Historically, insurers used 50-, 100-, and 500-year flood models for risk evaluation and pricing. The extreme weather events we have experienced in 2017 alone prove how dated these methods really are. To better understand their customers and potential current/future liability claims, forward thinking insurers are monitoring, analyzing, and integrating external data sources in real time (weather feeds from USGS.gov, news and stock feeds, and satellite imagery, to name just a few). By integrating and injecting these new data sources into their risk models and underwriting, insurers are better able to identify their risk appetites and effectively price. The session will include real-world case studies, including how a global P&C insurer is now quickly analyzing and monitoring 50,000 customers and targets, gaining new insights into the market. Another example is a global reinsurance and specialty company that now leverages digital news channels to monitor its risk portfolio for early warning claims indicators to help drive down loss costs. Speaker Cindy Maike, VP Industry Solutions, GM of Insurance, Hortonworks

1. 1 © Hortonworks Inc. 2011 – 2018. All Rights ReservedPage1 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Risk Listening: monitoring for profitable growth

2. 2 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Emerging Tech, Real-time data and the Connected World
Smart Cities
and
Buildings
Smart
Factories /
Commercial
Connected
Life / Health
/ Medicine
IoT /
Robotics
Telematics
Shared
Economy
Smart Homes
Cyber / AI /
Analytics

3. 3 © Hortonworks Inc. 2011–2018. All rights reserved.
Hortonworks confidential and proprietary information
Individual and business
customers are increasingly
residing in cities
The world’s population continues to
migrate to cities, passing 50%
urbanization and projected to exceed
70% urbanization by 2050
The entities underwriting
risk, and the liability in an
automated, smart world,
may change significantly
Smart city projects and
technologies introduce new
risks. For example, cyber-risk
and many different liability
exposures are much higher for
smart cities
Smart technologies have the
potential to dramatically
reduce risks for vehicles and
property and improve
people’s health and well-
being
The evolution of smart cities is
changing the risks of both individual
and business customers
The Connected World Is Reshaping the Nature of Insurance Risks
Connected vehicles estimated to
generate 300 TB of data per year,
or 25GB per hour!

4. 4 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Insurance Industry Data Sources in the Connected Digital World
Catastrophic
Event Data
Customer
Onboarding Data
Seismic
Data
Biometrics
Data
Usage-Based
Driver Data
Cyber Threat
Metadata
Drones &
Aerial Imagery
Claims Docs,
Notes & Diaries
Weather &
Environment
News Feeds
Policy
Histories
Photos
Telematics
Connected
Devices/IoT/
Sensors
Chat Bots
Call
Transcripts
RISK & UNDERWRITING
ANALYSIS
USAGE-BASED
INSURANCE
CLAIMS
ANALYTICS
NEW PRODUCT
DEVELOPMENT
CYBER RISK
ANALYTICS
CRM

5. 5 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Understanding the Impact to Insurance Data and
How to Leverage for Business Value

6. 6 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Insurers Planning for Connected
World Data (company illustration)
BatchReal-time
Datavelocity
Dimensional/Structured Behavioral/Unstructured
Data variety
Semi-structured
Climate / air quality / weather events
Drone image feeds
Social media / Sentiment
Sensors/ Wearables (IoT)
Geo-location
Deposition recording
Notes and diary
Medical bills
Transcriptions
Photos
Investigation
TPA invoices
FNOL intake
Claims triage
Vendor invoices
Forms and
letters
Claim payments
Policy verification
Applications / Submissions
3rd party risk models
Prior loss runs
Customer Profiles
Currently using for analytics
Currently available, but unable to use for analytics
Plan to use in next 12 months
Plan to use in next 24 months
1
3
1
3
1
1
1
1
3
1
1
1
Historical Weather-events1
Population data1
Call center Chat bots3

