The Big Data Revolution: The Next Generation of Finance
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Transcript of The Big Data Revolution: The Next Generation of Finance
Finance & Risk ServicesThe Big Data Revolution: The Next Generation of Finance May 2016
2Copyright © 2016 Accenture All rights reserved.
AgendaBig Data revolution and financial services industry trends
Big Data - opportunity for CFOs to play a greater role
The transformation journey to become a Big Data-driven bank
The value at stake for the CFO
Copyright © 2016 Accenture All rights reserved.
More data More relevant data
Real-time streaming dataDifferent types of data
From… …ToTerabyte
≈ 1,000 Gigabyte
≈ 1,000,000,000,000 Gigabyte
3
The Big Data revolution means access to large volumes of new data: It’s time for organizations to capture the huge value hidden in this dataBig Data: What does it really mean?
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 IrrelevantInformation
The 4Vs
model
t+30 Live update
TXT
Twitter Facebook
Insights (novel info)
Signal (relevant info)
TXT
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According to recent surveys and market evidence, the Financial Services industry is increasingly embracing the Big Data revolution with the opportunity it presents to reinvent the spaceHow Big Data is affecting the Financial Services (FS) industry
71%of surveyed FS industry firms areexploring Big Data and predictive analytics1
$6.4 billionBig Data investment in 2015by FS firms5
+26%Increase in Big Data spending estimated for 2015-20196
70%of FS industry firms surveyed report that Big Data is of critical importance to their firms354%of surveyed FS firms have appointed aChief Data Officer to their organizations4
+201%Total investment growth (2014 vs 2013) in new Technology firms (Fintech)7$12 billionGlobal Fintech financing activity in 20158
60%of banks worldwide expect to process the majority of their transactions in cloud by 20162
How is the market moving?What is the market sentiment?
How much is this bet?How widespread is the use of Big Data?
5Copyright © 2016 Accenture All rights reserved.
AgendaBig Data revolution and financial services industry trends
Big Data - opportunity for CFOs to play a greater role
The transformation journey to become a Big Data-driven bank
The value at stake for the CFO
6Copyright © 2016 Accenture All rights reserved.
Discovery of new business opportunities Data-driven decision making
Risk and regulatory managementEnhanced productivity and efficiency
The adoption of advanced technologies and capabilities is a key enabler to new and important opportunities for CFOs to expand their strategic roleThe potential value behind Big Data adoption
The timely availability of large amounts and different types of data allows decision-making processes based on data rather than intuition.
New technologies allow the automation of manual business processes and the handling of large volumes of unstructured data at lower costs.
New solutions to extract valuable insights and facilitate the discovery of business opportunities, enabling CFOs to expand their role as trusted advisor to the CEO.
Agile infrastructures and processes able to manage what is required now, and what is likely to be required in the future by the Regulator.
Opportunities
for CFOs to play a
larger strategic
role
Cost Reduction
Revenue Growth
InsightsDiscovery
Data Monetizatio
nStrategic Decisions
Investment Choices
Process Automation
Low Storage Costs
High Scalability
CFO/CRO Integration
Real-time Simulations
Regulatory Reporting
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Discovery of new business opportunities Data-driven decision making
The Big Data revolution will help CFOs use real-time and valuable insights to improve decisions making and support their role as a strategic partnerData-driven decision making and discovery of new business opportunities
CFOs now have the opportunity to use insights generated from data to make decisions with the aim of enhancing revenue growth and driving cost reductions.
CFOs are now positioned to unlock the power of Big Data and take on the role of trusted advisor to the CEO, providing ideas, guidance and perspectives for developing new business opportunities that create addition value.
Big Data and advanced analytics help improve data management processes through the elaboration and analysis of large amounts of data. They also provide real-time information and useful insights that allow CFOs to make faster and better decisions based on data rather than intuition.
Data Storage Data Elaboration Data AnalysisDecision Making
Huge volume and different types of data
Generation of combined information
Data visualization techniques
Real-time data and insights
discovery
Big Data and digital technology help CFOs shift from business operator activities (budgeting, forecasting, performance monitoring) to a C-levels advisor role (insights for supporting strategic decisions, analysis of investments choices, new business opportunities).
Big Data ManagementCFO Business Role
CFO
Capa
bilit
ies
Business AdvisorStrong industry
knowledge to act
as business leader
Business OperatorMonitoring
skills,reporting activities
Strategic PartnerAnalytics
capabilities todrive decisions and create new opportunities
8
Big Data techniques allow CFOs to gain useful information at a lower cost, particularly in regulatory reportingEnhanced productivity, efficiency and risk and regulatory management
Copyright © 2016 Accenture All rights reserved.Note: A legend describing the acronyms can be found at the back to the presentation
Risk and regulatory managementEnhanced productivity and efficiency
New architectures, moving from silo solutions to “data lakes” and using Big Data technologies can help generate important cost advantages due to a higher level of scalability and large volumes of data managed at a lower cost per unit.
