Usage-Based Insurance & Telematics · new sales within Motor are Telematics products By 2020 the...

Usage-Based Insurance & Telematics

Slutet på traditionell prissättning eller bara en fluga?

Aktuarieföreningen april 2016. Speakers: John Brandel & Martin Einemo, EY

Introduction & Market overview

Highly engaged customers have a 37% lower rate of accidents and their cost of claims are significantly lower (27%)

Reduce claims cost by 40%

Reduce policy administration by

50%

In Italy approximately 30% of

new sales within Motor are Telematics products

By 2020 the market penetration

is expected to be 15%

Share of telematics enabled policies in Europe and in the US

Telematics in numbers► Usage-Based Insurance is an insurance product with highly personalized premiums that are set after specific behavior

► Telematics is a type of vehicle insurance whereby the costs are dependent upon type of vehicle used, measured against time, distance, behavior and place

The traditional insurance market is moving towards a big change

1

18%

56%

15%2,5%7,5%

Totalpremiumincome

Profit Fraudulentclaims

Admincosts

Behavioralrelatedclaims

Non-behavioral

relatedclaims

Distribution of costs per premium income

► Technically an insurance is a transfer of risk from one entity to another in exchange for money

► Insurance companies earns revenue from two primary sources:

• Charging enough premium to cover for expected claims and administrative costs

• Earning investment returns► There are different types of insurance

How does insurance work?

12 March 2016

Key facts of traditional insurance

Pricing by segmentation

Nordic market: An oligopoly

New insurance mega trends

Issues with insufficient data

Combined ratiosf(x)


Agenda

1 Introduction

2 Big Data

3 UBI & Telematics

4 Impact on business

12 March 2016 Usage-Based Insurance & Telematics

Effective Big Data management

Access to new data sources is a game changer for pricing and business models

What does access to Big Data mean for the insurance company and its market position?

More material to form a competitive pricing model

Individualised pricing

By lowering claim sizes the insurer can stream line the organisation

Better forecasting of future claims


0

5

10

15

20

25

30

35

40

45

Data available in the world (Zettabytes*)

*1 ZB ≈ 1,126,000,000,000,000,000,000 bytes

Apple users download

51,000 apps

YouTube users upload

300 hours of new video

► Every minute…

The customers can benefit from sharing theirdata

What data do we generate?

… and how can the customer benefit from that?

Location

Physical status

Social media data

Transaction pattern

Other smartphone activities

By sharing personal data the customer can benefit from tailored services

Emergency services

Motivation for healthy and safe living

Form base for individual services

Fraud detection

Loyal customers get recognised


Agenda

1 Introduction

2 Big Data

3 UBI & Telematics



Telematics in cars can increase the claims prediction accuracy

Analysing different types of data:► Speeding► Excessive

acceleration and breaking

► Safe or unsafe road

► Safe or unsafe time of driving

Collection of huge amount of information:► Storage► Ownership► Integrity► Wash and filter

data► Size of data

Measure driving behaviour through:► Application for

smartphone► Built-in black box

in car

Better pricing for safe drivers:► Young drivers

that drive safe► Males that drives

safer than their peers

1. Measure 2. Data 3. Analyse 4. Product


Telematics has an opportunity to increase traffic safety

By capturing detailed data on driving behaviour insurers price more efficiently

Traditional insurance

Use the following as proxy of the true risk:

Car factors

► Age of the car

► Make and model of the car

► Value of the car

Driver factors

► Age of the driver

► Claims history

Other

► Socio demographic

► Geographic

True risk of the insured

Car

► Age of the car

► Make and model of the car

► Condition of the car

Driver

► Age of the driver

► Experience of the driver

Where the car is driven

► Traffic density

► Type of road

► Traffic enforcement (e.g. Speed cameras)

When the car is driven

► Day or night

► Weather conditions

► Seasonal use only

How the car is driven (DBD)

► General adherence to laws & regulation

► Length of journeys

► Acceleration, deceleration and speed of car on different road types / traffic density

Telematics Data


Time for a question!

Telematics

Consider the the following scenario:

Based on a scoring model, drivers get between -20%

and +20% on their standard motor tariff price“ ”What is the most likely effect of this approach?

