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


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?


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


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)


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


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


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


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


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


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

http://fsblog.accenture.com/finance-and-risk/global-consistent-standard-can-help-anti-money-laundering-efforts/?c=fs_frdfincrmsldshr_10000007&n=smc_0815

https://www.accenture.com/us-en/insight-big-data-revolution-next-generation-financial-services?c=fs_fnrsbgdtsmss_10000001&n=smc_0616


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


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

https://hbr.org/2016/02/just-using-big-data-isnt-enough-anymore

http://www.banktech.com/management-strategies/gartner-majority-of-banks-will-turn-to-cloud-for-processing-transactions-by-2016/d/d-id/1296641

http://www.banktech.com/management-strategies/gartner-majority-of-banks-will-turn-to-cloud-for-processing-transactions-by-2016/d/d-id/1296641

https://hbr.org/2016/02/just-using-big-data-isnt-enough-anymore

https://hrboss.com/blog/2014-02-03/what-big-data-infographic

http://www.technavio.com/report/global-big-data-it-spending-in-financial-sector-market-research-2015-2019

http://www.technavio.com/report/global-big-data-it-spending-in-financial-sector-market-research-2015-2019

https://www.accenture.com/us-en/insight-future-fintech-banking


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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the big data revolution: the next generation of finance

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