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Technology & Analytics for Usage-Based Auto Insurance Technology & Analytics for Usage-Based Auto Insurance

Technology & Analytics for Usage-Based Auto Insurance - PowerPoint Presentation

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Uploaded On 2017-05-18

Technology & Analytics for Usage-Based Auto Insurance - PPT Presentation

M ileage Discount Analytics Daniel HernándezStumpfhauser PhD Lead Statistician True Mileage Inc Ryan N Morrison CEO True Mileage Inc ID: 549614

discount mileage age rating mileage discount rating age vehicle analytics driver variables true vehicles 000 discounts double older drivers

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Slide1

Technology & Analytics for Usage-Based Auto Insurance

M

ileage Discount Analytics

Daniel Hernández-Stumpfhauser PhDLead Statistician | True Mileage, Inc.

Ryan N. Morrison

CEO | True Mileage, Inc.

Slide2

2

Mileage Up

To Discount

2,50054%

5,000

39%

7,500

34%10,00026%12,50018%15,00013% 15,000 +7%

Typical on-going verified mileage discounts today:

Mileage Discount Analytics

TM

Discounts apply regardless of other rating variables.Slide3

Rating variables with the strongest mileage relationship?

- Driver Age - Driver Gender

- Urban vs. Rural - Drivers/Vehicles - Vehicle Type - Vehicle Age3

Mileage Discount Analytics TMSlide4

Rating variables with the

strongest mileage relationship

? - Driver Age - Driver Gender - Urban vs. Rural - Drivers/Vehicles - Vehicle Type - Vehicle Age

4

Mileage Discount Analytics

TMSlide5

5

S

hould a 10,000 mile vehicle get a discount?

Mileage Discount Analytics

TMSlide6

6

Not always! It would

be a double discount

for older drivers and vehicles.

Should a 10,000 mile vehicle get a discount?

Mileage Discount Analytics

TMSlide7

7

How do we resolve the

double discounting issue?Rating Mileage: The mileage a vehicle is effectively being charged for in an existing rating plan. Vehicles should only get a discount if they are below their rating mileage.

Rating Mileage function of vehicle age, driver age, and state.

Mileage Discount Analytics

TMSlide8

Rating Mileage Model

1)

Data: Unbiased national data set with hundreds of thousands of mileage observations.

2) Variables:

The most predictive rating variables are driver age and vehicle age.

3)

Goal: Estimate rating mileage, the mileage a vehicle is effectively charged for through a typical rating plan.8Slide9

Driver Age

Vehicle Age

Rating Mileage Model

Results: 2D

9Slide10

10

To

reduce double discounts risk use:

Example 1:

(

new car and mid-age driver

)

Example 2:(older car or older driver) Mileage Discount Analytics TMSlide11

Driver Age

Vehicle Age

11

Rating Mileage Table

State

adjustments to the national rating mileage table also recommended and available.

Mileage Discount Analytics

TMSlide12

Mileage Discount Analytics

TM

12Ryan N. MorrisonCEO | True Mileage, Inc.

Visit True Mileage at Booth #1

Insurance Telematics USA, Chicago, Sept 3-4, 2014

Daniel Hernández-Stumpfhauser PhD

Lead Statistician | True Mileage, Inc.