All customers will get a more accurate price1The good drivers get a more accurate price2Bad drivers get negative behavior punished twice3

In order to build the price model accurately, one need to consider the full tariff

Let part of the premium be based on a traditional tariff and part be based on

driver score

Telematics

Exempel:

En 25-åring har för en BMW 320 ett tariffpris på 25 000 kr/år, genomsnittligt tariffpris är 8000 kr/år.

Personen har en driving score på 55. Genomsnittlig driving score är 70.

Vilken driving score förväntas utifrån ett tariffpris på 25 000 kr/år?

There are different ways of setting up a tariff including Telematics

1

Using driver score as a separate argument in the GLM2

Using a normed driver score as a factor giving a discount or penalty3

There are three main sources for premium pricing with telematics

► Using studies, public data and trials one can obtain a very accurate risk model even with small collected datasets

► Most common parameters to use for risk diversification under UBI are exposure, speeding and acceleration profile

► Some insurance companies apply a pay-per-mile insurance premium

In our experience, the difference in predicted accident frequency is very large between drivers

Exposure Speeding Acceleration profile

Weekday, time of day and season are important indicators of exposure risk

Around 20-30x difference in accident probability between the best and worst time to drive, however aggregated results are showing smaller differences

Speeding and type of road are the most used factors among insurers

Here we can observe a 4-10x difference in accident frequency between the safest and the most unsafe driver

Usually, a filtered acceleration signal is used to obtain indicators of unsafe driving

Among drivers, this factor stands for around 4-12x difference in accident frequency between the safest and the most unsafe driver


Agenda

1 Introduction

2 Big Data

3 UBI & Telematics



In our point of view, the business case for telematics is complex and contains several components that are of importance for success

Pricing Strategy…

Using more data, and more data that is directly relevant to the individual customer can help to bring pricing to the next level

1Customer Experience

Providing services such as streamlined claims handling, advice to improve driving and reduce premiums can improve the customer experience

2Expense Reduction

Improving claims underwriting can help to reduce costs, and through better understanding of customers marketing can be targeted more effectively

3Revenue Enhancement

Value adding services coupled with increased market share and cross selling can increase revenue

Risk Management

Improved understanding of customer behaviour can be used for a more refined portfolio risk analysis, and can also help to identify fraud incidents

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The business case for telematics contains several components

Telematics is an opportunity to improve not just pricing, but all parts of the insurance business


Reward customer for driving well, improving his/her driving knowledge and awareness and making sure the car is safe to drive.

► To maximise rewards one needs to earn as many DQ Points as possible and aim for an Advanced Vitalitydrive status

► Good drivers experience a 37% lower rate of accidents and their cost of claims are significantly lower (23% lower)

Example of motor UBI programs worldwide

Carrot Insurance (UK)

Young driver program using a black box installation.

► Quarterly appraisal of “Driving Style score” used to calculate cash rewards, loaded onto a pre paid MasterCard

Recently introduced a mass market telematics program that is app based.

► Weekly rewards are given for good driving

Moderna (Sweden)

Discovery (South Africa)

Mobile app on a pay-how-you-drive approach:

► Gives up to 15% discount

► Need to drive 500 km while the appregisters your driving behaviour

► Uses speed and accelerationmonitoring

In Sweden, the large players are expected to introduce UBI programs shortly after the release by Moderna and the release in May 2016 by Folksam


How can an insurance company increase profits with decreased premium income?

Company X earn 100 MEUR in premiums

Scenario:

► 30% of their customers engage in the telematics offering

► These customers lower their premium in average with 12.5%

12 March 2016

Company X


If you were the CEO of this insurance company, what would you do?“ ”

Do nothing. Claims cost will decrease so the result will be better anyway

Increase the total premium with 3.75 MEUR for all customers prior to the offering

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3

Increase the premium for customers who decide not to engage in the telematics offering

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How will big data, data analytics and telematics affect FS-business?


There are many stakeholders that have an opportunity to be market leading

► How can insurance companies increase their profits with telematics?

► Why are telcos applying for

banking licences and setting up

telematics solutions?

Insurance

Telecom

► Why are big retail companies expanding outside of their core areas i.e. banking, insurance and pharmacies?

► How can car producers use

their position as being the

suppliers of the user data?

Retail

Car producers

Time for a question!

Telematics

What do you think about Telematics on the Swedish market:

How many of the medium and large insurers will offer Telematics

products within 5 years?“ ”> 75%150% to 75%2

25% to 50%3< 25%4

The better the question. The better the answer.The better the world works.

Thank you!

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