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Google Lighthouse - Financial Services

Google Lighthouse - Financial Services

Talk given on 2017-03-29 about Ravelin's technology stack and GCP.

Leonard Austin

March 29, 2017
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  1. Ravelin
    How Ravelin is leveraging data to combat fraud
    rather than managing infrastructure.
    Leonard Austin | 29.03.2017 ravelin.com

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  2. Meet the exec team
    Martin Sweeney
    CEO
    Leonard Austin
    CTO
    Nick Lally
    COO
    Mairtin O’Riada
    CIO
    Gerry Carr
    CMO
    Mairtin is as obsessive about
    catching fraudsters as he is
    about drinking tea. Before
    Ravelin, he had a storied
    career in international
    intelligence which gave him
    the perfect insight into the
    criminal mind. Previously
    Head of Fraud at Hailo, he’s
    now channeling all that
    experience into the perfect
    fraud product.
    Leonard has been designing,
    developing and deploying
    online technologies for over
    a decade. He is passionate
    about the power of agile
    teams, iterative
    development, continuous
    integration, automated
    testing and empowered
    engineers. He can often be
    found in the far corners of
    the earth.
    Martin was Founding
    Engineer at Hailo the taxi
    app, building the systems
    and team there over four
    years into a global business.
    He is a Physicist by training,
    but left behind an academic
    calling for the glamour of
    fraud detection and
    software. Martin is a father,
    husband and sporadic
    fisherman.
    Nick loves creating teams
    and processes in
    fast-growing organisations.
    Before Ravelin, he held
    Finance Director roles at
    Hailo and Canonical, the
    company behind Ubuntu, the
    OS that dominates cloud
    computing. An accountant at
    heart, he hates seeing any
    company lose money to
    pesky fraudsters.
    Gerry was the original
    marketing hire at Ubuntu
    and over five years there
    launched its cloud products,
    seeing it become the most
    used cloud OS in the world.
    Now juggles breaking
    phones with making people
    in the fraud prevention
    business aware of what
    Ravelin can do.
    ravelin.com

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  3. ravelin.com
    Fraud, the numbers.
    €4.79
    out of €100 in online sales is
    at risk of fraud
    ⇧215%
    increase in the rate of online payment
    fraud since last year
    27
    attacks per 1000
    transactions in Q4 2015
    1.3%
    of revenue is lost by
    merchants on average
    *Source: Global Fraud Attack Index (2016)

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  4. Many M’s
    where is
    the N?
    Detection is hard

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  5. The Fraudster
    ravelin.com

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  6. The Fraudster
    ravelin.com
    50 iMacs
    + 19 Kebabs = £100k+
    Taxi Driver Fraudster
    Dublin to Galway twice a day
    Chargeback Flights
    Tweets “looking forward to my flight”.
    Forgotten Bag
    40 Stolen Credit Cards and Cloning Gear
    Fraudsters Top Five
    Budwiser
    Jack Daniels
    Guinness
    Gelato
    Malibu
    Cardz & Deetz & Fullz
    allthefreestuff@
    youllnevercatchme@
    ilovesmokingpot1992@
    moneyzzz@

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  7. Ravelin
    Smarter Fraud Detection
    ravelin.com

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  8. Requirements
    Better than 3D Secure
    Fraud Detection
    Fast
    We sit within the checkout flow
    <300ms
    Process & Store Big Data
    All historic data from all clients.
    All real-time data from all clients.
    Global Markets
    Clients operate all over the world. Fraud is
    different from country to country.
    Highly Available
    Clients rely on Ravelin to decide whether to
    accept an order
    Secure
    We store/analysis bank cards, location data
    and PII (e.g. address, email, phone,
    transaction history etc) data
    ravelin.com

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  9. ravelin.com
    Ravelin’s Graph DB is1000x the
    speed of traditional graph database
    solutions.
    Can be integrated into real-time
    scoring.
    Ravelin maps every user, card
    number, phone number, device,
    email, IP Address etc
    Ravelin Network

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  10. ravelin.com
    Ravelin’s rules engine allows
    configure custom rules based on
    client’s experience of fraud.
    Set the boundaries acceptable
    behaviour.
    We track purchasing behaviour prior
    to the transaction so that each
    decision is made with as much
    information as possible.
    Rules & Fingerprints

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  11. No other approach provides the accuracy that our
    customers demand at a speed and scale that fits in with how
    their businesses operate.
    Our data science teams deploy models across industries and
    fine tune them for clients.
    These models learn based on the fraud that our clients
    experience, taking out much of the analysis work that goes
    with traditional rules based systems.
    This leads to higher accuracy - less fraud, and fewer genuine
    customers being turned away.
    ravelin.com
    Machine Learning

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  12. Machine Learning

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  13. Provider name free provider
    % Digits % Vowels
    average key distance capitalised
    % upper/lowercase length
    total number of characters tld
    total number of digits all uppercase
    disposable contains special characters (+,#,& etc)
    contains “.” contains given name
    contains family name Levenshtein distance (email & name)
    Email Features

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  14. Ravelin System - Deeper Drive
    Client Event→API
    →Decode
    →Enrich
    →Store
    →Read All History & Graph Data
    →Feature Extract
    →ML/Rules/BlackWhite Lists
    →Respond
    →Fanout
    ravelin.com
    After We Respond
    →Store all features
    →Notification - callback
    →Fanout
    →Re-Score
    →Train Models

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  15. Category Technology Type
    Storage Cassandra Infrastructure
    Queue RabbitMQ, Kafka, NSQ etc Infrastructure
    Big Data Hadoop Infrastructure
    SQL Postgres Infrastructure
    Instrumentation Graphite, Influx, Grafana Infrastructure
    Distributed Synchronization Zookeeper Infrastructure
    Cache Memcache, Redis Infrastructure
    Search ElasticSearch Infrastructure
    Machine Learning Custom Python Services Business
    Software 50 x Go Services Business

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  16. ravelin.com
    A Sample of Ravelin’s Platform

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  17. The DevOps Team
    Mike
    ravelin.com

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  18. ravelin.com
    A Sample of Ravelin’s Platform

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  19. ravelin.com
    A Sample of Ravelin’s Platform

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  20. Category Technology Type
    Storage Bigtable Infrastructure
    Queue Pub/Sub Infrastructure
    Big Data Bigquery + Dataflow Infrastructure
    SQL Cloud SQL Infrastructure
    Instrumentation Datadog Infrastructure
    Distributed Synchronization Zookeeper Infrastructure
    Cache Redis Infrastructure
    Search ElasticSearch Infrastructure
    Machine Learning Custom Python Services Business
    Software 50 x Go Services Business

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  21. ravelin.com
    Moral of the Story.
    Outsourcing infrastructure
    to GCP keeps Mike happy
    and provides me with more
    time to run the business.

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  22. Thank you
    @leonardaustin
    @ravelinhq
    ravelin.com

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