leveraging geo-spatial (big) data for financial services solutions

© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Leveraging Geo-Spatial (Big) Data for Financial Services Solutions Ernest Martinez (Capgemini), Guillaume Runser (HP), Stephen Williams (Capgemini)/ 4.12.2014 #HPDiscover

© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 2

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Session DT6127 Speakers: Ernest Martinez, Guillaume Runser, Stephen Williams

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How Big Data is impacting the Insurance industry


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


“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

“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

Big Data is recognized throughout the Financial Services Industry as a key competitive lever


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

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

82%

86%

88%

96%


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?

•  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?


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?

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

=

Enhancing Financial Services Solutions with Geo-Spatial Data


•  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.

Leveraging Geo-Spatial Big Data for Financial Services Solutions


Geographic

Political

Economic

Crime

Social Media

Natural Perils

Dashboards with Drill Down Analytics

Client External Data Sources

Enables advanced spatial reasoning to support applications in pricing, claims, including reserving, and fraud. Provides for the integration of other types of external data

Client Internal Data Sources

Accounts

Products

Customer

Claims

Geo

-Spa

tial D

ata

Incorporating Geo-Spatial Data into the Reference Architecture enhances Financial Services Solutions

HAVEn

Data Integration, Analytics, ETL and data store


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

In the UK, Ordnance Survey Data has been incorporated into the Big Data Reference Architecture


•  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

Highly-Granular Geo-Spatial Data provides enhances risk analysis

Commercial Insurance Risk Analytics on HP HAVEn


“60% of insurance firms affirm that underwriting systems technology provides high or very high value to their company1.”

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”.

“86% Insurers agree that analyzing multiple-source data together, rather than separately, is crucial to making accurate predictions2.”


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

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.

Introducing a “one-stop shop” for collecting, synthesizing, and analyzing risk data


“Plug and play” capabilities display risk data exactly how you want it

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

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.

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.


Architected to provide a powerful, single data resource

HAVEn

Political

Economic

Crime

Risk Density

Customer

Claims

Geographic

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


100% of your data 1000x faster answers

1.2 month ROI *

1,000,000+ machine events per second

30x More data per server

700+ connectors

* Source: Forrester Consulting, April 2013

Big Data Cloud Mobility Security

H A V E n

Hadoop/ HDFS

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


Backed by a business-driven approach, CIRA directly addresses real client challenges

Business-driven approach to the definition and development of intellectual property removes a significant amount of risk for our 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

CIRA core concept originated in a workshop with one of our global insurance clients

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

Accelerated time to market with ability to move from concept to prototype within 45 days.

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.

Solution demonstration


Information on CIRA is also available on YouTube https://www.youtube.com/watch?v=Qr8tAEsRI0Y

CIRA – The Commercial Insurance Risk Analytics Platform


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: [email protected]

•  Visit the HP HAVEn Partner Solution booth at HP Discover

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