Analyses and processing of big data in financial services - central and commercial banks

1. Analyses and processing of big
data in financial services
Fisnik Doko

2. Content
• What is Big Data?
• 4 V‘s of Big Data
• Turning Big Data into Value
• Big Data Analytics
• Trends in 2016 for financial services
• Big Data use cases - Finance
• Big data in central banks
• Credit Registry of NBRM
• Questions
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3. What is Big Data?
• Big data is data that exceeds the processing capacity of
conventional database systems
• The data is too big, moves too fast, or doesn't fit the
structures of your database architectures
• Aim to solve new problems or old problems in a better way
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4. 4

5. 4 V‘s of Big Data
More data More relevant data
Real-time streaming dataDifferent types of data
From… …To
Terabyte
≈ 1,000
Gigabyte
≈ 1,000,000,000,000
Gigabyte
Zettabyte Mountain of data Useful insights
Business/structured data Unstructured data
Monthly-based reporting
Fixed frequency data input Continuous flowing data input
…ToFrom…
Real-time reporting
From… …To …ToFrom…
Interpretable Uninterpretable
Relevant Irrelevant
Information
The 4Vs
model
t+30
Live
update
TXT
Twitter Facebook
Insights
(novel info)
Signal
(relevant info)
TXT
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6. Turning Big Data into Value
The ‘Datafication’ of
our World;
• Activities
• Conversations
• Words
• Voice
• Social Media
• Browser logs
• Photos
• Videos
• Sensors
• Etc.
Volume
Veracity
Variety
Velocity
Analysing
Big Data:
• Text
analytics
• Sentiment
analysis
• Face
recognition
• Voice
analytics
• Movement
analytics
• Etc.
Value
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7. Big Data Analytics
• Examining large amount of data
• Appropriate information
• Identification of hidden patterns, unknown correlations
• Competitive advantage
• Better business decisions: strategic and operational
• Effective marketing, customer satisfaction, increased
revenue
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8. Trends in 2016 for financial services
• Banks are continuing to make progress on drafting big data
strategies
• Machine learning will accelerate
• Gaps will become more evident between the leaders and
the laggards
• Data governance and other compliance aspects will become
more deeply integrated with big data platforms
• Financial services organizations are struggling to understand
how to leverage IoT data
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9. Big Data use cases - Finance
• Credem Bank - uses data analytics to predict - increased
revenue 22%
• MasterCard - analyze the behavior of customers – find
insights
• Morgon Stanley (financial services firm) - determine the
impact of a particular market event, as well as its original
cause
• Radobank - analysed criminal activities at ATMs
• Zions Bank – froud detection – receiving data from many
sources
• Bundesbank - Expert panels and planning
• Chinese Banking Corporation - marketing strategy
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10. Big data in central banks
• Central banks have an active interest in big data
• Develop their own data platforms to handle regulatory data
collection
• Useful for research
• Monetary policy is seen to benefit most from big data
• Central banks actual involvement in the use of big data is
currently limited
• Seminars about big data in central banks in many countries
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11. Credit Registry of NBRM
• Information's about credit exposure of banks and clients in
RM
• Improving credit quality and to maintain stability of banking
system
• Biggest database in NBRM
• Will be used for big data analytical purposes
• Applying technological analyzes
• Gain information and value
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12. Questions
?
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