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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