For effective decision making, Big Data needs to be delivered at the right level of granularity at the right time. Capgemini’s FS BIM Innovation Practice, working through our Mastermind and Greenhouse processes to ensure a focus on real-world client issues, has developed a Reference Architecture (RA) based upon HP HAVEn to achieve these goals. While Geo-Spatial Data has traditionally been applied to non-FS domains, effective application of this data has the potential to improve decision-making in FS, including in the areas of underwriting and pricing, claims, and bank and credit card fraud. Presented at HP Discover Barcelona 2014 by: Guillaume Runser - WW Solutions Marketing, HP Ernest Martinez - Global Head - FS BIM Banking, Capgemini Stephen Williams - BIM Innovation Practice Head, Capgemini

1. Leveraging Geo-Spatial (Big)
Data for Financial Services
Solutions
Ernest Martinez (Capgemini), Guillaume Runser (HP), Stephen Williams (Capgemini)/
4.12.2014
#HPDiscover
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2. Please give us your feedback
Session DT6127 Speakers: Ernest Martinez, Guillaume Runser, Stephen Williams
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3. How Big Data is impacting
the Insurance industry

4. Is the insurance industry keeping up
with the changing risk environment ?
“Insurers and brokers are trying to get their arms around the challenges
better. I think part of the answer is investing in research and development;
making better use of the vast amount of data available and perhaps looking
at solutions with a greater degree of innovation - without discarding the
fundamentals of insurers managing their books of business in a way that has
served them well in times of financial turmoil for other sectors.”
• President of FERMA
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

5. Big Data is recognized throughout the Financial Services Industry
as a key competitive lever
“No other industry has more to
gain from leveraging Big Data
than the financial services
sector..”
Market Watch, Big Data in Financial Services Industry
“Financial services companies
should be looking to emerging
big data tools as the answer to
finding hidden consumer
sentiment on a real-time basis.”
Putting Big Data to Work for Financial Services
Companies
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
“82% of those surveyed in the
Chartered Institute of Loss
Adjusters believe those insurers
that do not capture the potential of
big data will become uncompetitive”
The Big Data Rush
”Part of the answer is investing in
research and development is
making better use of the vast
amount of data available and
perhaps looking at solutions with a
greater degree of innovation”
President of Federation of European Risk Management
Associations
“The visionary bank
needs to deliver
business insights in
context, on demand,
and at the point of
interaction by
analyzing every bit of
data available”
Financial Services Data Management: Big
Data Technology in Financial Services

6. Most insurers agree on Big Data’s potential for competitive
advantage
Believe those insurers that do not capture the
potential of Big Data will become uncompetitive
Agree that analyzing multiple-source data
together, rather than separately, is crucial to
making accurate predictions
Agree that linking information by location is key
to usefully combining disparate sources of Big
Data
Say that the digitally-enabled world will see the
emergence of new risk rating factors
82%
86%
88%
96%
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Source: the big data rush: how data analytics can yield underwriting gold. Survey conducted by Ordnance Survey and the Chartered insurance Institute, 25 April 2013

7. A wealth of data exists inside and outside the organization that
could improve risk assessment
• Geographic and Geo-Spatial
Is the facility located in a site prone to natural disasters?
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
• Political
Is the facility located in a region of political stability/instability?
• Economic
Is the facility located in a high, middle, or low economic area?
• Crime
Is the facility located in a high crime area?
• Risk Density
What are the nearby risk
factors?
• Customer
Personal details, claims history, other policies ?
• Claims
How many claims have been made in this area?

8. The challenge is to integrate large volumes
of varied data and make it accessible
How do separate the
data I need from the
vast data that exists?
How and where can I
access the data I
need?
How do I identify new
data sources to mine
for relevant
information? How do I analyze data
in multiple formats from
disparate sources?
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Business impact
Delays and inefficiencies in
collation of data required for
informed decision-making
Inability to treat risks individually
and assess accurately
Inability to use data proactively
and lack of predictive
capabilities
=

9. Enhancing Financial Services
Solutions with Geo-Spatial Data

10. Leveraging Geo-Spatial Big Data for Financial Services Solutions
• To be useful to decision makers, Big Data needs to be delivered at the right level of granularity at the right time
• Capgemini’s FS Business Information Management (BIM) Innovation Practice, working through our Mastermind
and Greenhouse processes that ensure a focus on real-world client issues, have developed a Reference
Architecture for Big Data based upon HP HAVEn to achieve these requirements.
• Geo-Spatial Data has traditionally been applied to problems in oil and gas as well as utilities. However, effective
application of this data has the potential to improve decision making in FS, including in the areas of:
• Underwriting and Pricing – Individualized Risk Assessment
• Claims – Adjuster Placement and Fast Claim Payouts
• Bank and CC Fraud – Point of Sale Cross Referencing
• Capgemini BIM Innovation is currently working with HP to incorporate geo-spatial data and reasoning into our
Big Data Reference Architecture using our Commercial Insurance Risk Analytics (CIRA) platform as a use case
• Through the inclusion of geo-spatial data and reasoning, and incorporating the power of Autonomy/IDOL to
integrate these data, the depth of solutions we provide to our clients will dramatically increase.
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

11. Incorporating Geo-Spatial Data into the Reference Architecture
enhances Financial Services Solutions
Geographic
Political
Economic
Crime
Social Media
Natural Perils
Client Internal Data
Sources
Accounts
Products
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Dashboards with
Drill Down Analytics
Client External Data
Sources
Customer
Claims
Enables advanced spatial reasoning to support applications in pricing, claims, including reserving, and fraud.
Provides for the integration of other types of external data
Geo-Spatial Data
HAVE
n
Data Integration,
Analytics, ETL
and data store

