Database for check risk decisions populated with check activity data from banks of first deposit

• US 20030217003A1
• Filed: 05/14/2002
• Published: 11/20/2003
• Est. Priority Date: 05/14/2002
• Status: Active Grant

• Current Assignee: Early Warning Services, LLC
• Original Assignee: Primary Payment Systems, Inc.
• Inventors: Spooner, Larry W., Weinflash, Laura E.
• Granted Patent: US 7,383,227 B2
• Time in Patent Office: Days
• US Class Current: 705/42
• CPC Class Codes: G06Q 20/042 characterized in that the payment protocol involves at least one cheque
• CPC Class Codes: G06Q 20/108 Remote banking, e.g. home banking
• 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 40/128 Check-book balancing, updating or printing arrangements

Abstract

A plurality of banks of first deposit provide checking account activity data for both transit items (checks received for deposit that need to be cleared) and incoming returns (bounced checks) to a statistical model which determines from the data the likelihood that a check from a specific checking account will be returned. This data is used to populate a database of checking accounts to be used for making check risk decisions, such as check hold policy decisions, check acceptance decisions, and open to buy decisions.

Claims

1. A computer implemented method of populating a database of checking account with statistical data regarding the likelihood that a check from a specific checking account will be returned, the method comprising:

(a) receiving checking account activity data directly from a plurality of banks of first deposit, the checking account activity data including;

(i) transit items, and

(ii) incoming returns;

(b) analyzing the checking account activity data using a statistical model to determine the likelihood that a check from a specific checking account will be returned;

(c) populating a database with checking account data including;

(i) checking account numbers, and

(ii) likelihood that a check from a specific checking account number will be returned; and

(d) periodically repeating steps (a) and (b) with new checking account activity data and updating the database of checking account data with the new checking account activity data.

2. The method of claim 1 wherein step (b) further comprises determining if there is enough checking account activity data for a specific checking account number to make a statistically significant determination of the likelihood that a check from a specific checking account will be returned, and if so, then populating the database with checking account data for that checking account number, and if not, then holding the checking account data for that specific checking account number in a hold queue, and step (d) further comprises periodically reviewing the checking account numbers in the hold queue and populating the database with checking account data for any checking account numbers in the hold queue which are determined to have enough checking account activity data to make a statistically significant determination of the likelihood that a check from a specific checking account will be returned.

3. The method of claim 1 wherein step (b) further comprises determining if there is enough checking account activity data for a specific checking account number to make a statistically significant determination of the likelihood that a check from a specific checking account will be returned, and if so, then populating the database with checking account data for that checking account number, and if not, then holding the checking account data for that specific checking account number in a hold queue and populating the database with only the checking account number, and step (d) further comprises periodically reviewing the checking account numbers in the hold queue and populating the database with the likelihood data for any checking account numbers in the hold queue which are determined to have enough checking account activity data to make a statistically significant determination of the likelihood that a check from a specific checking account will be returned.

4. The method of claim 1 wherein step (a) further comprises receiving the checking account activity data solely from a plurality of banks of first deposit.

5. A computer-implemented method of making a check risk decision using a database of checking account data, the database being created and maintained by (i) receiving checking account activity data directly from a plurality of banks of first deposit, the checking account activity data including transit items and incoming returns, (ii) analyzing the checking account activity data using a statistical model to determine the likelihood that a check from a specific checking account will be returned, and (iii) populating the database with checking account data including checking account numbers and likelihood that a check from a specific checking account number will be returned, the method comprising:

(a) receiving checking account data of a check presented for deposit, payment or clearing; and

(b) using the information in the database to make a check risk decision.

6. The method of claim 5 wherein the database is created and maintained by receiving checking account activity data solely from a plurality of banks of first deposit.

7. The method of claim 5 wherein the check risk decision is a check acceptance decision.

8. The method of claim 5 wherein the check risk decision is a check hold policy decision.

9. The method of claim 5 wherein the check risk decision is an open to buy decision.

10. A computer-implemented method of making a check risk decision using (i) a first database populated with checking account status and item level data from checking accounts of payor institutions that belong to a member service, and (ii) a second database that is populated with checking account data of checking accounts that are not held by payor institutions that belong to the member service, the second database including checking account numbers and likelihood that a check from a specific checking account number will be returned as determined by a statistical model, the second database being populated by checking account activity data, including transit items and incoming returns, received directly from a plurality of banks of first deposit, the method comprising:

(a) receiving checking account data of a check presented for deposit, payment or clearing;

(b) using the first database to make a check risk decision for checking accounts of payor institutions that belong to the member service; and

(c) using the second database to make a check risk decision for checking accounts that are not held by payor institutions that belong to the member service.

11. The method of claim 10 wherein the second database is populated by receiving checking account activity data solely from a plurality of banks of first deposit.

12. The method of claim 10 wherein the check risk decision is a check acceptance decision.

13. The method of claim 10 wherein the check risk decision is a check hold policy decision.

14. The method of claim 10 wherein the check risk decision is an open to buy decision.

15. The method of claim 10 wherein the item level data includes stop payments and early outgoing return notices.

16. A computer implemented method of populating a database of checking account with statistical data regarding the likelihood that a check from a specific checking account will be returned, the method comprising:

(a) receiving checking account activity data from a single entity that receives such data from a plurality of banks of first deposit, the checking account activity data including;

(i) transit items, and

(ii) incoming returns;

(b) analyzing the checking account activity data using a statistical model to determine the likelihood that a check from a specific checking account will be returned;

(c) populating a database with checking account data including;

(i) checking account numbers, and

(ii) likelihood that a check from a specific checking account number will be returned; and

(d) periodically repeating steps (a) and (b) with new checking account activity data and updating the database of checking account data with the new checking account activity data.

17. The method of claim 16 wherein the single entity is the Federal Reserve.

18. The method of claim 16 wherein the single entity is a clearinghouse.

19. The method of claim 16 wherein the single entity is a check processor.

20. A computer-implemented method of making a check risk decision using a database of checking account data, the database being created and maintained by (i) receiving checking account activity data from a single entity that receives such data from a plurality of banks of first deposit, the checking account activity data including transit items and incoming returns, (ii) analyzing the checking account activity data using a statistical model to determine the likelihood that a check from a specific checking account will be returned, and (iii) populating the database with checking account data including checking account numbers and likelihood that a check from a specific checking account number will be returned, the method comprising:

(a) receiving checking account data of a check presented for deposit, payment or clearing; and

(b) using the information in the database to make a check risk decision.

21. The method of claim 20 wherein the single entity is the Federal Reserve.

22. The method of claim 20 wherein the single entity is a clearinghouse.

23. The method of claim 20 wherein the single entity is a check processor.

24. A computer-implemented method of making a check risk decision using (i) a first database populated with checking account status and item level data from checking accounts of payor institutions that belong to a member service, and (ii) a second database that is populated with checking account data of checking accounts that are not held by payor institutions that belong to the member service, the second database including checking account numbers and likelihood that a check from a specific checking account number will be returned as determined by a statistical model, the second database being populated by checking account activity data, including transit items and incoming returns, received directly from a single entity that receives such data from a plurality of banks of first deposit, the method comprising:

(a) receiving checking account data of a check presented for deposit, payment or clearing;

(b) using the first database to make a check risk decision for checking accounts of payor institutions that belong to the member service; and

(c) using the second database to make a check risk decision for checking accounts that are not held by payor institutions that belong to the member service.

25. The method of claim 24 wherein the single entity is the Federal Reserve.

26. The method of claim 24 wherein the single entity is a clearinghouse.

27. The method of claim 24 wherein the single entity is a check processor.