METHOD AND SYSTEM FOR ANALYZING AND OPTIMIZING DISTRIBUTION OF WORK FROM A PLURALITY OF QUEUES

• US 20130218630A1
• Filed: 03/29/2013
• Published: 08/22/2013
• Est. Priority Date: 07/02/2010
• Status: Active Grant

• Current Assignee: Memento Inc. (Fidelity National Information Services Incorporated)
• Original Assignee: Fis Financial Compliance Solutions LLC (Fidelity National Information Services Incorporated)
• Inventors: Taintor, Robert C., Leibon, Gregory David
• Granted Patent: US 10,325,235 B2
• Time in Patent Office: Days
• US Class Current: 705/7.26
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors

Abstract

A method and system for analyzing and optimizing the distribution of work from a plurality of queues includes storing historical data in a database. The historical data may include sets of different types of data items, each of the data items having an associated monetary value. The method further includes assigning a relative score to each of the data items within the sets and calculating a cumulative monetary value for each relative score, the cumulative monetary value being the summation of the monetary values for all items having relative scores up to and including the relative score. The method further includes determining the maximum cumulative monetary value calculated and its corresponding relative score. In one embodiment, the corresponding relative score is then used to determine which items to work in a set of queues that has not yet been worked.

Claims

1-49. -49. (canceled)

50. A computer-implemented method for analyzing investment in reviewing potential fraud, comprising:

storing historical data in a database comprising a plurality of fraud activities of a first type, each fraud activity having a fraud determination and an associated monetary value, wherein the associated monetary value of each fraud activity is associated with a related cost of investigation;

assigning a relative score to each of the fraud activities of the first type, based on at least the other fraud activities of the first type;

calculating, using at least one processor, a cumulative monetary value for each particular relative score, the cumulative monetary value for each relative score being a function of a summation of the monetary values of at least the fraud activities having the particular relative score;

determining a highest cumulative monetary value and a relative score corresponding to the highest cumulative monetary value; and

determining which of a set of potential fraud items to analyze, based on a relative score associated with each of the set of potential fraud items and the corresponding relative score.