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© 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© 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
© 2016 Celent, a division of Oliver Wyman
Insurance Trends for 2016:
Data, Analytics, Cloud
January 2016
Donald Light
dlight@celent.com
© 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
© 2016 Celent, a division of Oliver Wyman
Q: What are insurers’ 2016 priorities?
A: Data, analytics, digital, omni-channel
© 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
© 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
© 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
© 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
© 2016 Celent, a division of Oliver Wyman
Q: Where is the big data coming from?
A: Everywhere
© 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
© 2016 Celent, a division of Oliver Wyman 1313
Data source use case: Your car is watching you and itself
© 2016 Celent, a division of Oliver Wyman 1414
Data source use case: Telematics leverages car and driving data to create new
products and services
© 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 #
© 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
© 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
© 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/
© 2016 Celent, a division of Oliver Wyman
What do you do with the big data?
© 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
© 2016 Celent, a division of Oliver Wyman
What does it mean for insurers?
© 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
© 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
© 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
© 2016 Celent, a division of Oliver Wyman
Questions or comments?
Contact
Donald Light
dlight@celent.com
Thank you
Dan Fiehn
CIO
Nick Turner
Enterprise Data Architect
Up to the minute data
Streams of personal data
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
Objectives & Use Cases
• Operational Reporting & Monitoring
• Analytics & Exploration
• Point of Quote Enrichment
• Customer View
• Actionable Insight
Selection Criteria
• Enterprise Platfor m
• Support and Maintenance
• Professional Services
• People and Skills Development
Impact on Business
• Project completed in under 7 months
• Policy conversions increased by over 120%
• 50% fewer cancellations
• Reduced fraud by 5 million pounds
Tomorrow’s Headlines
SAY HELLO!!
Dan Fiehn:
https://uk.linkedin.com/in/danfiehn
Nick Turner:
https://uk.linkedin.com/in/enterprisedata
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©	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©	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©	Cloudera,	Inc.	All	rights	reserved.
SAS	and	Cloudera	Integrated	to	Support	Analytical	Lifecycle
40©	Cloudera,	Inc.	All	rights	reserved.
Big	Data	Analytics	- Claims
41©	Cloudera,	Inc.	All	rights	reserved.
Big	Data	Analytics	- Underwriting
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©	Cloudera,	Inc.	All	rights	reserved.
Thank	you

Markerstudy Group Drives Growth and Innovation

  • 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.
  • 28.
    Up to theminute data
  • 29.
  • 30.
    Enormous volumes The population ofBarcelona, 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 & UseCases • Operational Reporting & Monitoring • Analytics & Exploration • Point of Quote Enrichment • Customer View • Actionable Insight
  • 32.
    Selection Criteria • EnterprisePlatfor 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.
  • 35.
    SAY HELLO!! Dan Fiehn: https://uk.linkedin.com/in/danfiehn NickTurner: https://uk.linkedin.com/in/enterprisedata
  • 36.
    C o py 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.
  • 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.
  • 40.
  • 41.
  • 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.