Insurance Telematics: Big Data, Big Potential, Big Headache

Dave Huber, President

Kairos Solutions

IFSUG March 2012

Big Data

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One of the few products whose price is set before costs are known

Known costs Unknown costs

3

O Loss adjustment expense

O Operations

O Advertising

O Underwriting

O Commissions

O Pure premium (freq x sev)

O Bodily injury

O Comp & Collision

O Regulatory

O Trends

Known costs

Unknown costs Premium

Data drives insurance decisions

Pricing sophistication is a competitive advantage and depends on data analytics

O Granularity O The number of pricing cells per question or variable

O Age: 16-19, 20-25, 26-30…vs. 16, 17, 18, 19….

O Dispersion O The range of rates for each of the variables

O $450-$900 vs. $225-$1375

O Interactions O The lift when combining variables

O Vehicle symbol & territory – pickups in suburbs

O Variables O New questions and/or external data

O Credit, occupation, prior limits

4

Insurers generally use the same data to price

5

Age

Gender

Marital status

Violations

Points

Homeowner

Prior insurance

Credit

Vehicle

31

M

S

Speed

4

Own

Y

611

YMM

31

M

S

Speed

4

Own

Y

611

YMM

These drivers look like Pure Premium Carbon Copies and are priced identically

$1000 $1000

But imagine knowing something about drivers that no one else knows

6

31

M

S

Speed

4

Own

Y

611

YMM

10,651

4.9

31

M

S

Speed

4

Own

Y

611

YMM

13,182

6.1

$800 $1200

Age

Gender

Marital status

Violations

Points

Homeowner

Prior insurance

Credit

Vehicle

Verified Annual Miles

Trips per day

So they’re NOT Pure Premium Carbon Copies after all…and they deserve a different price

Usage-Based Insurance is all about segmentation & pricing

O How, when & where you drive

O Driving data’s not readily available &

expensive to collect

O Need a lot of driving data

O Beyond insurers’ core competency

O Insurers would really like a driving score

7

8

The pricing advantage of UBI data is big

O Granularity O The number of pricing cells per question or variable

O Age: 16-19, 20-25, 26-30…vs. 16, 17, 18, 19….

O Self-reported mileage buckets vs. verified continuous mileage

O Variables O New questions and/or external data

O Credit, occupation, prior limits

O How, when & where, self-selection, personal driving score akin to a credit score

O Interactions O The lift when combining variables

O Vehicle symbol & territory – pickups in suburbs

O Miles x time of day, frequency & magnitude of speed changes, speed x traffic

O Dispersion O The range of rates for each of the variables

O $450-$900 vs. $225-$1375

O Personalized pricing

How big is Big Data?

O Time-stamped trip start/stop, engine on/off

O OBD - vehicle speed every second

O GPS - lat, long & heading every second

O Accelerometer – 3 axis acceleration

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O 5,000 GPS-enabled devices

O 8MM journeys & 15B journey points

O 20 million new rows of data daily

So what does when, where & how look like?

How might all this Big Data show up?

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Annual mileage

Avg trip duration

Avg trip length

Trips per day

Trips per time of day

Journeys

Miles by time of day

Miles by day of week

Weekdays

Weekends

Miles in speed bands

Time in speed bands

Average speed

Trip regularity (miles)

Trip regularity (time)

Aggressive acceleration per 100 miles

Aggressive braking per 100 miles

Road type

Relative speed

Miles in territory

Drive time in territory

Idle time in territory

Cornering

Lateral acceleration

Rolling stops

Self-selection

Lane changes

Acceleration events in speed bands

Braking events in speed bands

Frequency of speed changes

Magnitude of speed changes

Commuter profile

Errand-runner profile

Coffee drinkers

YMM relativities

OnStar subscription

Cruise control

Driver score

Driver “footprint”

Left turns

Speed variation

Trip type (speed vs time)

Territory by time of day

Holiday driving

School zone

Violations by trip type

Trip radius

Student profile

Intersections

Turn signal

Seat belt

Lights / wipers

Vehicle maintenance

Time between trips/journeys

Congestion index

Summer car

Texting & phone use

Big Potential

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12

Growth depends on acquisition & retention

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Driving data colors the opportunity

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But insurers without UBI are color blind

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UBI book attracts preferred drivers who are accurately priced…

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Insurers without UBI are left with a book that looks like this to them…

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But in reality behaves like this…

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