Method and system for identifying teaser surfers with time series credit history

• US 7,421,409 B1
• Filed: 02/16/2000
• Issued: 09/02/2008
• Est. Priority Date: 02/16/2000
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kraemer, James Richard, Liu, Shiping, Murphy, Edgar Leroy Jr.
• Primary Examiner(s): Poinvil; Frantzy
• Assistant Examiner(s): GRAHAM, CLEMENT B
• Application Number:
  US09/505,031
• Time in Patent Office: 3,121 Days
• Field of Search: 705/37, 705/38, 705/36, 705/35, 705/34, 705/14, 705/27, 235/379
• US Class Current: 705/37
• 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
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Initially the amount of data is checked to determine whether a sufficient history is present for the method. Credit card accounts are classified as new, relatively new, and old cards, i.e. opened within six months, within twelve months, and over twelve months ago. The balances for each of the three categories are calculated for each month. The average balance percentages of cards opened within six months and twelve months for the last twenty-four months is calculated and teaser surfers are defined as either having average percentages within the last twenty-four months for all credit cards opened within six and twelve months are greater than predefined percentages.

Claims

1. A processing system implemented method for identifying teaser surfers, the method comprising:

receiving, by the data processing system, a credit history data for a creditor;

calculating, by the data processing system, a first set of sums, wherein each sum in the first set of sums comprises a total credit card debt for all credit cards issued to the creditor for a corresponding, different one month period, and wherein a first total number of sums in the first set of sums equals a predetermined number of months;

calculating, by the data processing system, a second set of sums, wherein each sum in the second set of sums comprises a total new credit card debt for all new credit cards issued to the creditor for the corresponding, different one month period, and wherein a second total number of sums in the second set of sums equals the predetermined number of months;

calculating, by the data processing system, a third set of percentages, wherein each percentages in the third set of percentages comprises a percentage of new credit card debt to total credit card debt for the corresponding, different one month period, and wherein a third total number of percentages in the third set of percentages equals the predetermined number of months;

calculating, by the data processing system, an average percentage of new credit card debt to total credit card debt over the predetermined number of months;

comparing, by the data processing system, the average percentage of new credit card debt to total credit card debt to a preset cutoff average percentage, wherein, by comparing, a comparison is formed; and

determining, by the data processing system, whether to issue a credit card to the creditor based on the comparison.

2. The method recited in claim 1, further comprising:

calculating, by the data processing system, a fourth set of sums, wherein each sum in the fourth set of sums comprises a total credit card debt for all relatively new credit cards issued to the creditor for the corresponding, different one month period, and wherein a fourth total number of sums in the fourth set of sums equals the predetermined number of months;

calculating, by the data processing system, a fifth set of percentages, wherein each percentage in the fifth set of percentages comprises a percentage of relatively new credit card debt to total credit card debt for the corresponding, different one month period, and wherein a fifth total number of percentages in the fifth set of percentages equals the predetermined number of months;

calculating, by the data processing system, an average percentage of relatively new credit card debt to total credit card debt over the predetermined number of months;

comparing, by the data processing system, the average percentage of relatively new credit card debt to total credit card debt to a second preset cutoff average percentage, wherein, by comparing the average percentage of relatively new credit card debt to total credit card debt to the second preset cutoff average percentage, a second comparison is formed; and

determining, by the data processing system, whether to issue a credit card to the creditor based on the second comparison.

3. The method recited in claim 1, wherein the new credit cards have been issued to the creditor for less than six months.

4. The method recited in claim 1, wherein the new credit cards are credit cards having been issued to the creditor for a period of time less than a preset time period, and wherein during the preset time period the new credit cards have low interest teaser interest rates.

5. The method recited in claim 2, wherein the relatively new credit cards are credit cards having been issued to the creditor for less than twelve months.

6. The method recited in claim 2, wherein the relatively new credit cards have been issued to the creditor for a period of time less than two preset time periods, and wherein the two preset time periods correspond to time periods during which the relatively new credit cards have low interest teaser interest rates.

7. The method recited in claim 1, wherein the predetermined number of months is twelve months.

8. The method recited in claim 1, wherein the predetermined number of months is twenty-four months.

9. The method recited in claim 1, wherein the preset cutoff average percentage is sixty-five percent.

10. The method recited in claim 2, wherein the second preset cutoff average is eighty-five percent.