insurance day 2015 - presentation · (as of january 2015) up to 180k new customers in a month 141...

Inf ormation presented in this document is highly confidential and cannot be disclosed to any party without Octo’s prior written consent

Octo Telematics and SAS: a global partnership to

build new solutions of Usage-Based Insurance

through Advanced Analytics

Insurance Day 2015

Athens, 13th March 2015


OCTO & SAS - THE AGREEMENT

• The scope of the agreement is designed to exploit state-of-the-art

technology and joint R&D to create new analytics algorithms and services

• With a shared and common go-to-market strategy to selected insurance

companies

• Insurers will gain better consumer insight, improve CRM, generate more

accurate pricing and have a more predictable risk base.

• Consumers will get individualized pricing, improved safety and better

customer journey

2


As at 30.09.2013

Octo is the global leader in providing insurance telematics services as well as pioneering applicationsin motor rental and fleet management, car manufacturing and governmental sectors. Founded on 2002Octo is the largest Insurance Telematics provider in Europe and fast growing at the average rate of 5.000new installationsper day.

OCTO AT A GLANCE…

12 years of flawless execution in the

Insurance Industry

Over 3.2 million active vehicles

(as of January 2015)

Up to 180K new customers in a month

141 Worldwide Insurance Partners,

Car Makers and Rental companies

150K data points recorded, processed and

stored every minute

152 Billion data points analyzed to deliver

insight to our Partners

More than 400K crash events analyzed.

3


4

OCTO’S MARKET POSITIONING

Insurance companies

OEMs

Car rentals

4

Octo has 141 World Wide Insurance Partners, Car Makers and Rental companies.


1+1 = 3

Octo Telematics’

approach to smart data

and telematic services

5


6

• Common Layer is the core of the

system

• It gathers data from telematic devices,

attributes and external data in order

to better characterize drivers’

behavior and enrich knowledge from

a business point of view

• Devices and drivers are analyzed on

various dimensions time and space,

vehicle data, socio demographic data,

traffic, crashes, in order to spotlight

their main features and behaviors

THE COMMON LAYER: OCTO’S APPROACH TO SMARTDATA

THROUGH ANALYTICS

Data gathering from different sources

Data transformationtrought Advances

Analytics

KPIs and Data insight

PredictiveModeling

and Scoring

Data

Mon

eti

zati

on

’ valu

e c

hain

Data

managem

ent

6


7

• Benchmarks are driving behaviors in a specific context

• They are related to a group of drivers

• E.g. Average Speed Nighttime, Urban Road, Expressway, Old Economy car

• E.g. Max Number Brakings Daytime, Motorway, New car, Cruise Car

• Quantitative measures (braking's, accelerations, cornering’s, …) are analyzed in all possible context

combinations (dimensions: time of the day, road type, …). A driver can belong to various contexts

COMMON LAYER – BENCHMARK

7


8

COMMON LAYER – PATTERN

• This layer has the purpose to analyze drivers and their behavior patterns

• E.g. John, Motorway, Daytime, Big Car, Nice Weather John drives very fast and he is among the

fastest drivers so his speed distribution is skewed to the right hand side of this benchmark

• E.g. John, Motorway, Nighttime, Big Car, Nice weather John drives copiously below this benchmark

average

John

John

8


9

COMMON LAYER – PATTERN & BENCHMARK

• All drivers are compared with their contexts (benchmarks)

• Important statistical Common Layer KPI will be distances between individual patterns

and their relative contexts (benchmarks)

• Comparison between individual patterns and benchmarks will outline drivers

positioning on the behavioral scale

9


A new generation of products and services which allow the policy holder to feel

himself at the center of customer journey

THE POLICYHOLDER will pay based on the real usage of what has been

assured.

THE INSURERS knows at any time, the level of individual risk or quality

rating of your customers as a current or predictive portfolio level

Insurance Telematics

OCTO supports Insurers for launching new products using rating based, even

partially, on electronic data collected through a telematic device.

Devices gather individual’s daily driving habit, driving behavior and

environmental risk related information to be used to define premium rated on

personal usage

PAY PER USEPAY AS YOU DRIVE

PAY HOW YOU BEHAVE

TELEMATIC SERVICES BASED ON RISK RATING

10


Risks can be measured or estimated through the entire policy lifecycle

Using a representative and huge telematics data-set it is possible to evaluate the entire

client portfolio

RATING TIMELINE

Time

Ex-ante portfolio RatingRisk exposure for clustered portfolio

Ex-post individual ScoringCurrent scoring of risk exposure

Prospect or traditional customer Policy-renewalPolicy

EX-ANTE SCORING

premiums rating are based on clustered risks which are better defined considering

telematics data and occurred events. These scorings are derived by multivariate or

cluster analysis.

EX-POST SCORING

calculated by using both individual driver devices information (including crashes/ claims

instances) and related environment risks information

t0

t0 t1

t1

11

TELEMATIC SERVICES BASED ON RISK RATING


How can Telematics help meunderstand my non telematicsportfolio?

How can I avoid “flat discounts” fornew telematics policies?

Is my “driving feedback” programworking?

Am I really decreasing the risk throughtelematics or just “eatingmy revenue”?

Are my current “customer segments”the correct ones?

Do I know my customers?

What data do I really need?

AM I PRICING EFFECTIVELY?

12

SERVICE DESCRIPTION CLIENT’S VALUE

S1-S2

Non Telematics PortfolioAnalysis to support Telematicslaunch (with or w/o claimshistory)

Support prospectsselection andtargeted commercialdiscount

S3 – S4 Individual or Portfolio DrivingTrends

Correlation analysisbetween individualor cluster drivingbehavior andinfluencing factors(feedbacks and tips,crash, etc)

S5 Individual Frequency predictive model correlating driving habits and behavioursto crash frequency

To support pricing accuracy

S6 As S5 + damage costs As S5 (enhanced)

S7 Individual «Context Based» asS5/6 with additional «context» (traffic, weather, context risk) weights

As S6 (top)

T0

T1

STRATEGIC QUESTIONS FOR INSURER

T1

OCTO’S TELEMATIC SERVICES


13

USING EXTERNAL DATA FOR GEODEMOGRAPHIC ANALYSIS

Octo’s approach

• Specific Algorithms and software helping to define and classify homogeneous risky zonesleveraging on different type of data (urban density, traffic, income,....)

1. Define granular map and create a new zone

2. Georeference events with latitude and longitude information (crash, acceleration, cornering...)

3. Create zones with an algorithm that seeks the best division of areas, “breaking” the links where other characteristics are weaker


Thank you for your attention

Daniele Tortora

Head of SASDOcto Telematics Corporate

[email protected]

Francesco FrinchillucciChannel Sales Manager

[email protected]

mailto:[email protected]

insurance day 2015 - presentation · (as of january 2015) up to 180k new customers in a month 141...

Documents