A discussion on how insurance companies could use telematics data, social media and open data sources to analyse and better price policies for their customers

1. Data Driven Insurance Underwriting
David M Walker
Data Management & Warehousing
http://datamgmt.com
26 November 2013

2. What happens when you add a little
black box to a car?
• This small box can be fitted
to a car in about an hour
• A basic model collects the
following info:
– Longitude, Latitude &
Altitude
– X, Y & Z Acceleration
– Speed
– Direction of travel
– Distance travelled since last
report
– Box Identifier
– Date & Time
26 November 2013
http://datamgmt.com
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3. On device collection of data in a Round
Robin Database
• A Round Robin Database or Circular Buffer
records the data regularly (e.g. milliseconds)
• After a time interval or a distance travelled an
aggregate report is sent to the server (Usage
Reports)
– Usage reports can be separately buffered if there is
no data transmission signal
• If a crash occurs the entire content of the buffer
is sent to the server (Crash Reports)
26 November 2013
http://datamgmt.com
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4. Sending Data Home
1.
Black
Box
sends
data
to
central
colla1ng
server(s)
over
mobile
data
networks
2.
Colla1ng
server(s)
send
data
files
to
MMP
Analy1cal
Server
Geo
Info
Under-­‐
wri1ng
Claims
ERP
CRM
26 November 2013
3.
Supplement
the
data
with
informa1on
from
the
opera1onal
systems
and
external
data
sources
http://datamgmt.com
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5. Usage Reports
• In town driving typically generates more
time limited reports
– Short distances driven in slow traffic
– Typically every 15 seconds
• Motorway driving typically generates
more distance limited reports
– Long Distances driven at high speed
– Typically every 1 km
• Trips are defined as ignition start to
ignition stop
• Usage reports describe the driving
behaviour
26 November 2013
http://datamgmt.com
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6. Crash Reports
• How was the driver driving
immediately prior to the crash?
• Where did the impact come from?
– X, Y & Z Acceleration determine point of impact
• negative acceleration on the front – you hit them
• positive acceleration on the back – they hit you
• Crash reports are used to help determine
fault
26 November 2013
http://datamgmt.com
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7. Basic Data Model
Social
Media
Policy
Holders
Drivers
Policies
Policy
Holder
Underwri1ng
Data
Driver
Underwri1ng
Data
Vehicles
Geographic
Layer
Informa1on
Claims
Data
Points
Crashes
26 November 2013
Trips
http://datamgmt.com
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8. Data Volumes
• 88 – 290 Bytes Per Data Point
– Depends on the type of Black Box
• 124 Data Points per Trip on average
• 81 Trips per Month per Vehicle
• Retained over 5 years
– ~ 165 Mb per customer
– ~ 1 Tb per 7000 customers
– ~ 15 Tb for 100,000 customers
• All the rest is insignificant
– Policies, claims, reference data, etc. becomes
insignificant in comparison to trip data
26 November 2013
http://datamgmt.com
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9. Data Collected At Quote Time
• Vehicle
– Make, Model, Engine Size, Alarm,
Modifications, #Seats, Where
kept (Day & Night), Use (Social,
Domestic, Commuting, etc.),
Annual Mileage
• Policy Holder & Other Drivers
– Address, Age, Gender§,
Marital Status, #Children, Other Vehicles,
Employment Status, Occupation, Industry,
Residency, Previous Claims & Convictions, Licence
Type & Additional Qualifications, Medical Conditions
§Gender
prohibited
as
ra1ng
factor
by
European
Court
of
Jus1ce
aTer
21st
December
2012
26 November 2013
http://datamgmt.com
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10. Data Collected At Claim Time
•
•
•
•
•
•
•
•
•
•
•
Type of Incident
Location of Incident
Weather
Other Parties Involved
Types of Vehicles Involved
Injuries
Damage to vehicles
Damage to third parties and property
Police Involvement
Description of the incident
Photographs and Sketches
26 November 2013
http://datamgmt.com
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11. Data Collected about Geography
• Commercial & Government Sources
– Road Name, Road Type, Speed Restrictions
– Average Speed by Road, by Day, by Day of
Week and by Time of Day
– Points of Interest
• Supermarkets, Petrol Stations, Car Parks,
Theme Parks, Sports Stadiums, etc.