12. In the UK, Ordnance Survey Data has been incorporated into the
Big Data Reference Architecture
The Ordnance Survey supplies data for FS in the UK by providing geographic information available to:
• Develop Policy
• Plan
• Deliver Services
• Monitor Success and Risk
• The Points of Interest (PoI) database contains over 4 million unique places with over 600 classifications
• As a strategic alliance partner Capgemini have full access to all historic data sets for free on a 3 year contract
Key Uses:
• Identify the use and function of different
premises to enable accurate risk assessment
• Monitor, track and analyse the changing retail
space of city centres over time
• Locate crime hotspots by PoI
• Advanced OS API mapping tool for triangulation
of risk factors
• Link to core unstructured data sets
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

13. Highly-Granular Geo-Spatial Data provides enhances risk analysis
• Points of Interest (PoI): Identification of hundreds thousands of PoIs provides
for more accurate risk assessments:
• Proximity of risks
• Nature of risks
• Going beyond the Postcode Level: Building level data provides additional
data to the assessor supporting individualized pricing as well as claims:
• Distance of building from property line and access road
• Height above sea/ground level
• Estimated building size
• Vector Mapping: Providing for complex spatial analysis to determine risk and
exposure
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

14. Commercial Insurance Risk
Analytics
on HP HAVEn

15. “60% of insurance firms affirm that underwriting
systems technology provides high or very high value
to their company1.”
“86% Insurers agree that analyzing multiple-source
data together, rather than separately, is
crucial to making accurate predictions2.”
Commercial Insurance Risk Analytics:
Harnessing Big Data for Underwriting Efficiencies
Source: 1 CEB FSI Technology Survey, 2013–2014
2 Ordnance Survey “ The big data rush: how data analytics can yield underwriting gold”.
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

16. Introducing a “one-stop shop” for collecting, synthesizing, and
analyzing risk data
Capgemini Commercial Insurance Risk Analytics (CIRA), powered by HP, gives underwriting
professionals unprecedented access to accurate, granular information on
individual risk factors for a much more informed, faster risk assessment and
the ability to lower overall operating cost across the portfolio.
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Multiple sources
integrated for real-time
decision making
Supporting risk
assessment on an
individual policy basis
for enhanced
accuracy
Providing the right
data for the right
decisions
Enabling a focus on
the business of
underwriting

17. “Plug and play” capabilities display risk data exactly how you
want it
Through the integration of big data and our Rapid Data Visualization capabilities, Capgemini brings the right data
in the right format, customized for underwriters and providing for comprehensive decision support.
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Finely-grained risk data from
multiple external sources ( such as
social media), integrated with the
insurer’s own data
(such as policy and claims)
Dashboard displays with full drill
down analytics capability into the
underlying data
Our Rapid Data Visualisation methodology will be used to define a set of dashboards measuring risk grouping that
are drillable to policy risks and further to supporting data.

18. Architected to provide a powerful, single data resource
HAVE
n
Geographic
Political
Economic
Crime
Risk Density
Customer
Claims
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
CIRA
Dashboard
Data
Integration,
Analytics, ETL
and data store
Structured and
unstructured data
sources
Integration of Multiple data sources for
real-time decision making
Granular Risk Data for
increased accuracy

19. Big Data Cloud Mobility Security
100% of your data 1000x faster answers
1.2 month ROI *
H A V E n
1,000,000+
machine events per second
Hadoop/
HDFS
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
30x
More data per server
700+
connectors
* Source: Forrester Consulting, April 2013
Autonomy
IDOL
Vertica Enterprise
Security
nApps
Catalog massive volumes
of distributed
data
Process and index all
information
Analyze at extreme scale
in real-time
Collect & unify machine
data with ArcSight
Logger
Powering HP Software +
your apps
Social media Video Audio Email Texts Mobile Transactional
data
Documents IT/OT Search engine Images
HP HAVEn – Making Sense of the Noise

20. Backed by a business-driven approach, CIRA directly addresses
real client challenges
Capgemini intellectual property (IP) development originates from ideas, pain points, and issues
of our insurance clients and involves clients and independent industry experts throughout the IP
lifecycle.
Business-driven
approach to the
definition and
development of
intellectual property
removes a significant
amount of risk for our
clients
CIRA core concept originated in a workshop
with one of our global insurance clients
Independent underwriting firm qualified
to QA the CIRA - Proof of Concept (PoC)
PoC is being demonstrated to multiple
insurers in the EU and NA for feedback,
shaping the next stage development
Accelerated time to market with ability to move from
concept to prototype within 45 days.
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Capgemini Financial
Services
• 20 years of Insurance experience
• More than 6,000 dedicated
insurance professionals
• Currently serving 11 of the top 15
insurance companies*
• 3000+ BIM experts dedicated to
financial services
*Ranked by revenue; Forbes ‘The Global 2000’ for 2013

21. Solution demonstration

22. CIRA – The Commercial Insurance Risk Analytics Platform
Information on CIRA is also available on YouTube
https://www.youtube.com/watch?v=Qr8tAEsRI0Y
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

23. More information
• Capgemini CIRA web : www.capgemini.com/cira/hp
• HP HAVEn: www.hp.com/HAVEn
• CIRA Solution Brief: http://bit.ly/1nVPdoM
• CIRA demo video: http://bit.ly/1rmqXsX
• Webinar: Empower Commercial Lines Underwriters with Data, Analytics, and Secret Sauce
http://bit.ly/1pEkHMH
• Request a live demonstration of CIRA: HAVEnAlliancesMarketing@hp.com
• Visit the HP HAVEn Partner Solution booth at HP Discover
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.