How big data, advanced analytics and cognitive computing is disrupting traditional business and operating models in financial markets? New competitors, powered by social, mobile, analytics, and cloud computing, are making new business models emerging rapidly. Wealth Management, Corporate Banking and Transaction Banking & Payments are significant sources of growth in Financial Markets. How take advantage from those new technologies to face this new scenario?

1. © 2015 IBM Corporation
Financial Markets Data & Analytics Led Transformation
Gianpaolo Zampol
Business Development Executive | Financial Services Sector
São Paulo, July 29th, 2015

2. 2
Financial Markets Data & Analytics Led Transformation
Latin & South America
• Rising rates
• Loan growth remains sluggish
• Increasing focus on costs
• Revenue growth under pressure
• Asset quality deteriorating in emerging markets
• Negative earnings momentum
• Litigation risks an regulatory uncertainty
Challenging economic environment
Source: IBM

3. 3
Financial Markets Data & Analytics Led Transformation
The Brazilian Financial Market – Evolution
Merger & Acquisitions [BRL
billion; 2014]
Funds under management [BRL
trillion; 2011-03/2015]
1,9
2011
2,3
CAGR: +11%
03/2015
2,8
0,1
2,7
2,5
0,4
0,4
2012 2013
0,2
1,1
0,6
2014
Source: Anbima; BM&F Bovespa;IBM
47,5
32,9
29,8
34,1
52,2
7,0
18,8
25,5
6,8
14,3
Debt issuance [BRL billion;
04/2014-03/2015]
Comments
• Primary market
– Mergers & Acquisitions: Predominantly
international players with local presence,
except BTG Pactual, which rose to a
significant Brazilian investment bank
– Debt issuance mostly through large
universal Brazilian banks
• Funds
– Strong growth, with focus on fixed
income, multi market and pension funds,
accounting for more than 75% of total
assets
• Technology
– Mostly national, product specific solutions
and less integrated packages, with
interfaces within bank’s technology
architecture
• Partnerships
– Middle and back office operations of
medium sized players outsourced to large
players, e.g. Banco do Brasil, Itaú and
Bradesco are large fund administrators for
other fund managers

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Financial Markets Data & Analytics Led Transformation
Disruptive competition
4
Source: IBM

5. 5
Financial Markets Data & Analytics Led Transformation
Only deposit taking and fiduciary responsibilities are protected by regulation – everything else is up for
disintermediation
Disruption is spreading to Financial Markets as well
Source: IBM

6. 6
Financial Markets Data & Analytics Led Transformation
Power of
Analytics
Cloud
Enablement
Social
media
explosion
Mobile
revolution
“Although [social, mobile, analytics, and cloud] are… disruptive on their own; together they are
revolutionizing business and society, disrupting old business models and creating new
leaders.” – Gartner
The digital world is enabling radical innovation
Source: Gartner; IBM

7. 7
Financial Markets Data & Analytics Led Transformation
• Wealth management
• Corporate Banking
• Transaction banking & payments
Significant sources of growth in Financial Markets
Source: IBM

8. 8
Financial Markets Data & Analytics Led Transformation
With 75% of change-the-bank costs absorbed by regulatory change by many global banks,
mutualisation and utilities are becoming a necessity
Source: IBM
Cost pressure will result in new service models enabled by collaboration
and cloud-delivery

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Financial Markets Data & Analytics Led Transformation
New business models are rapidly emerging
30 October 2018
Contextualization of Financial Services
ManufacturingDistribution
Causes a fracturing of…
Source: IBM

10. 10
Financial Markets Data & Analytics Led Transformation
2.2x
Analytically sophisticated
companies outperform their
competition
more likely to outperform
industry peers
260%
more likely to be top
performers
90% of the data in the world today has been created in the last two years -
80% of it is uncertain
Source: IDC; Cisco; IBM analysis

