Capgemini Smart Analytics Solutions Platform for Banking

2016
Capgemini Smart Analytics
Solutions Platform for Banking
Powered by IBM
IBM World of Watson October 24-27 | Mandalay Bay, Las Vegas

Copyright © Capgemini 2016. All Rights Reserved
Capgemini Smart Analytics Solutions Platform | IBM World of Watson | October 24-27 | Mandalay Bay, Las Vegas
for Banking
Capgemini’s Smart Analytics Solutions Platform
Generate actionable Insights from Data
2
Quickly Ingest data from
different sources
Apps
Closed
Loop
Service
Wealth
Manage-
ment
Next Best
Offer Voice of
Customer
… Many
More
Loyalty
Management
Apps Gives flexibility for
discovery analytics
Segments Data
Customer Data
Enterprise Data
Market Data
Web data
SMART ANALYTICS
Solution Engine
Powered by IBM
Remove noise and drive
insights out of data
Targeted Use-case solutions, in the form of a pre-built analytics and user engagement tools that deliver predictive capabilities specific to a particular
use case, that in turn drives more relevant, more personalized and more timely offers through Dashboards, Marketing systems.
The result is increased sales, and profitability, at the same time reducing operational costs and improving customer and associate relationships.

for Banking
Capgemini’s Smart Analytics Solution Applications
3
Smart
Analytics
Platform
Connecting all customer
touch points
To enable better social
customer service
To proactively provide prospects
information to financial advisors
To enable predictive intelligence
on customer data
To provide relevant next best
offers
To analyze voice of customer
in near to real time
To enable location based
offering
Powered by IBM

for Banking
Solution Application Benefits
4
Faster Implementation: 40-50% efforts saving due to pre built application models
720 Customer View
 Business Metrics Improvement – Revenue, Profit etc…
Closed Loop Service
 Improved Customer Lifetime value
 Higher Loyalty and Affinity
 Increased retention rates
Voice of Customer
 Increased retention rates
 Lower Customer Acquisition Rates
Next Best Offer
 Improved Products per Customer
Wealth Management
 Improved Customer experience
 Improved Conversion rates
Loyalty Management
 Improved Conversion rates
Predictive Customer Intelligence
 Get instant answers with Search-Driven and Voice-Driven
Analytics
Customer Acquisition
 To identify prospect through social channels

for Banking
 Profile-based: Move from generalized segmentation to personalization
customer demographics, providing a “segment of one.
 Behavior-based: Determine customer affinity through individualized
understanding of customer insights coming from interactions, enterprise
assets, dark enterprise assets and external assets, not just
observations. Use these assets and customers’ behaviors to truly
understand your customer and drive personalization.
 Collaboration-based: Customization should extend to integration with
relevant tools, relationships and touch points.
 Adaptive: Personalization features should leverage explicit consumer
feedback as well as implicit feedback from closed-loop consumer
responses and be flexible to changing behaviors and attitudes.
 Channel-optimized: Identify and personalize combinations of markets,
segments and media tactics to adjust integrated marketing efforts to
optimize market-specific channel effectiveness.
720 Customer View – Application
5
Payment
History720 Integrated
Customer
view
website
Kiosks
In-Store
POS
Direct Mail
Search
Client
Centers
Call
Center
Customer
Service
Online
Advertising
Mobile
@
SMS/MMS
Emails
Social
Media
Events
Transactions
Orders
Usage
History
Purchase
Stage
Needs
Desire
Preferences
Opinions
Attributes
Demographics
Characteristics
Email/Chat
Call center
notes
Web click
streams
In-person
dialogs
Five key elements of personalization

for Banking
Next Best Offer – Application
Right OFFER to Right CUSTOMER at Right TIME with Right MESSAGE
6
 Customer Profiling: Identify the behavioral features of customers who
buy certain products and tailor cross and up sell offerings
 Interaction Behavior: Track interaction behavior and navigation
behavior
 Purchasing Knowledge: Track purchasing history and paths
 Efficient Campaigns: Determine the best channels and times to
communicate with customers
 Accurate prediction: Use advanced analytics to predict customer-
product opportunities
 Automation: Implement cross and upwelling strategies systematically
with Big Data Analytics Workflow
Solution Features (Personalized Offer)Predictive Analytics – Clustering, Segmentation, Propensity
Business Rules
Data Input
Customer
Data
Clickstream
Data
Social
Channel
Transactions
Data
Data
Integration
and
Event
Correlation
Multi
Channel
Delivery
Customer
Action
External and
Internal
Events –
Credit Score
Changes/
Disaster
Policy
and
Regulations
Mapping
with
Services
Life
Events
General
Preferences
Real Time
Decision
Engine