– Meteorological Information
• Rainfall, Temperature, Sunrise/Sunset Times
• Open Sources
– Wikipedia
– Google/Bing/Apple Maps
26 November 2013
http://datamgmt.com
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12. Data Collected from Social Media
• Customer ‘Likes’ the insurance company on
Facebook
– “Wow - just got a great
deal on my car insurance”
• Customer chats to their friends
– “Just had a bump in my car, going to try and get
them for whiplash too!”
• Yes – people really are
that stupid!
26 November 2013
http://datamgmt.com
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13. Advanced Data Collection
• More sensors in the little black box
• Vehicle Interface Modules (VIMs)
– Provide an interface between a vehicle's on-board
diagnostics link (e.g. OBD II) and the black box
– Depending on the vehicle this provides access to
data such as oil/water/tyre pressures, time since
last service, car dashboard warning
lights that are on, ABS usage,
airbag deployment, was the
Bluetooth active, lights on/off,
windscreen wipers on/off etc.
26 November 2013
http://datamgmt.com
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14. A Note On Data Privacy
• Data Protection & Privacy Laws
– These vary by country so just how
much you can use of what you could
collect will also vary
• You can’t use all the data anyway
– European Court of Justice banned
insurance companies from using
gender as a rating factor after 21st
December 2012
• Opt-in/Opt-out data usages
– It is also possible, with permission, to
resell individual and aggregate
information to third parties
26 November 2013
http://datamgmt.com
14

15. Creating an Insurance Offering
• Offerings are typically designed a lot like
‘Pay As You Go’ Mobile contracts
– Fixed element – covers the device cost,
administrative aspects, etc.
– Usage (Risk) element – price per km driven,
with different rates for different levels of
service
• e.g. driving in the rush hour or the dark carries a
higher price than driving off-peak in daylight
– Usage bundles – First 500 km included
per month
• Requires top-up once they are all used up
otherwise you are not insured to drive
– normally auto debited from a credit card
26 November 2013
http://datamgmt.com
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16. Unexpected Consequences
• Driver behaviour is modified but this may not
deliver the expected results
hVp://www.dailymail.co.uk/news/ar1cle-­‐2359150/Teenage-­‐driver-­‐passenger-­‐died-­‐broke-­‐limit-­‐beat-­‐11pm-­‐insurance-­‐curfew.html
26 November 2013
http://datamgmt.com
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17. New Business & Renewal Quotations
• Year 1 Underwriting
– New policy prices based on traditional (nontelematics) underwriting scores
– No renewals
• Year 2+ Underwriting
– New policy prices based on data about existing
customers and vehicles with similar profiles
– Renewals based on the individual risk profile
26 November 2013
http://datamgmt.com
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18. (Dis)-Incentivising
• Carrots
– Bonus miles for driving within speed limits, in
daylight, off-peak, good weather, parking offroad, etc.
• Sticks
– Increased cost per km for persistent
speeding, regular hard braking (detected from
accelerometer), etc.
– Note: Penalising customers too hard will force
them to move away and have a reputational
impact
26 November 2013
http://datamgmt.com
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19. So what does the data show?
•
•
•
•
•
•
•
Driving Behaviours
Policy Compliance
Claim Assessment
First Responder
Theft & Fraud
Risk Profiling
Customer Behaviours
26 November 2013
http://datamgmt.com
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20. Driving Behaviours
• Does a person driving follow speed limits?
– Average speed as a percentage of the speed
limit by roadtype, user and between dates
• Does the person regularly brake hard?
– # of negative X-Accerations by 1000 miles driven
by roadtype, user and between dates
• Does the person drive unduly long hours?
– Number of trips longer than X hours
– Number of minutes break between trips
26 November 2013
http://datamgmt.com
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21. Policy Compliance
• Total number of miles driven
• Is a vehicle registered for Social, Domestic &
Pleasure being used for commuting or business
– Regularly driving between A and B in the morning
and between B and A in the evening
• Location where the car is parked over night
– Usually at a point near the policy holders address or
somewhere completely different
• Taxi & Delivery Drivers
– Don’t buy a commercial policy but can be spotted by
their driving patters
26 November 2013
http://datamgmt.com
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22. Claim Assessment
• When a claim is made the details can be
verified
– Location of accident – even have a look at it on
Google Maps
– Point of collision and who hit whom
– Weather, Amount of Light
– Speed and G Forces at time of impact
– Did the vehicle roll?
