Banking on Big Data: Harnessing Big Data to drive valuable BigDecisions

Ian WestHead of Enterprise Information Management

| ©2014, Cognizant

Key Discussion Points

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BIG DATA AND ANALYTICS IN FINANCIAL SERVICES

KEY TRENDS SHAPING YOUR INDUSTRY

ABOUT COGNIZANT

BIGDECISIONS2.0TM

REAL WORLD EXPERIENCES

| ©2014, Cognizant

CognizantFrom internal consulting unit to a market leading Global Services Provider

1223+ Active Customers

$8.84 Billion2013

178,600+Employees Globally

20, 000+ Projects in 40 countries

25+ Regional Sales Offices

75+ Global Development CentresFinancial Services: 42.3%

Healthcare: 25.4%Retail, Manufacturing & Logistics:

21.1%

20.4%

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Emergence of Big Data and AnalyticsIncreasing belief in its potential to create competitive advantage

of banking organisations globally have invested in big data1

>34%

Between 2012- 2017, the uptake of big data analytics amongstlarger enterprises in the UK will more than double to ~30% of organisations 3

30%

of large global companies will have adopted big data analytics for at least one Security or Fraud Detection Use Case by 2016 (up from 8% today) 2

25%

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Big Data and Analytics drive business value

“Leveraging

the power

of big data

& analytics

to drive

valuable big

decisions”

Business value

Big Data & Analytics

Traditional Analytics & BI

Improved understanding of customer

Information based business decisions

Deeper insight into risk

Increase revenue

Reduce cost

Mitigate risk and ensure compliance

Additional data sources to enrich customer profiles Variety of unstructured information to better

understand context Real time analysis

Structured & transactional customer data Ad hoc & retrospective pattern analysis

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Corporate Listening - Voice of our customers

Identify the right customer for the right product at the right

price at the lowest risk to improve revenue and

profitability

Deal with aggressive and innovative non-bank

competitors by leveraging data as an asset

Develop new and reliable sources of revenue & increase

business value of customer relationship through analytics

Incorporate mobile banking as a regular delivery channel &

develop a strategy around social media to personalise

engagement with customers

Achieve & monitor regulatory compliance across Line of Businesses and Business

Functions

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Big Data & Analytics can be leveraged across multiple areas in the Financial services industry

Improving branch & channel efficiency and effectiveness

Helping to drive high value, high touch traffic back to branchesCustomer

Centricity

Improved targeting of customer segments Moving from a product to customer focus Better management of sales leads across

channels Inclusion of customer incentives to

influence behaviour

Reduce Costs &Increase

Revenues

Branch, ATM Online, Mobile Omni-channel Channel management & integrationEveryone’s

Mobile

Sentiment analysis Social media analysis Credit analysis Customer profitability & lifetime value Predictive analytics

CustomerInsight

Ability to process increased volume & variety of data

Cost effective technologyTechnology Advancement

Risk & capital management, Risk adjusted pricing

Portfolio risk management, Fraud/AMLRisk & Compliance

Management

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The Data You Need is Everywhere Around You!Big Data and Analytics Opportunity in Banking

To deliver the best customer experience, banks need to

• Augment internal data with external data assets to

enrich customer profile

• Provide customized products and services

• Personalise communication in a timely, relevant and

impactful manner

Customer profileintegration

Customerexperience analysis

Customer preferences & behaviour analysis

Customer sentiment analysis

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Big Data and Analytics Opportunity in Retail Banking Breaking Siloes and Analysing Raw Data from Multiple Sources

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Example Outcomes

Profile Contact History Transaction Models

Big Data Analytics

Customer View

Integrated Web Intelligence

The Web Visit• What searches?• How did they get you?• Page navigation

Research• What do they look at?• What do they search?• Do they dig deeper?

Purchase Path• Which product?• How far into the process?• What’s looked at during

purchase?

Social Media

Verbatim• Blogs• Tweets• Postings• Reviews

Internal Text Data

Research• Verbatim• Ad-hoc• Longitudinal studies• NPS/Satisfaction

Other Direct Contact• Branch interview Records• Branch Enquiries• Manger Notes• E-Mails

Call Center• Queries• Complaints• Service issues

Micro-segmentation

Higher Quality Leads

Better Fraud Detection

More accurate Propensity Models

Multi-channel Customer Sentiment

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Changing Regulatory EnvironmentFinancial organisations’ leverage Big Data Analytics

Cost-reduction programmes, de-risking & price adjustments

Manage ROI in the new environment

Reduce capital and liquidity inefficiency Balance-sheet restructuring

Business-model adjustments

Achieving compliance with evolving regulatory norms

Strategic planning for the BASEL III world

Capital & risk strategy

Implementation management

Challenges Response

RiskCompliance

Gove

rnan

ce

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Risk Management Office (RMO)

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Predict risk & provide

guidelines

A scientific, intuitive statistical

model

Risk CatalogingRisk

Analytics engine

Unique risk management

model

Identify the right project

non-invasively

Tangible Value to Customers

Framework

‘Entry Strategy’ Solutions ‘Account Expansion’ Solutions

Rules-based project evaluation

engine

Enhanced data quality pertaining to schedule, testing and effort

Help create a model for future engagements

Integrated scientific, statistical & human intelligence to predict risks

Single authority for proactive

Risk Identification for existing &

new age delivery

methods taking a holistic view

across an engagement

lifecycle.