for Banking
Closed Loop Service – Application
Harnessing the power of social media as Customer Service Channel
7
 Real time capturing, setting up prioritization and resolution of customer
complaints
 Text Mining to discover business problems and mapping with universal
taxonomy
 Detecting early signals and business areas (like products, training
needs, business functions) requiring improvement
 Event/News Analytics
 Leveraging new channels like social with high presence of current
generation customers to decrease operating costs from traditional
channels
 Connect Customer journey by having a single consolidated view of a
customer touch points & identify their preferences
Solution Features
Tweet
Channel
Severity
Category
Customer Data
Tone of
complaint
Customer
Segment
Geo Information
Previous
Interactions
NPS
Post Reply Data
Event/News
Analytics
Voice of
Customer
Dashboard
DashboardMapping
Unified Identity
Customer Data is pulled
Customer touch points
data Customer
Transaction Data
Customer Segment
Customer
Tweet
Customer
Tweet with
Sentiment
Sentiment
Analysis
Taxonomy
to classify
the
complaint
Business
Rules
to Identify
Severity of
Complaint
Alert
Email
Triggered
to
Manager
Cluster
Trigger
Agent Response

for Banking
Voice of Customer – Application
8
 Identify relevant topics and performed a rich analysis of consumer
discussions across multiple social channels to more effectively engage
with target consumers.
 Analyze customer data with Natural Language processing.
 Near real-time alerting of emerging trends based upon business rules.
 Deep dive analytics on attrition and retention drivers.
 Machine learning approach to improve classification and mapping with
business drivers
 Sentiment scale of 5 to understand the intensity and for prioritization
Solution FeaturesCapgemini Social Media
Engagement Key Service Components
 Filter the Noise
 Gather High-Level Sentiments
 Identify Key Influencers
 Understand Root Causes
 Problem-Solve
 Amplify
 Influence
Leverage Identified Opportunities to:
 Better the Client Experience
 Increase Revenue
 Lower Cost
ANALYZE
ENGAGE
LISTEN

for Banking
Wealth Management – Application
9
 Integrate data from different sources and provide single, UNIFIED
customer view
 Track assets anywhere automatically so that financial advisors know
BEFORE their clients
 AGGREGATE information even before having first introductory meeting
 Helps in generating SALES FUNNEL
 Identify circle of INFLUENCE which helps in converting prospect into
client
 Advisers can improve client EXPERIENCE and enhance their ability to
deliver high-quality advice
 Mobile application enables the advisor to access the solution from
anywhere, anytime
 Analytical representation of information results in quicker decision
making
 Easily Integrate with Other Applications for Comprehensive
Functionality
Solution Features
Social Media
Integration
Connectivity
with Market
data Providers
Prospect
Engagement
Customer
Acquisition
Customer
Servicing
Customer
Information
Internal
Data
Portfolio
Watch
Smart Analytics: Wealth Management Solution
Interfacing Systems

for Banking
Loyalty Management – Application
10
 Using real time geo location data to understand customers requirement
more at micro level
 Helps organizations to have better cross Sell and Up Sell
 Help financial organization to improve margins and better Targeting
Organization goal.
 Minimize client attrition because offers will be as per customers need
and easy access.
 Process is different from traditional marketing. Offers are here more
customer centric and real time.
 Increase customer life time value of customers
Solution Features

for Banking
Predictive Customer Intelligence – Application
11
 Search-Driven Analytics and voice-driven analytics for business users
 Answers complex queries in seconds
 Enable predictive intelligence on customer data
 Guided search experience designed for data analytics that anyone can
use with zero training
 Improve various business drivers accelerating decision with search-
driven and voice-driven analytics
 Anyone can be their own data analyst
Solution Features
Show Customer with debt funds by age among
blue-collars
Display Customer having credit cards by state
Show Job Distribution among males in New York
Who is going to buy debt funds in New York
Predictive
Intelligence
Recent
Queries
New Query

for Banking
Smart Analytics Solution Platform – Logical Architecture
12
The Smart Analytics Solution sticks to a general architecture that is shared among all use
cases.
An application data sources can be:
 Non real-time (suitable for batch processing)
 Real-time (require stream-like processing)
Data Ingestion & Acquisition:
 Python based scripts utilizing various APIs
 Perform data gathering, and basic preprocessing
Business data Lake:
 HDFS as data warehouse
 ML models & rules
Hadoop layer:BigInsights
 Combination of HBase and Hive for data with low structure
 Bigmatch social profile will be match with MDM golden record and persisted in Hbase.
 GraphDB for social network related data
 RDBMS for well defined, structured data.
Analytics
 Currently :Python script, reading data from banks . Proposed BigIntegrate and BigQuality
systems
 Predictive Customer Insight Models readily available in SPSS.
The Smart Analytics Platform sticks to a general architecture that is
shared among all use cases
Real-time data (streaming)
Financial
Advisers
Business
Users
Power
Users
Non real-time data (batch processing)
Cognos
Analytics
Watson Analytics
Watson SMA
Services
Social Data
Bank internal data
External sources: Zillow,
FICO, and other
Transactions
Communication
channels
Marketing
Team
Data Ingestion & Acquisition Layer
Predictive Customer Insight SPSS
SPSS Modeller Batch and
Realtime Recommednations
Watson Services/API’s
Big Match
BigInsights
Customer MDM
dashDB
Core Addon
BasedontheIBMBluemixtechnology

