Flink at Capital One:Case

Study

Slim Baltagi @SlimBaltagiDirector of Big Data Engineering, FellowCapital One

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Agenda

1. Capital One at a glance2. Some elements of our Technology

Strategy3. What is the business problem of this

case study?4. What is the related solution

architecture? 5. What values Flink added to the solution?

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A leading consumer and commercial banking institution with $306.2 billion in assets, $204.0 billion in loans and $210.4 billion in deposits– 8th largest bank based on U.S. deposits1

– 4th largest credit card issuer in the U.S.3 – 3rd largest issuer of small business Visas

and MasterCards in the U.S.4

– 3rd largest independent auto loan originator5

– Largest US direct bank6

Conducts business in the US, Canada and the U.K.

• More than 65 million customer accounts and 46,000 associates

• Fortune 500 rank: 124• Best Companies rank: 85

1. Capital One at a glance

1) Domestic deposits ranking as of Q4’142) Source: FDIC, June 2014, deposits capped at $1B per branch3) Company-reported domestic credit card outstandings, Q1’15, American Express ex Charge Cards

4) Source: Nilson Report, Q4’135) Source: JD Power, 20146) FDIC, company reports as of Q4’14

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2. Some elements of our Technology StrategyLeverage the power of Open Source

technology beyond just a ‘low cost’ alternative.

Introduce new capabilities to address limitations of our legacy platforms.

Shift the data processing paradigm from a batch to real-time stream processing.

Build solutions easy portable from on-premise to the cloud.

Empower our associates to dream, disrupt and contribute to Open Source projects.

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3. What is the business problem of this case study?

Real-Time monitoring of customer activity data (Audit log event details, failure and success data, … ) to:

• proactively detect and resolve issue immediately

• prevent significant customer impact • enable flawless digital enterprise experience

The current legacy solution uses expensive and proprietary tools.

The current legacy solution offer very limited real time and advanced analytics capabilities.

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4. What is the related solution architecture?

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5. What values Flink added to the solution?

A cost effective solution with the same capabilities as proprietary log data analytics tools

Real-Time event processing which was not possible with our legacy system:

• Reliable real time, exactly once event processing. Example: Real-Time alerts

• Transformations, enrichments, lookups with very low overhead in real time

A future proof solution to handle growing customer activity data

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5. What values Flink added to the solution?

More advanced analytics on data streams, such as: • Advanced windowing to perform analytics

beyond event at a time operations. • Machine learning: Event correlation,

automated fraud detection, event clustering, anomaly detection, user session analysis, etc

Solution aligned with our technology strategy

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Please come to my talk!

Day 1 - October 12, 2015 16:00 - 16:40

Flink and Spark: Similarities and Differences

@SlimBaltagi @CapitalOne