A SELF-CALIBRATING OUTLIER MODEL AND ADAPTIVE CASCADE MODEL FOR FRAUD DETECTION

Patent №

US 8,041,597

Granted

2011-10-18

Filed 2008

Owner

FAIR ISAAC CORPORATION

Lab

AI components

6

ml · vision · kr · planning · evo · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

12189023

A system and method for detecting fraud is presented. A self-calibrating outlier model is hosted by a computing system. The self-calibrating outlier model receives transaction data representing transactions, and is configured to calculate transaction-based variables, profiles and calibration parameters, and to produce a score based on the transaction data according to the transaction-based variables, profiles and calibration parameters. An adaptive cascade model is also hosted by the computing system, and is configured to generate a secondary score for the transaction data based on profile information from the variables and/or profiles calculated by the self-calibrating outlier model, and based on a comparison with labeled transactions from a human analyst of historical transaction data.

AI classification

Machine learning1.00
Planning1.00
Evolutionary computation1.00
Knowledge representation1.00
Vision1.00
AI hardware0.98
Natural language0.03
Speech0.00

Ownership

FAIR ISAAC CORPORATION

assignment · 214260656

Assignors

LI, XIANG, ZOLDI, SCOTT M., ATHWAL, JEHANGIR, LI, XIANG, ZOLDI, SCOTT M., ATHWAL, JEHANGIR

On an employer assignment, the assignors are typically the inventors.

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