Andrea Lynn Allmon

US Patent:

8639522, Jan 28, 2014

Filed:

Apr 16, 2008

Appl. No.:

12/104242

Inventors:

Anu Kumar Pathria - La Jolla CA, US
Andrea L. Allmon - San Diego CA, US
Jean de Traversay - Solana Beach CA, US
Krassimir G. Ianakiev - San Diego CA, US
Nallan Suresh - Irvine CA, US
Michael K. Tyler - San Diego CA, US

Assignee:

Fair Isaac Corporation - San Jose CA

International Classification:

G06Q 10/00
G06Q 50/00

US Classification:

705 2, 705 3, 705 4, 706 21

Abstract:

Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.

US Patent:

20060217824, Sep 28, 2006

Filed:

Feb 23, 2006

Appl. No.:

11/361473

Inventors:

Andrea Allmon - San Diego CA, US
Jean Traversay - Solana Beach CA, US
Craig Nies - Carlsbad CA, US
Anu Pathria - San Diego CA, US
Phuong Nguyen - San Diego CA, US
Nallan Suresh - Irvine CA, US
Michael Tyler - San Diego CA, US

International Classification:

G06F 17/00

US Classification:

700090000

Abstract:

A computer-implemented approach for processing benefits payment claims for prescription medicine, with these operations. Receiving pending pharmacy benefits payment claims submitted for payment by a pharmacy benefits claims payor, each claim specifying a patient. For each claim and its specified patient, performing operations including the following. Performing computer-driven statistical analysis of predefined aspects of one of the following in relation to a compiled history of past claims paid by one or more pharmacy benefits claims payors: claims history for the patient, the claim, medical history of the patient. Generating an indicator of predicted legitimacy by scoring results of the statistical analysis. Providing an output of at least one of the following: the indicator, payment advice prepared by applying predefined criteria to data including the indicator.

US Patent:

20090094064, Apr 9, 2009

Filed:

Oct 9, 2007

Appl. No.:

11/869628

Inventors:

Michael Tyler - San Diego CA, US
Moiz Saifee - Ujjain, IN
Shafi Rahman - Bangalore, IN
Anu Pathria - San Diego CA, US
Andrea Allmon - San Diego CA, US

International Classification:

G06Q 40/00

US Classification:

705 4

Abstract:

A healthcare insurance claim that includes variables characterizing aspects of a healthcare service for which reimbursement is sought is analyzed in order to determine whether there are any aspects that are indicative of fraud or error. This analysis includes generating score variables from the variables of the healthcare insurance claim and determining whether a presence of one or more of the pairs of variables is indicative of fraud or error based on levels of co-occurrence of the one or more pairs in historical healthcare insurance claims. If a positive determination occurs, then the healthcare insurance claim can be flagged or elevated for review by a user. Related techniques, apparatus, systems, and articles are also described.

US Patent:

7813937, Oct 12, 2010

Filed:

Feb 6, 2003

Appl. No.:

10/360858

Inventors:

Anu K Pathria - San Diego CA, US
Andrea L Allmon - San Diego CA, US
Jean de Traversay - Solona Beach CA, US
Krassimir G Ianakiev - San Diego CA, US
Nallan C Suresh - Irvine CA, US
Michael K Tyler - San Diego CA, US

Assignee:

Fair Isaac Corporation - Minneapolis MN

International Classification:

G06Q 10/00
G06Q 50/00

US Classification:

705 2, 705 3, 706 15

Abstract:

Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.