Post on 08-Jan-2017
Online Predictive Modeling of Fraud Schemes from Multiple Live Streams
David Talby Claudiu BranzanCTO, Atigeo Principal Lead, Atigeo
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What we’re up against
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50+Schemes(and counting)
99.9999%‘Good’ messages
6+Monthsper case
Needle in a haystack
Hybrid analytics
No training data
Semi-supervised learning
Adversarial learning
Online feedback
Why hybrid analytics?
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Ignore more rules
Unusual timing of events
Unusualpersonal network
Teamwork & scale
Think & talk
differently
(bits of) the toolbox
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Rule Inference
Time Series
AnalysisLink Analysis
Ensemble Learning
Natural Language
Can we see some code please?
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Freely available IPython notebooks
Open source libraries & open data
Jump-start via AWS Marketplace
Stream processing
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Kafka
Email Stream
Account transactions Stream
Email NLP Features
People graph
Transactions time series
Sample email patterns
Sample natural language annotatorsUnderstandvocabulary
– Jargon– Codewords– Multi- lingual
Understandgrammar
– Whoarewetalkingabout?– Past,presentorfuture?– Compoundsentences
Understandcontext– Email:Re:,Fwd:,attachments– SMS&IMhavetheirowngrammar
Sample email patterns
K-Means failing on “haystacks” Bregman Bubble Clustering
User analysis iteration
Email NLP Features
User graph
Transactionstime series
Graph Features
Time SeriesFeatures
NLP Features
Agent Feedback
Trai
n / T
est C
lass
ifier
Really• Makes the world a better place • Needle in a very large haystack
– Actually needs a petabyte-scale platform
• Multi-modal: no single trick works– Hybrid analytics
• No labeled data– Semi-supervised learning– Cold start problem
• Sparse & high-dimensional– Graph based features & change over time
• Adversarial– Feedback & online learning
Technically
Summary: why hunting criminals is cool
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THANK YOU!Get the notebooks: github.com/Atigeo/Atigeo/hunting_criminals_demo
Try it yourself: “xPatterns Connect” on AWS Marketplace
Ask us about it: @davidtalby , @melcutz
appendixAppendixIn case the live demo gets cold feet on stage
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