Learn how Markerstudy Group is driving growth and innovation. The general insurer uses both Cloudera Enterprise powered by Hadoop and SAS Analytics. With it's big data analytics platform, Markerstudy has achieved significant ROI including 120% increase in policy count over 18 months.

1. 1© Digital Reasoning & © Cloudera, Inc. All rights reserved.
Webinar: Insurers Capitalize on Big Data
Analytics and Hadoop
DATE: January 21, 2016
TIME: 11:00am ET / 8:00am PT

2. 2© Digital Reasoning & © Cloudera, Inc. All rights reserved.
Agenda
• Key Trends Impacting Insurers in 2016 and Beyond
• How Markerstudy Group is Driving Growth and Innovation with Big Data
Analytics
• Use of Cloudera Enterprise and SAS Analytics Across Key Areas in Insurance
• Q&A

3. 3© Digital Reasoning & © Cloudera, Inc. All rights reserved.
Our Speakers
Donald Light
Director, Property & Casualty
Celent
Dan Fiehn, CIO
Markerstudy Group
Stuart Rose
Head of Global Insurance Practice
SAS Institute
Maneeza Malik
Head of Global Insurance Practice
Cloudera Inc.
Nicholas Turner
Enterprise Data Architect
Markerstudy Group

4. © 2016 Celent, a division of Oliver Wyman
Insurance Trends for 2016:
Data, Analytics, Cloud
January 2016
Donald Light
dlight@celent.com

5. © 2016 Celent, a division of Oliver Wyman 55
Celent: The leading global insurance technology analyst firm
• Insurers
• Technology firms
• Strategic consultants
• Technology investors
• Research bridging
technology and business
• Technology consulting
• A division of
• A member of
A knowledge-based
intermediary working with
Organizational FamilyTwo Core Offerings

6. © 2016 Celent, a division of Oliver Wyman
Q: What are insurers’ 2016 priorities?
A: Data, analytics, digital, omni-channel

7. © 2016 Celent, a division of Oliver Wyman 77
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Digital Transformation
Innovation
Analytics
IT Operational Excellence
Core System Modernization
Completed in past three years Underway and continuing Will begin in 2016 In planning process Not under consideration
Property/Casualty insurers’ key 2016 initiatives
Source: Celent 2016 CIO Survey: large insurer segment

8. © 2016 Celent, a division of Oliver Wyman 88
Life/Health insurers’ key 2016 initiatives
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Core System Modernization
Digital Transformation
Innovation
Analytics
IT Operational Excellence
Completed in past three years Underway and continuing Will begin in 2016 In planning process Not under consideration
Source: Celent 2016 CIO Survey: large insurer segment

9. © 2016 Celent, a division of Oliver Wyman 99
Property/Casualty insurers’ plans for the application portfolio
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Call Center/Telephony
CRM
Stand-alone Rating Engine
Claims Admin System
Reinsurance system
Illustrations (Life)
Bus Process Mgmt
Document Creation
Document Repository
Business Intelligence
Predictive Analytics/Modeling
Investment Management System
Enterprise Risk Management System
Portals
Mobile for agents/customers
Stand-alone Underwriting Workbench
Policy Administration System
Billing System
Bus Rules Mgmt System
Financial and Administration Systems
Distribution Mgmt (Comm. Licensing)
Master Data Management
Begin replacement Replacement in progress Significant enhancements Maintain N.A./No activity
Source: Celent 2016 CIO Survey: large insurer segment

10. © 2016 Celent, a division of Oliver Wyman 1010
Life/Health insurers’ plans for the application portfolio
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Portals
Call Center/Telephony
CRM
Stand-alone Underwriting Workbench
Policy Administration System
Stand-alone Rating Engine
Billing System
Claims Admin System
Reinsurance system
Illustrations (Life)
Document Repository
Business Intelligence
Master Data Management
Predictive Analytics/Modeling
Investment Management System
Mobile for agents/customers
Bus Rules Mgmt System
Bus Process Mgmt
Document Creation
Financial and Administration Systems
Enterprise Risk Management System
Distribution Mgmt (Comm. Licensing)
Begin replacement Replacement in progress Significant enhancements Maintain N.A./No activity
Source: Celent 2016 CIO Survey: large insurer segment

