More Related Content Similar to Learn How to Prepare for Usage Based Insurance Roll-Out (20) Learn How to Prepare for Usage Based Insurance Roll-Out2. Agenda
Adoption patterns of telematics insurance
• Usage-based insurance will enable a competitive edge
Key steps in implementation of an economically viable usage-based
insurance product with mass consumer appeal
© 2009 EMB. All rights reserved. Slide 2
4. Personal Auto
Early pilots used professionally installed OEM or after-market
devices
Subsidized cost for learning
Inconvenient for consumers and low adoption rate
Opportunities as device costs decline
Multiple electronic makers offering devices
Reliable self-installed devices becoming available
© 2009 EMB. All rights reserved. Slide 4
5. Technology costs have dropped
Pricing accuracy
Customers love it
Politically accepted
Accident reduction potential
Retention dramatically increased
7. Monitored Driving Programs
Hollard – SA AIOI – Japan
Uniqua – Austria Real Insurance – Australia
WGV - Germany Aryeh - Israel
AXA – France, Ireland, Italy Aviva – Canada & Europe
Allianz – Italy Progressive – US
Lloyd Adriatic – Italy GMAC - US
Reale Mutua – Italy Safeco – US
Sara – Italy American Family – US
Polis Direct - Netherlands Milemeter – US
MAPFRE - Spain Travelers – US
Norwich Union – UK (discontinued) CSAA - US
Royal & Sun - UK Unigard – US (pending)
Coverbox – UK
© 2009 EMB. All rights reserved. Slide 7
8. Appeals to participating consumers
Once educated, UBI appeals to consumers
Makes sense
Controllable
Side benefits
As it is causal, reduces
reliance on risk proxies
Insurance credit scores
Driver assignment
Charges for relatively rare
accidents, convictions
© 2009 EMB. All rights reserved. Slide 8
10. Key Benefits of Telematics
Customer Insurer
Significant reduction in premium Improved ability to assess risk
for good risks Improvement in profitability:
Less cross-subsidy for poorer Improved Loss Ratio
drivers Increased persistency
Feedback and recommendations Better Customer segmentation
for improving driving and targeting
Empowerment – more control Self-selection by customers
over premium further compounds risk benefits
Social benefits Avoid adverse selection
Opportunity for ancillary benefits
You have to get the customer proposition right – sharing the benefits
Slide 10
11. Historical Perspective
Motor insurers have historically used risk proxy factors for assessing
and pricing risk
Risk Proxy Factors Genuine, Fundamental Risk Drivers
Age At what time of the day is the vehicle
Gender When? used?
Marital status
Garaging address
Where? What type of road is the car driven on?
Use (personal, business, etc) ?
Convictions
Credit How is the vehicle driven – how fast
How?
Vehicle type and how safely?
How How many miles does the vehicle
Much? travel?
To date, these approximations have been good enough but technological advancements
mean access to fundamental risk data is now achievable
Slide 11
12. Tremendous predictive power
Various studies demonstrate predictive potential
Companies gain competitive advantage through better segmentation
Elimination of cross-subsidization is more “fair”
© 2009 EMB. All rights reserved. Slide 12
13. How does UBI work?
Driver
Improve Driving
Feedback
Customer
Feedback Loop
Policy Period
Market Quote
Collect & Analyze
Driving Score
Improve Rating
Company
Feedback Loop
Underwriting
© 2008 EMB. All rights reserved. Slide 13
14. Improves driving and reduces accidents
UBI experience significantly better
Norwich Union: 30%
frequency reduction
GreenRoads: >50%
improvement in fleet crash rate
Iceland postal service reduced
crash rate by 56%
Pepsi (Iceland) reduced fleet
crash rates by over 80%
Early adopters will have increased profits and a competitive advantage
© 2009 EMB. All rights reserved. Slide 14
16. Risk Segmentation
Deriving risk factors from the data,
and applying loadings / discounts
to customers to enhance selection
Risk Influence
Customer feedback on behaviours
to avoid
Reducing Vehicle usage overall,
and especially higher risk miles
Claims Effectiveness
Informing the claims process
Use of telematic data as evidence
Self Selection
Reducing underwriting and claims
fraud
17. KEY STEPS
Do it right and make money!
© 2008 EMB. All rights reserved. Slide 17
18. Challenges
1. Building customer proposition
2. Technology
3. Collecting and storing data
4. Translating data into risk exposure
5. Integration with existing systems
6. Customer interactions
7. Business risks
© 2009 EMB. All rights reserved. Slide 18
19. Alternative Models
Dedicated Device
Insurance must pay for device and install
Need self install to appeal to mass market
– Reasonable cost
– Ease of use
Shared Services Device
Device is able to support added value services outside insurance for example
– Satellite Navigation
– Rerouting to avoid Traffic Congestion
– Theft Tracking
– Speed camera warnings
– Emergency Call etc.
Hard install may be required for these
© 2009 EMB. All rights reserved. Slide 19
20. Important Questions
What should device specifications include?
What devices include critical functionality?
What investment is the required and how to optimize
the return?
What data is pertinent?
Is the data accurate?
How much data is required?
How to transfer, store, and analyze all this data?
What do consumers want?
How to begin without loss cost models?
© 2009 EMB. All rights reserved. Slide 20
21. Device Installation
Are vehicles compatible with the device?
Self-installable:
Simple and convenient?
Documentation and customer support?
Verify installation?
Professionally installed:
Arrangements with installers?
Cost and time required?
© 2009 EMB. All rights reserved. Slide 21
22. Installation
OBD: Vehicle Event messages, VIN Number, Odometer reading, Speed
© 2009 EMB. All rights reserved. Slide 22
23. Data Sources
Internally recorded by device
Clock, Accelerometer
Obtained from vehicle diagnostics
VIN, Odometer, Speedometer, Engine operation
Obtained from external sources
GPS, Maps, Weather, Traffic
Developed from raw data
© 2009 EMB. All rights reserved. Slide 23
25. Data Transmission Costs and Alternatives
Data types
Record size
Frequency of transmission
Data Compression
© 2009 EMB. All rights reserved. Slide 25
26. Data Uses
Data needed for loss cost models
Data consumer wants
Data for additional services
© 2009 EMB. All rights reserved. Slide 26
28. Added Value Services
Safe Driver Coaching
In vehicle feedback
Web site reports
Emergency Call
Detect significant impacts
Send text alerts (“Where am I” message)
Real-time service to dispatch help
Theft Service
Detect motion without ignition
Tracking and call for help
Geo-fence Service
Detect location outside boundary zone
Trigger notification
Subscription services could help subsidize the costs
© 2009 EMB. All rights reserved. Slide 28
30. What does this mean?
Devices can track simple or very detailed driving behavior
Significantly increase pricing accuracy
Minimize reliance on detailed questions
and controversial proxy variables
Help customers understand and eliminate
risky behaviors
Differentiate product offering via
additional services
All this means increased profits and retention!
© 2008 EMB. All rights reserved. Slide 30
31. Contact Info
Robin Harbage, FCAS MAAA
C-Counsel Consultant
EMB America LLC
622 Falls Rd
Chagrin Falls, OH 44022
Robin.harbage@emb.com
(440) 725-6204
© 2008 EMB. All rights reserved. Slide 31