26 November 2013
http://datamgmt.com
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23. First Responder
• When an accident occurs:
– If it is severe enough try and contact the
customer
– Contact emergency services if required
– Arrange for your preferred recovery/repairers to
deal with the incident reducing the claim costs
– Perception bonus – My insurance company
really cares for me!
26 November 2013
http://datamgmt.com
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24. Theft & Fraud
• Theft
– Device is always tracking so if a vehicle is
reported stolen it can traced and recovery action
• Fraud
– Fraud rings may fake traffic accidents or stage
collisions to make false insurance or
exaggerated claims
– Many of the details can now be validated
(location, weather, speed, collision, etc.)
26 November 2013
http://datamgmt.com
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25. Risk Profiling
• What combination of attributes for both a
driver and a vehicle have the lowest total
claim value per 100,000 miles driven?
• Are a larger number of small claims more
expensive than a smaller number of large
claims?
• Statistical Cluster Analysis techniques to
determine high and low risk proposals
26 November 2013
http://datamgmt.com
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26. Customer Behaviour
• Football Supporter
– Regularly goes to home ground
– Do they go to away matches too?
• Business Traveller
– Regularly leaves car at airport parking
• School Run
– To and from home to local school twice a day
• Change of job
– Changes location of daily commute parking
• This information can (with permission) be sold to third parties
– Marketing companies, Football clubs, etc.
– These techniques are already being used by some mobile
companies
26 November 2013
http://datamgmt.com
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27. Security Services
• Fact Of Life
• Courts will order access to data if someone
is under suspicion
– Anti-Terrorism, Organised Crime, etc.
• Data will be used after an event to track
– Where did they travel from
– Who did they visit before the act
– etc.
26 November 2013
http://datamgmt.com
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28. The Future
• Pay As You Go Road Usage Pricing
– Governments requiring cars to be fitted with
telematics and road usage data sent to them
• Reduced Premiums & Higher Profits
– If all cars have telematics then low risk
customers will not be used to subsidise high risk
customers – some of this benefit is passed on to
the consumer by way of lower premium and
some is retained by the insurance company
26 November 2013
http://datamgmt.com
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29. An Observation
• Some of the evidence from telematics is
either counter-intuitive or goes against what
the underwriters ‘know’ is right
• Getting business users to use the data and
adjust the way they rate risk is difficult
• If you make changes to how risk is rated you
have to track the effect of the changes
26 November 2013
http://datamgmt.com
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30. Who’s doing this in the UK ?
26 November 2013
http://datamgmt.com
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31. Have a play …
• InstaMapper GPS Tracker
– http://www.insta-mapper.com
– iPhone & Android App
– Gives GPS but not accelerometer data
• Other applications are available but this is
the one I used for the Proof of Concept work
26 November 2013
http://datamgmt.com
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32. David M Walker
Data Management & Warehousing
THANK YOU
26 November 2013
http://datamgmt.com
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33. Contact Us
• Data Management & Warehousing
– Website: http://www.datamgmt.com
– Telephone: +44 (0) 118 321 5930
• David Walker
– E-Mail: davidw@datamgmt.com
– Telephone: +44 (0) 7990 594 372
– Skype: datamgmt
– White Papers: http://scribd.com/davidmwalker
26 November 2013
http://datamgmt.com
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34. About Us
Data Management & Warehousing is a UK based consultancy that
has been delivering successful business intelligence and data
warehousing solutions since 1995.
Our consultants have worked with major corporations around the
world including the US, Europe, Africa and the Middle East.
We have worked in many industry sectors such as telcos,
manufacturing, retail, financial and transport. We provide
governance and project management as well as expertise in the
leading technologies.
In The Netherlands Data Management & Warehousing works in
partnership with DeltIQ Group.
26 November 2013
http://datamgmt.com
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35. Data Driven Insurance Underwriting
David M Walker
Data Management & Warehousing
http://datamgmt.com
THANK YOU