DATA INNOVATION LAB · 2019-02-28 · 3 | SMART DATA AND DATA INNOVATION LAB AXA Vision 2020 –Focus and Transform Focus, the first pillar of our strategy, is about taking actions

DATA INNOVATION LABAS A KEY TRANSFORMATION ENGINE FOR AXA

Ankur Agrawal

June 1, 2017

A global leader in insurance and asset management*

2 |

€100BN

Revenues

€5.7BN

Underlyingearnings

€75.9BN

Shareholders’equity

Existing AXA locations

Based in 64 countries

165,000 employees

and distributors

Serving

107 million customers

* 2016 figures

3 | SMART DATA AND DATA INNOVATION LAB

AXA Vision 2020 – Focus and Transform

Focus, the first pillar of our strategy, is about

taking actions today to deliver sustainable

growth and meet the expectations of our

stakeholders.

The second pillar of our strategy is to transform

our company to ensure tomorrow’s growth and

prepare for future. We want to adapt our

business model from payer to partner.

Leading a profound transformation journey

4 | SAS - Bootcamp

Technological revolution

Regulatory changes

Customer expectations

Market environment

Transform means how do we get into a different relationship with our customers. Customers want more from us than just paying bills. They want us to accompany them. They want us to be easy with them. They want us to help them reduce their risk. This aligns our interests and their interests, and creates a win-win situation.

Thomas Buberl, Chairman and CEO AXA Group

To redefine the way we operate and call for a strong transformation of our business

With a strong focus on innovation

AXA PARTNERSManage large

partnerships

AXA NEXTDevelop new

business models

AXA LABDetect emerging trends

AXA STRATEGIC VENTURES

Invest in promising startups

KAMETBuild and incubate innovative companies

DATA INNOVATION LABLeverage data to transform

AXA TECH ENGINEERING LAB Test & learn digital ideas

DIGITAL AGENCYCreate digital assets

I N N O V A T I O N

Via key innovation structures

to create the most relevant services & assets and better serve customers

to foster a culture of inclusion, innovation and trust and transform our workforce

TRAINING

to upskill the people accross the

Group

REVERSE MENTORING

to reinforce digital saviness amongst

senior executives

START-IN

to promote internal creativity

And via key innovation programs

Data is a key

enabler in the new

Focus & Transform

strategy, and

the DIL acts as

a catalyst

9 | SAS - Bootcamp

Connected Devices as one of the key focus areas

Breaking new insurance grounds….

Connected Cars

Connected Homes

Connected Health

AXA

DriveCheck(Germany)

Smart Drive(Japan)

Collect, store,

analyze and share

data generated by

devices capturing

user’s’ behavior to

encourage safe

driving behavior and

healthy lifestyle

MyAXA Protected Home(Swiss)Eg.-

AXA HealthKeeper(Spain) AXA Xtra(Hong Kong)

Car Telematics

LAB &

EXPERTISE CENTER

To run research studies and

offer entities with advanced

telematics capabilities

TELEMATICS DATA

COORDINATION

To deploy Connected Devices

strategy on telematics data &

technologies

INTERNAL

TSP

To provide entities with end-

to-end telematics solution

Data Innovation Lab supports telematics business as a…

11 | Machine Learning in Telematics Insurance

5 steps to success ...

1.Pick a

device & app

from our

catalogue

2.We help

you define

your

telematic

program

3.Advertise

& Onboard

drivers

4.Let your

drivers

enjoy the

experience

5.Monitor

adoption &

performance

PAYD

PHYD

Gaming

SDK

INTERNALMachine Learning in Telematics Insurance

... keeping in mind a few things


Data protection laws are strict regarding collection and use of data:

o the insurer is not the police and cannot detect speed over the

limit

o the insurer has a contract with the insured client that does not

allow for pricing based on life profile data (though it can be

used to provide personalized driving tips)

Data quality and processing speed are essential:

o Dealing with bad precisions, wrongly API-enriched data, auto-

start in unwanted situations

o Being able to run disqualification/smoothing algorithms and send

back a score in ~seconds

Software stack


The team


Prototypers

Data

Scientists Developers

Designers

Product

Owners

~ 15 people

TEX Dashboards

Data visualization dashboards dedicated to each collaborator (manager, actuaries, claims handler, customer service desk etc.)

TEX Scores

Telematics Score – Speed, Acceleration/ Braking, Cornering, time of the day/ week, Road type

External Data: Road type, Traffic information, Weather conditions

Score Score

Pro

po

rtion

Pro

po

rtio

n

Normalized score as a (truncated) Gaussian (Mean: 70, Standard Deviation: 18)

Once raw subscores have been computed, they can be slightly modified to match a

desired score distribution while preserving the ranking of the drivers.

Team works with product/ pricing managers to integrate the scores in the proposition.

1: Road riskiness

We analyzed geolocalized open accident data to determine which characteristics of a road piece makes it dangerous

Road’s curviness and sinuosity are the highest risk factors

We use Here & OSM to map drivers with roads

We could warn drivers when they approach high risk road piece

We could weight driving scores w.r.t road dangerousness


2. Life Profile Analysis - Bad scores understanding


2. Life Profile Analysis - Using DBSCAN to determine areas of interest


2. Life Profile Analysis


Given the first 2 minutes of a trip,

can we determine where an insured

driver is going ?

Inform ahead of dangerous zones,

and provide tips, combine prediction

with road riskyness

Challenge the driver with his/her past

driving score on this road

Detect unusual trips

Provide prediction almost instantly

3. Trip Prediction

CONFIDENTIALITY LEVEL22 | Machine Learning in Telematics Insurance

The Telematics journey ….

23 |

Traditional Pay as you drive Pay how you drive

Behavioral Change towards Safe Driving

Risk Proxies

Utilization

Simple behaviors

using event encounters

Full behavioral

rating

• Estimated

mileage

• Garage Location

• Claims History

• Number of trips

• Time of day

• Mileage

• Acceleration

• Braking

• Cornering

• Excess Speed

• Approx. location

(GPS)

• Weather conditions

• Maneuvers

• Anticipation

• Aggression

• Adaptability

• Predictability

THANK YOU

Documents

DATA INNOVATION LAB · 2019-02-28 · 3 | SMART DATA AND DATA INNOVATION LAB AXA Vision 2020 –Focus and Transform Focus, the first pillar of our strategy, is about taking actions