Method and apparatus for pattern generation

• US 6,598,030 B1
• Filed: 12/03/1999
• Issued: 07/22/2003
• Est. Priority Date: 05/27/1997
• Status: Expired due to Term

• Current Assignee: Visa International Service Association (Visa, Inc.)
• Original Assignee: Visa International Service Association (Visa, Inc.)
• Inventors: Faith, Patrick L., Siegel, Kevin P., Washburne, Theodore P.
• Primary Examiner(s): Coggins, Wynn W.
• Assistant Examiner(s): ROSEN, NICHOLAS D
• Application Number:
  US09/454,696
• Time in Patent Office: 1,327 Days
• Field of Search: 705/1, 705/35, 705/38, 705/39, 705/42, 705/43, 705/44, 700/91, 700/92, 706/46, 706/47, 706/48
• US Class Current: 705/38
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 20/108 Remote banking, e.g. home banking
• CPC Class Codes: G06Q 20/40 Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 20/403 Solvency checks
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G07F 7/08 by coded identity card or credit card or other personal identification means without personal verification means G07F7/02

Abstract

Methods and apparatus for transforming scoreable transaction data into financial data features are disclosed. In one aspect, a computer-implemented method transforms transaction data into a financial data feature for assessing credit risks. The financial data feature is extracted from the transaction data. The method involves obtaining the transaction data from a data source, and performing a set of operations on the transaction data to transform the transaction data into the financial data feature. The set of operations is selected only from a predefined set of classes of operations which are interrelated by a predefined order of precedence. Each operation in the set of operations is performed in an order based on the predefined order of precedence of a class associated with each operator.

Claims

1. A computer-implemented method for transforming scoreable transaction data into a financial data feature for use in assessing credit risk, the method comprising:

obtaining the scoreable transaction data from a data source; and

performing a set of operations on the scoreable transaction data to transform the scoreable transaction data into the financial data feature, the set of operations being selected only from a predefined set of classes of operations, the set of predefined classes of operations being arranged in a predefined order of precedence, wherein each operation in the set of operations is performed in an order based on the predefined order of precedence of a class associated with the each operator, the set of predefined classes of operations including only classes selected from the group consisting of a data structure class, an atomic transformation class, an entity transformation class, a time transformation class, and a joining operator class.

2. A computer-implemented method as recited in claim 1 wherein the financial data feature is configured for use in a risk prediction model, the computer-implemented method further including:

providing the financial data feature to a risk prediction model.

3. A computer-implemented method as recited in claim 2 further including:

implementing the risk prediction model the financial data feature; and

assessing a risk of bankruptcy based on as result of the implementation of the risk prediction model.

4. A computer-implemented method as recited in claim 2 wherein the financial data feature is further configured for use in a transaction scoring process associated with the risk prediction model, the computer-implemented method further including:

providing the financial data feature to the transaction scoring process.

5. A computer-implemented method as recited in claim 1 wherein the set of operations are performed substantially in real-time.

6. A computer-implemented method as recited in claim 1 further including

replacing the predefined order of precedence with a second predefined order of precedence in order to transform the scoreable transaction into a second financial data feature.

7. A computer-implemented method as recited in claim 6 wherein the scoreable transaction data includes the financial data feature, the second financial data feature, and additional data, the computer-implemented method further including:

providing the financial data feature and the second financial data feature, and not the additional data, to a credit risk prediction model.

8. A computer-implemented as recited in claim 2 wherein the risk prediction model is arranged to assess a level of credit risk using the financial data feature.