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Financial Markets Data & Analytics Led Transformation
Characteristics of big data
Big data embodies new data characteristics created by today’s digitized
marketplace
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Traditional Approach Big Data Approach
Analyze small subsets of information Analyze all information
Carefully cleanse information before analysis Analyze all information as is
Start with hypothesis, test against selected data Explore ALL data, identify correlations
Analyze data AFTER it has been processed
and landed in a warehouse or mart
Analyze data IN MOTION as it is generated,
in real-time
Paradigm shifts enabled by big data
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Big data objectives
Top functional objectives identified by organizations with active big data pilots or
implementations. Responses have been weighted and aggregated.
Customer-centric outcomes
Operational optimization
Risk / financial management
New business model
Employee collaboration
Other
functional
objectives
Customer-
centric
objectives
49%
18%
15%
14%
4%
55%
4%
23%
15%
2%
Banking & Financial
Markets
Global
Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business School
at the University of Oxford, 2012; IBM
Better understanding customer behavior underpins almost half of all active
big data efforts

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Financial Markets Data & Analytics Led Transformation
Structured and
Unstructured Data
Captured
Detected
Inferred
Descriptive
Analytics
Prescriptive
Analytics
Predictive
Analytics
What
happened?
What exactly
is the
problem?
How many,
how often,
where?
What actions
are needed?
How can
achieve the
best outcome
and address
variability?
Stochastic
Optimization
How can we
achieve the
best outcome?
Optimization
What if these
trends
continue?
Forecasting
What could
happen?
Simulation
What will
happen next
if? Predictive
Modelling
Analytics Sophistication
Cognitive
Computing
Sophistication of analytics is increasing exponentially
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Cognitive Systems address uncertainty
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Cognitive in action
16
Rule and regulation inquiry for returning military personnel
Investment decision support for Wealth Relationship Managers
Online Self Directed Wealth advice for the Mass Market
Multi-party compliance approval of a structured trade
Source: IBM

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Financial Markets Data & Analytics Led Transformation
GrowthProfitabilityEfficiency GrowthProfitabilityEfficiency
Cognitive
Operations
Cognitive
Analytics
Cognitive
Engagement
Cognitive Operations
A Cognitive core that orchestrates a
network of distributed business services
and drives a simpler, leanerorganisation
that can make faster decisions and is
closer to customers.
Cognitive Analytics
Cognitive data -driven discovery that
applies machine learning algorithms to
mine big data for trends, real-time
behaviours, predicted outcomes and
optimal responses.
Cognitive Engagement
Cognitive -orchestrated systems of
engagement that align financial services
supply with a customer’s economic
choices and optimise the customer
interaction and experience with the Bank.
Vision for the Cognitive Financial Markets Company
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Cognitive Operations
A Cognitive core that orchestrates a
network of distributed business services :
o Cloud Services
o Cognitive Computing
o Lean Processing
o Workforce Collaboration
Cognitive Analytics
Cognitive data-driven discovery and
decision making applied to business and
operating model performance:
o Business Performance
o Risk and Compliance
o Customer Lifetime Value
o Product Profitability
o PricingOptimisation
Cognitive Engagement
Cognitive orchestrated systems of
engagement with high value customer
networks and ecosystem partners
o Collaborative business models
o Open ecosystem architecture
o Boundary-less computing
o Omni channel Integration
o Mobility and Social
o Digital Security
Mobile & Social
Customer Analytics
Cognitive
Computing
Omni-channel
Ecosystem
Integration
Product & Pricing
Analytics
Collaborative
Business Models
Digital Security
Risk & Compliance
Cognitive
Operations
Cognitive
Analytics
Cognitive
Engagement
Cloud
Services
Business
Analytics
Boundary-less
computing
Lean
Processing
Workforce
Collaboration
Capabilities to drive innovation and make material gains in customer
experience and business performance
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Pre-Tax Profit gain of 40-60%
Cost-To-Income lowered 5-10%
The Customer Base
Revenue per Product
Product per Customer
Acquisition Costs
Selling Costs
Servicing Costs
Processing Costs
2-4%
4-6%
6-10%
1-2%
3-4%
4-6%
6-8%
Revenue Uplift of 12-20% Cost Savings of 14-20%
The size of the prize is very attractive
Source: IBM

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Financial Markets Data & Analytics Led Transformation
Thank you
Gianpaolo Zampol
Business Development Executive
Financial Services Sector
gianpaolozampol
@gzampol
gzampol