Vision

RMO - One stop shop for risk expertise through proactive risk identification, tracking & mitigation of program risk including financial, customer, execution, governance, solution and stakeholder management

| ©2014, Cognizant

RiskProfiling

Big Data Use Cases in Financial Services

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Business Impact Big Data Capabilities

Customer Churn Timely prediction and reduction of churn

Include customer contact (e.g. call centre transcripts) & social media data

Analyse customer sentiment Model and score churn propensity

Cross andUp-selling

Efficient and precisely targeted marketing Increased Cross- and Up-sell

Analyse & model response behaviour Select campaign addresses based on micro-segmentation

Data Offloading Performance & scalability Increased performance and storage

Enabled power of analytics on wealth of data

Segmentation Client lifestyle analysis and spend

prediction Increased customer satisfaction

Advanced analytics to enhance client lifestyle analysis and profiling

Predictive analysis of spend

Domain

Comprehensive risk profiling Improved risk evaluation

Refine risk profiling models frequently to adapt to dynamic business environment

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Introducing BigDecisions2.0TM

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BigDecisions2.0 Business Solution PlatformComponents providing agile delivery through focused business apps

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Robust Core Platform

Acquire, Manage and Use Any-Data

Rapid Value Delivery

Flexible, Agile & Economical

Relevant Business Apps

Intuitive, Focused and Bite-size BI & Analytics

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BigDecisions2.0 Business Solution PlatformA new paradigm for seamless, end-to-end information management & analytics value

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Sophisticated BI & Analytics

Leverage Universal Data

Select proven Technologies

Agility for Business Change

Easy to Build and Manage

Spend time on BI & Analytics, where it

matters most (not on building infrastructure)

Manage all-structures of data

with Universal Data Management

Deliver subject areas in weeks, not in months or years

Faster business value realisation

with proven set of technology options

Install, configure & customize, don’t develop

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Business App | Risk, Fraud & Compliance

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• Executive Dashboards around BASEL II/III and Adaptive Revenue Assurance• Machine-learning modules for fraud detection

and to strengthen entry to the real-time analytics market• Predictive analytics and new features to cover

areas in risk and governance prediction

• Smarter fraud detection capabilities reduce losses and improve recoveries

• Direct fulfillment of all CRO needs, providing them with business discovery tools and services

• Proactive risk management across LoBs and product lifecycles with stress testing and scenario analysis

RFC Data and Analytics Platform

• Flexible systems and processes to accommodate changing regulatory requirement

Holistic risk assessment, fraud detection and compliance application that ensures adherence to constantly changing regulatory requirementWhat?

App Features Benefits

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Representative Experiences

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Fraud Detection & Prediction @ Global Payment Processing

Company

• The accuracy of the fraud detection process was improved (~15%) and the speed of >400 million transactions

• Detect frauds within seconds and predict frauds within 8/16/32/48/72 hrs

Enhance fraud detection and prediction algorithm Historical data set was stored in a

Hadoop cluster (100+ nodes) Ran several algorithms to prepare

clustered data Neural network algorithm was

developed

Real-time Reporting @ Leading Financial

Services Company

• Response time was significantly improved

• Substantial performance gains were realised in data service aggregation scenarios by reducing the number of data service calls from RTM

PoC for conversion from Cognos to BOBJ

Infrastructure – Installed Hadoop, HBase, MySQL Performance tuning

NoSQL database for real-time service

Big data archive management for cost effective archival and retrieval

• 20% improvement in lead conversion

• Operational cost savings of 10 – 20%

• Greater NPS and customer satisfaction

Captured last 55 years of customer data involving 23 Million Customers, 13 Million Policies, 60 Million Claims, 8500 Active Products

Segmentation of customers leveraging machine-learning techniques

Churn analysis at each individual cluster level with combinations of net-worth, transaction volume and churn rate

Customer Segmentation and Churn Prediction @

Leading insurance major

| ©2014, Cognizant

In Summary

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BigDecisions Business Solution Platform: A platform-based approach to Universal Data Management with a suite of business ready analytical apps

Big Data and Analytics is a key driver in the financial services sector to help businesses run better & run different

Start small, think big. ROI on Big Data and Analytics is often too big to ignore

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BigDecisionsTM Business Solution Platformhttp://www.cognizant.com/enterprise-analytics/big-data

Thank You

| ©2014, Cognizant

Big Data Solution Frameworks & Platforms

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Pave the way to success

ScorelStock price analysis with prices, market

feeds, analyst quotes

iLASER LongitudinalAnalysis for Customer behaviour

GRecoGraph DB based

high performance recommendation

engineMIPS/DW

Offloading to Big data platforms for performance and

cost benefits

Delivery through BigDecisions 2.0 Platform – A Holistic Approach to EDM 2.0!

Industry Use Case Libraries

Solution Components

Reference Architectures

Proof of Value

Technology Frameworks

Proof of Concept

Big Data Analytics Value Assessment Framework (BAVA)

SmartNodeUnified access to

big data platforms for BI/Analysis

tools

iSMARTIntegrated Social Media Analytics and Reporting

PayNet GraphAnalyse Payment networks for Risk,

Fraud and targeted marketing

Churn Analysisusing big data and machine

learning