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Online fraud detection:A reference architecture for adversarial learningDavid Talby@davidtalby
SVP Engineering, Atigeo
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Why Semi-Supervised Learning & Feedback?
50+Schemes(and counting)
99.9999%‘Good’ messages
6+Monthsper case
3Why Hybrid Analytics?
Ignore more rules
Unusual timing of
eventsUnusualpersonal network
Teamwork & scale
Think & talk differently
4Why Hybrid Analytics?
Rule Inference
Time Series
AnalysisLink
Analysis
Ensemble Learning
Natural Language
5Stream processing
Kafka
Email Stream
Account transactions Stream
Email NLP Features
People graph
Transactions time series
6User Analysis Iteration
Email NLP Features
User graph
Transactions time series
Graph Features
Time SeriesFeatures
NLP Features
Agent Feedback
Trai
n / T
est C
lass
ifier
77
Thank you!
Source code available on request:
@davidtalby
© 2015 Atigeo, Corporation. All rights reserved. Atigeo and the xPatterns logo are trademarks of Atigeo. The information herein is for informational purposes only and represents the current view of Atigeo as of the date of this presentation. Because Atigeo must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Atigeo, and Atigeo cannot guarantee the accuracy of any information provided after the date of this presentation. ATIGEO MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
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