Each year, banks are confronted with new regulatory requirements and challenges. Big Data allows organizations a simplified and cost effective way to source their data and convert it into “usable information for regulatory reporting.”
Data Sources
2015 2016 2017 2018
Low
Med
ium
High
Enforcement Date
Expe
cted
Im
pact
236 (cap 8)
SSM SREP RDAR
RInterne
t Payme
ntsEMIR
SRM
Transparency
Bankit
CRS
PRIPs
CCD
Supervisory Reporting
EBAPayment
Account Directive
MAD II
MIFID (Mkts)
MIFID (Inv. Prot.) FRT
BAnaCredit AML
IVReg. EU Privacy
PSD II
IFRS9
Liikanen
236
CFOs now have the opportunity to reduce costs related to data elaboration by using automated and sophisticated analytical tools that store and analyze large amounts of data faster and more easily.
CFOs are now better positioned to respond quickly to regulator requests due to the availability of Big Data and advanced technologies that allow real-time simulations and scenario analysis.
Big Data Query
Machine Learning
Data Enrichment
In-Memory Technologies
Fast Access Database
Real-time Use (Mobile, Web,..)
Analytical Use (Report, Dashboards,..)
Data Lake (Big Data Platform)
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AgendaBig Data revolution and financial services industry trends
Big Data - opportunity for CFOs to play a greater role
The transformation journey to become a Big Data-driven bank
The value at stake for the CFO
10Copyright © 2016 Accenture All rights reserved.
The transformation to a Big Data-driven enterprise should address three key strategic imperativesThe transformation journey to becoming a Big Data-driven bank
A new data operating model based on the central role of data in decision-making processes and day-to-day activities is recommended. The model will define new roles and responsibilities related to the data governance processes.
Advanced technologies and flexible IT architectures that can store and analyze huge amounts of different types of data are recommended. These help extract useful insights and generate value across the enterprise.
A cultural change is encouraged in terms of innovative mindset, new business roles and advanced skills across the organization. This will help capture and understand the real business value behind the adoption of Big Data.
1. Data OperatingModel
2. Leading-Edge Architecture
3. CulturalChange
Strategic imperatives to becominga Big Data-driven enterprise
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The roles within the data operating model include the data officer as a leaderThe data operating model
Data Governance Coordinator• Coordinates and meets
regularly with all governance function players
• Oversees the reporting process and makes sure involved players use the appropriate data sources, methodology and tools
Data Quality Steward• Writes data quality
standards for the entire data management process and defines the data dictionary
• Manages the data quality process for reporting: coordinates, monitors and addresses the corrective measures according to the data quality policy
Data Owner (Business)• Defines the business’s data
requirements for proper and effective reporting
• Defines (with the Data Quality Steward) the data checkup activities in the reporting development process and makes sure the activities are performed correctlyData Manager
• Makes sure that data requiredfor reporting purposes (regulatoryand managerial) are always available and reliable
• Oversees the quality of data used for reporting purposes and takes actionto solve potential issues
Designs macro data governance processes, assigning roles, responsibilities and accountable for the reliability of the data used for regulatory and financial reporting purposes
Data Officer
DataOfficer
11
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A Big Data IT architecture based on different data layers offers greater flexibility, scalability and data explorationThe leading-edge architecture
PresentationUsers view reports, through dashboards, that provide data as support for business decisionsManagementData are elaborated, aggregated, enriched throughspecific algorithms and engines to provide syntheticmeasures and resultsData LakeData from legacy systems are collected in order to allow full flexibility from this point on in terms of data analysis, data quality and data elaborationLegacy and Source SystemsData sources for the banks, contain and manage data required for core banking activities and represent the point of origin of the information
Data Discovery and ExplorationUsers access, browse, explore and analyze data in all the different stages and aggregation levels
Legacy 1
Legacy 4
Legacy 2
Legacy 5
Legacy 3
Legacy n
Dat
a G
over
nanc
e an
d D
ata
Qua
lity
Dat
a La
yers
Management
Data Lake
Presentation
Data Discovery
Legacy Systems
• Engines• Datawarehouse
• Tableau de Bord / Dashboard• Reporting• Self Business Intelligence
12
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Cultural change in terms of innovative mindset, new business roles and advanced skills is encouraged throughout the organizationThe cultural change
Key Elements for a Cultural Change
Change in senior management mindset is encouragedto promote:• Innovation diffusion• Evidence and data-based decisions• Convergence of data and sharing of
information• Business accountability for data managementNew business roles should be established with the responsibility to:• Define and execute data strategy • Identify and manage data and design data
quality controls• Manage the reliability and traceability of
business data• Define data accountability New skills and capabilities should be acquired, such as:• Data scientists• Quantitative analysts• IT architects and big data specialists
InnovativeMindset
NewBusiness Roles
Advanced Skills and Capabilities
13
14Copyright © 2016 Accenture All rights reserved.
