
• Issued: 04/20/2010
• Est. Priority Date: 02/22/2000
• Status: Active Grant

• Current Assignee: Argus Information and Advisory Services Incorporated (Verisk Analytics Incorporated)
• Original Assignee: Strategic Analytics, Inc. (Verisk Analytics Incorporated)
• Inventors: Breeden, Joseph L, Franklin, R David, Giancola, Anthony J
• Primary Examiner(s): Colbert; Ella
• Application Number:
  US09/781,310
• Time in Patent Office: 3,353 Days
• Field of Search: 705/36, 705/38, 705/40, 705/35, 705/37, 705/10, 705/36.R, 709/703, 709/203, 707/3, 707/100
• US Class Current: 705/36.00R
• 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 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method predicts vintage behavior. The method receives a first set of data, the first set of data being based on at least one of a first factor and a second factor. The first factor includes a factor related to vintage maturation. The second factor includes a factor not related to vintage maturation. The method determines a second set of data and a third set of data based on the first set of data, the second set of data being based on the first factor, and the third set of data being based on the second factor. The method then predicts vintage behavior based on at least one of the second set of data and the third set of data.

Claims

1. A data processing method for automatically processing and analyzing vintage loan performance data in order to predict a behavior of a group of vintage loan accounts, the data processing method comprising the steps of:

(a) storing vintage loan performance data representative of a known group of vintage loan accounts in a memory device;

(b) processing said known vintage loan performance data stored in said memory device by way of a processor in order to automatically decompose said known vintage loan performance data into an age based component and calendar time based component; and

(c) forecasting the behavior of said vintage loan accounts based upon said age component and said calendar time component.

2. The data processing method as recited in claim 1, wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon one or more exogenous effects.

3. The data processing method as recited in claim 2 wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon seasonal effects.

4. The data processing method as recited in claim 2 wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon management actions.

5. The data processing method as recited in claim 2 wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon competitive influences.

6. The data processing method as recited in claim 2 wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon marketing campaigns.

7. The data processing method as recited in claim 2, wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon economic conditions.

8. The data processing method as recited in claim 2 wherein step (b) comprises decomposing said vintage loan performance data into said age component and said calendar time component, wherein said calendar time component is based upon management history.

9. The data processing method as recited in claim 2, step (c) includes the step of determining the demographic characteristics of said past loan accounts in order to predict the future performance of said vintage loan accounts.