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
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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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Session DT6127 Speakers: Ernest Martinez, Guillaume Runser, Stephen Williams
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.”
“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
• 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
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
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
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.
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.