AgendaBig Data revolution and financial services industry trends
Big Data - opportunity for CFOs to play a greater role
The transformation journey to become a Big Data-driven bank
The value at stake for the CFO
15Copyright © 2016 Accenture All rights reserved.
Big Data can enable tangible savings and potential intangible up-side transforming a traditional CFO department into Data-Driven CFO organizationThe value at stake for the CFOFrom issue To outcome
Poor data quality and technology inefficiency
Today
-5%
-10%
-20%
Non-harmonized
reporting Non-alignedprocesses
Alignment ofprocesses
Harmonizedreporting
Centralized data
sources
Traditional CFO Department The Data-Driven CFO Organization
+30%+50%
+15%
+5%
Cost of inefficiency
Cost Reductions
-35%
Further Up-side
Data-driven decision making
- Discovery of
new business
opportunities
Issue OutcomeThe impact of growing business constraints and regulatory requirements often result in greater inefficiency and costs. Poor data quality, outdated technology and misaligned data processing can lead to inconsistent information and greater difficulty in executing strategy. Based on our experience, such a situation could lead to significant cost increases (up to 50%).
Our experience indicates that high-performance CFO organizations can benefit from significant and tangible cost reductions (up to 35%) and potential intangible up-side. A new operating model to manage data (based on the alignment of data processes, high standards in data quality, new technologies, harmonized reporting and new analytics capabilities) can help sustain profitability and return on equity.
Tangible Costs Tangible Cost Reductions Intangible BenefitsTomorrow
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Accenture Point of View:– Exploring Next Generation Financial Services: The Big Data
Revolution• https://www.accenture.com/us-en/insight/big-data-revolution-
next-generation-financial-services
16
For More Perspectives on Big Data and Financial Services
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Legend• 236: Internal control systems for Italian
banks• 236 (8): Information security for Italian
banks• AML IV: Anti-Money Laundering IV• AnaCredit: Analytical Credit Datasets
project • CCD: Consumer Credit Directive• CRS: Common Reporting Standards• EMIR: European Market Infrastructure
Regulation• FRTB: Fundamental Review of Trading
Book• IFRS 9: International Financial Reporting
Standard 9• Liikanen: Liikanen Report• MAD II: Market Abuse Directive II• MIFID: Markets in Financial Instruments
Directive• PRIPS: Packaged Retail Investment
Products• PSD II: Payment Services Directive II• Reg. EU Privacy: Protection of personal
data• RDARR: Risk Data Aggregation and Risk
Reporting• SREP: Supervisory Review and Evaluation
Process• SRM: Single Resolution Mechanism • SSM: Single Supervisory Mechanism• Supervisory Reporting EBA (European
Banking Authority): New technical standards for regulatory reporting
• Transparency Bankit: Transparency exercise on RWA composition
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References1. “Just Using Big Data Isn’t Enough Anymore,” Harvard Business Review,
February 9, 2016. Access at: https://hbr.org/2016/02/just-using-big-data-isnt-enough-anymore
2. “Gartner: Majority of Banks Will Turn to Cloud for Processing Transactions by 2016,” Information Week, Bank Systems & Technology, October 16, 2013. Access at: http://www.banktech.com/management-strategies/gartner-majority-of-banks-will-turn-to-cloud-for-processing-transactions-by-2016/d/d-id/1296641
3. “Just Using Big Data Isn’t Enough Anymore,” Harvard Business Review, February 9, 2016. Access at: https://hbr.org/2016/02/just-using-big-data-isnt-enough-anymore
4. Ibid5. “What is Big Data,” HRBoss Blog, infographic, February 3, 2014. Access at:
https://hrboss.com/blog/2014-02-03/what-big-data-infographic6. ”Global Big Data IT Spending in Financial Sector – Market Research 2015-
2019,” Technavio. Access at: http://www.technavio.com/report/global-big-data-it-spending-in-financial-sector-market-research-2015-2019
7. “The Future of FinTech and Banking,” Accenture 2015. Access at: https://www.accenture.com/us-en/insight-future-fintech-banking
8. Ibid
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The Big Data Revolution: The Next Generation of Finance Disclaimer This presentation is intended for general informational purposes only and does not take into account the reader’s specific circumstances, and may not reflect the most current developments. Accenture disclaims, to the fullest extent permitted by applicable law, any and all liability for the accuracy and completeness of the information in this presentation and for any acts or omissions made based on such information. Accenture does not provide legal, regulatory, audit, or tax advice. Readers are responsible for obtaining such advice from their own legal counsel or other licensed professionals.
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