Data analysis for fraud detection - Wikipedia
This article is written like a personal reflection, personal essay, or argumentative essay that states a Wikipedia editor's personal feelings or presents an original argument about a topic. Please help improve it by rewriting it in an encyclopedic style. (April 2010) (Learn how and when to remove this template message) Fraud represents a significant problem for governments and businesses and speci
FDEC
Detecting Fraud with Data Mining: Three Success Stories Wojtek Kowalczyk Fraud Detection Expertise Center wojtek@fdec.nl wojtek@liacs.nl Leiden, 28.11.2012 Fraud Detection Expertise Center Founded in 2008 About 5 persons Main activities: research developmentdevelopment consultancy teaching & coaching Main areas: Electronic payments, Insurance, Government More info: www.fdec.nl We are searching fo
1 A Comprehensive Survey of Data Mining-based Fraud Detection Research ABSTRACT This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defi
1 A Comprehensive Survey of Data Mining-based Fraud Detection Research ABSTRACT This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines the professional fraudster, formalises the main types and subtypes of known fraud, and presents the nature of data evidence collected within
Square's Machine Learning Infrastructure and Applications - Dr. Rong Yan
Machine learning applications like fraud detection and recommendation have played a key role in helping Square achieve their mission to rethink buying and selling. In this talk, Dr. Rong Yan (Director of Data Science and Infrastructure, Square), gives a high-level overview of data applications at Square followed by a deep dive on how machine learning is used in our industrial leading fraud detecti
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