11. © 2016 Celent, a division of Oliver Wyman
Q: Where is the big data coming from?
A: Everywhere

12. © 2016 Celent, a division of Oliver Wyman 1212
The Internet of Things is a Big Data generating machine
• It creates value through what connects three components
Report states
Internal states/external status
Iterate
Models/analyses
Feedback and control
Commands and requests
THINGS WITH
NETWORKED SENSORS
At rest Active
CLOUD STORAGE
Data Text
Models/analys es
Videos Images
ANALYTIC ENGINES
Human/machine
learning
Servers/cloud

13. © 2016 Celent, a division of Oliver Wyman 1313
Data source use case: Your car is watching you and itself

14. © 2016 Celent, a division of Oliver Wyman 1414
Data source use case: Telematics leverages car and driving data to create new
products and services

15. © 2016 Celent, a division of Oliver Wyman 1515
Data source use case: GE will be teaching industrial equipment to talk to the IoT
via the “Industrial Internet”
• Any insurer writing coverage of industrial properties needs to tap into these data,
analytics and findings
Source: http://www.gereports.com/post/76430585563/ new- industrial- int ernet-r eport-fr om- ge-f inds #

16. © 2016 Celent, a division of Oliver Wyman 1616
Data source use case: Industrial control systems are jumping on the bandwagon
Source: http://www.rockwellautom ation.com/global/innov ation/c onnected- ent erpris e/operat ionaliz ing. page?gclid= CNa6mv CA gc gCF RS DfgodjL8NmQ http://www.industry.siemens.c om/t opics/global/ en/ digit al- ent erpris e-
suite/Pages/Default. as px
https://www.bosch-si.c om/ products/bosc h- iot-s uit e/iot-use-c as es/internet-things-c as es. html

17. © 2016 Celent, a division of Oliver Wyman 1717
Data source use case: New sensors sensing new things about people and their
environment
Source: Qualcomm Life Fund, Qualcomm Ventures, Smartwear Symposium

18. © 2016 Celent, a division of Oliver Wyman 1818
Data source use case: John Hancock’s Vitality life insurance products links
biomonitoring and behavioral awards to lower premiums in the next policy year
• Can the IoT beat the actuarial tables?
Source:http://www.jhrewards lif e.com/

19. © 2016 Celent, a division of Oliver Wyman
What do you do with the big data?

20. © 2016 Celent, a division of Oliver Wyman 2020
11 things insurers have to figure out about the IoT
1. Who owns the data?
2. Who will aggregate it?
3. Where will it be stored?
4. What incentives will enable
insurers to access the best
data?
5. What are the root causes
of losses?
6. Which data correlates to
those root causes?
7. How to mix and match IoT
data vs. already available
data?
8. How to work with images,
sounds, other unstructured
data?
9. What are the relevant skill
sets, and how can insurers
access those skill sets?
10.Positive or negative
incentives or both?
11.Do insurers want to
exercise direct control over
things?
Data Feedback and ControlAnalytics

21. © 2016 Celent, a division of Oliver Wyman
What does it mean for insurers?

22. © 2016 Celent, a division of Oliver Wyman 2222
Impacting every part of the insurance value chain
• Types of
sensors
• Sensor output
• Type of network
• Feedback
control
effectiveness
Product Design
• New data
elements
• New pricing
algorithms
based on
models/analyse
s
Pricing
• New elements
in scores and
decisions:
based on prior
or current output
of sensors
• New kinds of
data and
information
(video or
images)
Underwriting
• Responsible for
feedback and
control operation
• Must work well
with people and
objects
• Must understand
how to impact
motivation and
behavior
Policyholder
Service
Claims
• Use new data
elements,
models,
analyses to
understand
causation and
responsibility
• Fraud mitigation
tools use
broader and
better data and
algorithms

23. © 2016 Celent, a division of Oliver Wyman 2323
Implications for insurers’ value propositions and business models
1 Move from periodic to continuous engagement
2 Move from indemnity to avoidance – changing the nature of the risk
3 New capabilities introduced into the model
4 Ecosystem expands and transforms