for Banking
Some IBM Watson Services integrated with our solutions
13
Language Speech Third party
Alchemy
Data News
Alchemy
Vision
Data Insights
Speech

for Banking
Three Physical Deployment Models
14
The Capgemini Smart Analytics Solution Platform is available in a traditional On Premise deployment,
On Cloud hosted on IBM Softlayer, or As-A Service on IBM Bluemix.
On Premise – Traditional deployment for
implementations requiring tight integration
with existing systems and low latencies.
Softlayer Cloud deployment provides
fast implementation, lower cost, and
flexible configuration.
Bluemix deployment provides
immediate deployment and a fully
managed As-a-Service simplicity.

for Banking
3 Capabilities of Capgemini Smart Analytics Platform
15
 Quickly ingest all data, adaptive models
Scalable
and Agile
 Gives flexibility for discovery analytics
Speed to
Value
 Achieve fastest time to value by reducing complexity
Insights
as a
service
UNIFIED
VIEW

for Banking
Key Solution Platform Features
16
Unified
Solution
Pre Built Business
Taxonomies
Better Customer
Mapping
Real Time
Analytics
User Friendly
Interface
Pre-built Statistical
Models
Closed Loop Analytics
Measure
Indirect Impact

for Banking
Capgemini Analytics Ecosystem for Financial Services
18
Optimize Operations Manage Risk Improve ExperienceReduce Churn
Customer Behavior and
Marketing Analytics
Operational Analytics Risk & Fraud Analytics
People
Analytics
Asset/Equipment
Analytics
Grow Customers
Historical Contextual Predictive Prescriptive
Logical Data Access Layer
On Premises Cloud Open Source Partners
Data Integration and Governance

for Banking
Analytics Use Cases for Financial Industry
19
Closed loop Service
Next Best Offer
Real Time Location based Offerings
Micro Segmentation
Single View of Customer
Customer Gamification
Voice of Customer
Customer Life Event Analytics
Customer Data
AML
Network Analysis
MIS regulatory reporting
Real Time Topic Analysis
Single View
Reputational risk Management
Indirect Risk Exposure Analytics
Event Detection
Fraud and Risk
B2B Merchant Insight
Clickstream Analytics
IVR Analysis
Transactions Data

for Banking
Capgemini has global experience in Insights and Data delivery
20
 Delivery of projects with Capgemini Insights and Data
Practice gives our clients access to:
• Over 11,000 consultants focused on Insights and Data
globally.
• 2,000+ Financial Services domain focused insights and
data resources.
• Experience working with:
- 7 of the top 10 global banks,
- 12 of the top 15 global insurers,
- 8 of the top 10 global diversified financial firms
• An unmatched (and vendor independent) depth of
technology experience. Capgemini works with all major
analytics, data management and infrastructure vendors.
• Comprehensive experience in the analytics domain,
including the analysis of unstructured and social media
data
Outstanding Collaboration
Award 2011
Most valuable
partner award 2010
IIG President’s award
for Customer
Satisfaction 2012
S E R V I C E
S
GLOBAL
ALLIANCE
PART NE R
Pinnacle Awards
1 in 2013, 2 in 2012
1 in 2011, 2 in 2010
Innovation award
2009 & 2010
Epic award 2011
& 2012 APEX
Award 2013
Diamond Partner
BI Specialized Partner
Global Applications
Partner of the Year
Award 2012
Software's Most
Innovative Alliance
Partner of the Year
2011
Services Partner of
the Year award 2012
Global Partner
North America
United Kingdom
India

About Capgemini
With more than 180,000 people in over 40 countries, Capgemini is
one of the world's foremost providers of consulting, technology and
outsourcing services. The Group reported 2015 global revenues of
EUR 11.9 billion. Together with its clients, Capgemini creates and
delivers business, technology and digital solutions that fit their
needs, enabling them to achieve innovation and competitiveness.
A deeply multicultural organization, Capgemini has developed its
own way of working, the Collaborative Business Experience™, and
draws on Rightshore®, its worldwide delivery model. www.capgemini.com
The information contained in this presentation is proprietary. © 2016 Capgemini. All rights reserved. Rightshore® is a trademark belonging to Capgemini.
For more details contact:
Ramana Bhandaru – Vice President Financial Services
ramana.bhandaru@capgemini.com

Capgemini Smart Analytics Solutions Platform for Banking

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