7. 7 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Enhanced Risk Models – Geospatial Opportunities
 Product Development &
Prospecting
– Underpenetrated Regions
 Catastrophic event models
– Model comparison
– Supplement with near/real-time data
 Understanding Risk at Location
Level vs Acct Level
– Sharing of data across LOBs
– Risk Aggregation vs.
Account/Customer Aggregation
Location Sharing vs. Account View Events vs. Policy

8. 8 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Immediate Access to post-storm for timely and
accurate event analysis
 Within hours of an event, stream storm
event information (hail swath)
– date, time and details of hail size data using
open data sources such as USGS.gov or other
weather sources
– streaming data delivered via Hortonworks
Data Flow
 Overlay and compare data with policy
information (structure information, building
footprints stored in HDP) with geocoded
location and events
 Evaluate the impact on the policy book of
business:
– to simulate impact to the business
– for reporting individual and aggregate
information to the business
– for comparison to incoming FNOL and claim
investigation assisting with resource
deployment and potential fraud (hard and
soft fraud)
* Queries are executed directly in HDP (Apache Hive tables) for fast and full portfolio analysis

9. 9 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Traditional “PAYD” “PHYD”/”MHYD”*
Shift from Usage-Based Auto Insurance Programs to Behavioral Rating
Risk
Proxies
Utilization
Simple
Behaviors
Using
Event
Counters
• Estimated Mileage
• Garage location
• Prior claim history
• Maneuvers
• Anticipation
• Aggression
• Adaptability
• Acceleration
• Braking
• Cornering
• Excess speed
• Approximate location (GPS)• Number of trips
• Time of day
• Mileage
Method Adoption
• Vary by geography and locations due to data
availability, cost and regulations
• Companies have struggled with data storage and
analysis due to volume, variety and velocity
• Programs are evolving as technology changes
Data / Analytics Impacts
• Changes in data storage and analysis due to
volume, variety and velocity
• Need to provide additional “context” to the
driving data such as location, weather, road
conditions, accident data
* MHYD = Manage How You Drive

10. 10 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
New Opportunities for Personal Auto & Fleet Insurers
UBI with Connected Car & Infotainment Systems
Enhance Customer
Relationships
Enhance Customer
Relationships
 Leverage new data sources such as
Data.gov
 Historical accident prone roadways
& streets
 Dept of Transportation + driver
behavior
 Recommend alternate “safer routes”
 Driver behavior analysis
Vehicle Concierge
Service replaces
“roadside assist
offering”
Data Drives
the Connected
Vehicle
Enhance
Customer
Relationship
Vehicle Concierge
Service replaces
“roadside assist
offering” Loss Expense
Optimization
 Maintenance reminder
 Roadside assistance
 Parking management
 Travel discounts
 Service discounts
 Stolen Vehicle Location
Assistance
Enhance Claim settlement/subrogation
 Product Liability: Vehicle
manufacturer at fault (e.g. faulty
airbag)
 Speed claims settlement process
 Accident investigation (camera,
distance of vehicle)

11. 11 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Evaluating and Inspecting Property Risk & Damage
Risk Inspection
– Roofs
– Buildings
– Survey of construction “site safety”
Claims / Catastrophe Inspections
– Hurricanes -- Residential and Commercial Property
inspection
– Hail inspection
– Floods
– Fires
– Crop Insurance monitoring (verification)

12. 12 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Industry Examples

13. 13 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Real-time analysis and risk monitoring/listening
Insurer wanted on-going views into its bio-med industry customers for
current/future potential liability claims
External data sources were monitored in real-time (news feeds,
content from the customer’s website, stock/financial analysts
commentary) for 50 of top customers for potential liability claims.
• Expanded to 1K customers by end of 2016 as underwriters, product
managers and the claims organization found it very useful for
individual risks.
• Product management and actuarial also are using data to better
understand the risk correlations for the bio-med industry.
• In 2017, expanding and collecting data on 50K customers/target
market.
Outcomes
Approach
Business Challenge
1 2 3
Global P&C: Personal and Commercial
CAPABILITIES: Blending of a new predictive model
with risk monitoring for high-risk attributes.
Expanded insights to a customer market segment