24. © 2016 Celent, a division of Oliver Wyman 2424
• Model Insurer Award
– Celent recognizes technology innovation through annual Model Insurer Award
• Insurers are Recognized Across Multiple Categories
– Legacy and ecosystem transformation, digital and omni-channel transformation, innovation and
emerging technologies, data mastery and analytics…
• Markerstudy was a winner of the 2015 Data Mastery and Analytics Model Insurer Award
– Recognizing their use of big data analytics and Hadoop to drive speed to market, growth and
innovation
The 2015 winner of Celent’s Model Insurer Data Mastery and Analytics
Award: Markerstudy

25. © 2016 Celent, a division of Oliver Wyman
Questions or comments?
Contact
Donald Light
dlight@celent.com
Thank you

26. Dan Fiehn
CIO
Nick Turner
Enterprise Data Architect

28. Up to the minute data

29. Streams of personal data

30. Enormous volumes
The population
of Barcelona,
every 2hours...
The population
of Spain,
every 2 days...
The population of
Europe, every month!
44,000,000
1,200,000
740,000,000

31. Objectives & Use Cases
• Operational Reporting & Monitoring
• Analytics & Exploration
• Point of Quote Enrichment
• Customer View
• Actionable Insight

32. Selection Criteria
• Enterprise Platfor m
• Support and Maintenance
• Professional Services
• People and Skills Development

33. Impact on Business
• Project completed in under 7 months
• Policy conversions increased by over 120%
• 50% fewer cancellations
• Reduced fraud by 5 million pounds

34. Tomorrow’s Headlines

35. SAY HELLO!!
Dan Fiehn:
https://uk.linkedin.com/in/danfiehn
Nick Turner:
https://uk.linkedin.com/in/enterprisedata

36. C o p y r i g h t © 20 1 4 , SA S I n st i tu t e I nc . Al l r ig h ts r e s er v e d.
Maneeza Malik: Head of Global Insurance Practice – Cloudera
Stuart Rose: Head of Global Insurance Practice - SAS

37. 37© Cloudera, Inc. All rights reserved.
Key Challenges for Insurers
Fragmented Systems
and Data Silos
Limited Access to
Right Data at the
Right Time
Strategic Decisions
Based on Subsets of
Data
Unable to Tap into
New Data Sources or
Correlate Data from
Multiple Sources
Simultaneously
Disparate View of
Customers, Markets
and Risks
Poor Data Quality
and Lack of
Governance

38. 38© Cloudera, Inc. All rights reserved.
2
Structured Data Unstructured Data
Core Insurance Systems
Point Solutions
(Rating, Fraud Engines…).
CRM
Enterprise Applications
Website/Log Data
Sensor/Telematics
Traffic/Geospatial/Weather
Mobile Apps/Location Data
Social Media/
3rd
Party Data
Adjuster Notes
OPERATIONS
DATA+
MANAGEMENT
BATCH REAL2TIME
PROCESS,+ANALYZE,+SERVE
UNIFIED+SERVICES
RESOURCE+MANAGEMENT SECURITY
FILESYSTEM RELATIONAL NoSQL
STORE
INTEGRATE
BATCH STREAM SQL SEARCH SDK
Centralized Access to All Your Data
For Any Amount, From Any Data Source, For All Types of Workloads
Business/IT

39. 39© Cloudera, Inc. All rights reserved.
SAS and Cloudera Integrated to Support Analytical Lifecycle

40. 40© Cloudera, Inc. All rights reserved.
Big Data Analytics - Claims

41. 41© Cloudera, Inc. All rights reserved.
Big Data Analytics - Underwriting

42. 42© Cloudera, Inc. All rights reserved.
Take Action Today
Visit us at
• www.sas.com
• www.cloudera.com
Download
• White Paper (SAS and Cloudera): Driving Growth in Insurance with a Big Data Architecture
Meet us at
• Strata + Hadoop World in San Jose, CA (March 29-31, 2016)

43. 43© Cloudera, Inc. All rights reserved.
Thank you