Systems and methods of assisted strategy design

• US 8,930,262 B1
• Filed: 11/01/2011
• Issued: 01/06/2015
• Est. Priority Date: 11/02/2010
• Status: Active Grant

• Current Assignee: Experian Technology Ltd. (Experian plc)
• Original Assignee: Experian Technology Ltd. (Experian plc)
• Inventors: Searson, Paul A., Hastings, Maria M.
• Primary Examiner(s): Tran, Hai
• Application Number:
  US13/287,050
• Time in Patent Office: 1,162 Days
• Field of Search: 705/38
• US Class Current: 705/38
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/045 Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

In an embodiment, a computer system performs a method of modifying a decision algorithm, such as an algorithm for assigning credit limits or other credit terms, via a graphical user interface. The system displays a graphical representation of a decision tree comprising a plurality of decision nodes. The decision nodes are associated with respective conditions, and at least a portion of the decision nodes are associated with an outcome to be assigned to an individual matching the associated respective conditions in accordance with the decision tree. The system receives a selection of a decision node and selects a parameter to be used to construct subnodes of the selected decision node, and constructs the subnodes. The system calculates an outcome for each subnode, and it updates the graphical representation of the decision tree to include the plurality of subnodes.

Claims

1. A computer system configured to automatically assist a user in assigning credit terms to a plurality of decision nodes via a graphical user interface, the computing system comprising:

one or more computer processors;

a graphical display configured to display one or more user interfaces, the graphical display being connected to the one or more computer processors; and

one or more human interface devices configured to receive input from a user, the one or more human interface devices connected to the one or more computer processors;

the one or more computer processors configured to receive, via the one or more human interface devices, a selection of a plurality of nodes on a decision tree, each node being associated with benchmark data records of a corresponding group of consumers;

the one or more computer processors configured to receive, via the one or more human interface devices, a specification of one or more credit offer constraints associated with respective credit card offers;

the one or more computer processors configured to determine, for each of the plurality of nodes, based on the credit offer constraints being applied to the benchmark data records of the corresponding group of consumers, a proposed credit card offer having associated credit terms including one or more of a credit limit, an interest rate, or a penalty rate;

the one or more computer processors configured to cause the graphical display to display a user interface including the proposed credit card offers and associated credit terms for each node and related summary statistics for each of the constraints determined based on the benchmark data records, enabling the user to evaluate the proposed credit card offers for respective nodes; and

the one or more computer processors configured to apply the proposed credit card offers and associated credit terms to the plurality of nodes based upon an indication from the user accepting the proposed credit card offers and associated credit terms.

2. The computer system of claim 1, wherein the decision tree comprises one or more nodes, wherein each node is associated with a logical condition based on a parameter associated with an individual, and wherein each node is associated with either a credit card offer or one or more nodes as children nodes.

3. The computer system of claim 2, wherein the logical condition includes a range of values associated with the parameter.

4. The computer system of claim 1, wherein the credit offer constraints include an algorithm for forecasting one or more parameters to be optimized.

5. The computer system of claim 1, wherein the user interface is configured to display additional information relating to each proposed credit card offer in response to a user placing a mouse indicator over a portion of the user interface associated with the respective proposed credit terms.

6. The computer system of claim 1, wherein the one or more credit offer constraints include a maximum bad debt, a maximum credit limit, and a maximum number of benchmark data records.