Big Data in Financial ServicesSolving Banking’s Biggest Problem with Big Data

Karl Rieder, Code_N, March 11, 2014

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Big Data in Financial ServicesAdoption of Big Data: FS vs. All Industries

“Considerably enhancebig data capability”

“Invest in improveddata storage”

“Have Hadoop solution in production”

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Retail, Private, and Commercial Banks

“Single view of the client”

Customer portfolio analysis

Social media analytics

Credit card fraud

Big Data in Financial ServicesWhat are Banks Doing?

Improving customer service and sales; re-establishing trust

Investment Banks

Calculating daily P&L

Measuring market and credit risk

Regulatory reporting

Algorithmic tradingStreamlining operational procedures;

improving efficiency

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In investment banking, the current trend is evolutionary… improving existing processes – larger data stores and faster processing

In 2013, GFT has built:

Trade repository: holds 10 billion trade states (6 Petabytes)

Trade event store: records millions of daily events

Real-time trade processing and accounting system: calculates 100s of millions of daily balances

MapReduce-based ETL: processes 750 million rows of data

Volcker rule calculation: scours 4 Petabytes of historical data

Big Data in Financial ServicesEvolution

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Evolutionary approach has been clearly beneficial for the banks:

More efficient operational procedures

Reduced timelines

New calculations and insights

Accurate (regulatory) reporting

… but greater gains could be made from a more revolutionary approach

Big Data in Financial ServicesEvolution

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Big Data in Financial ServicesA Simplified View of an Investment Bank

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Big Data in Financial ServicesThe Silo Problem

A sadly common problem in all large investment banks…

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Big Data in Financial ServicesRevolution – The Soltuion

Source A

Source C

Source D

Source B

Source E

Process 1

Process 2

Process 3

Process 4

Result 1

Result 3

Result 2

Result 4

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Big Data in Financial ServicesRevolution – The Soltuion

Source A

Source C

Source D

Source B

Source E

Data and Processing Consolidation

Result 1

Result 3

Result 2

Result 4

Distributed storage

Distributed processing

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Consistent, golden-sourced data - single source of truth

Elimination of system and data redundancy

Reduction of operational costs

Cost-effective data administration

Unified, complete, and aggregated view of business

Improved analytical capability

Data consolidation

Architectural rationalization

Analysis of full data sets

Extraction of new information and insights

BenefitsObjectives

Big Data in Financial ServicesRevolution – Objectives and Benefits

A more compete view of banking activity, at a lower price!

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Big Data in Financial ServicesThe Future

Lots more data

Data quality is critical

Value comes from analytics

The time is now!

GFT Page 1213.04.23© Copyright GFT Technologies AG, 2014

Thank you

Karl Rieder

GFT IT Consulting, S.L.U., Avenida de la Generalitat, 163–167 08174 Sant Cugat del Vallès España

T +34 93 172 7071

M +34 649 845 130

karl.rieder@gft.com