14. 14 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Telematics analytics (machine learning) to understand context of
driving conditions
A ”still” view
taken from the
car’s dashcam.
Through machine
learning
understanding
the context of
the location
attributes
(orange vs. grey
fields)
Conditions of the
road surface, where
extreme values show
the presence of speed
bumps (as seen in the
picture).
Shows driver
behavior/speed
in this situation
Shows geo-
location
Street view to
compare with
the dashcam
view.
Powered by
SynerScopeusing HDP
and HDF

15. 15 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Public Accident Information (personal lines insurer)
Public Accident Data: Real-time camera-view, accidents by highway
Accident data per highway, live camera-cam highway viewCorrelation of all accident data, vehicle type, weight of vehicle,
brand of vehicle

16. 16 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
USING IMAGES TO BETTER GUIDE YOUR ACTIONS
(C) 2017 SynerScope

17. 17 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Satellite
• Situation post-event
GPS Location
• Drone path (green)
• Water Level Monitors (black)
• Water Level Crowd Reporting (orange)
Aerial Pictures
• Drones. Helicopters, Planes
Satellite
• Situation pre-event
Water Levels
• Showing surge patterns
AI Clustering
• Detecting similarity of events in unstructured
(C) 2017 SynerScope
MANY DATA
LAYERS FUSED
WITH AI
and
ADVANCED
VISUALIZATION
TECHNOLOGY

18. 18 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Risk Monitoring (listening) Use Cases
Fire Event Monitoring
Predictive
Analytics
• A fully automated monitoring of 7,000
digital news channels with a daily volume
of 250 gigabytes allows fire losses in the
United Kingdom and the USA to be
recorded more quickly and cheaply.
• Comparing this data with the risks in
portfolios allows for better identification
of risk patterns, so that claims
management can be faster and more
effective.
Global
Reinsurer
Needs based
coverage
• Micro-insurance policies for
agriculture provided in South
Africa that utilize real-time
weather data and mobile money
transfer to create affordable and
accurately priced micro-
insurance policies for farmers.
Real-time/Streaming
“Brand
Watch”
• Insurer is conducting “brand watch” of its insurance customers who are in the
biomedical industry.
• External data sources are monitored in real-time (news feeds, content from the
customer’s website, stock/financial analysts commentary) of its customers for
potential liability claims.
• Initially launched with a pilot started with collecting data for 50 customers and
expanded to 1K customers by end of 2016 as underwriters, product managers
and the claims organization found it very useful for individual risks.
• Product management and actuarial also are using data to better understand the
risk correlations for the bio-med industry.
• In 2017, will be expanding and collecting data on 50K customers/target
market.
• Leverages HDF and SparkGraphX.
Global Specialty
Carrier
Real-time analysis and risk monitoring
International
Specialty Carrier

19. 19 © Hortonworks Inc. 2011 – 2017. All Rights Reserved
Steps to Prepare

20. 20 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
Preparing for the Connected World & Risk Listening
 Track Emerging Tech: All insurers should actively follow those
emerging technologies that will have the highest impact on their
business, such as autonomous vehicles, AI, drones, the IoT,
blockchain, and many others.
 Follow Smart City Projects: Be aware of the projects that are
underway, especially those in nearby cities or cities where you
have a large customer base.
 Engage in Initiatives: Where appropriate, join consortiums or
partner with local governments to promote smart city projects,
especially those aimed at reducing risks and improving public
safety.
 Build Big Data and Analytics Capabilities: In any future scenario
for insurers, having the platforms and expertise to manage,
analyze, and act upon large streams of real-time data will be
essential.
 Design New Products: Leverage innovation to develop new
products and coverages that address new or increased risks
created by smart cities, or provide insurance in new areas or to
new customer segments.

21. 21 © Hortonworks Inc. 2011 – 2018. All Rights Reserved
THANK YOU!
cmaike@hortonworks.com
@cmaike76
mhesseling@usa.net
@monhess