Big Data Analytics event

Leveraging

Big

Data

Amsterdam, May 14, 2014

@jochemdavids jochemdavids.nl

3

• Introduction to CED • History • Key figures

BUSINESS BACKGROUND

• Maturity model • Straight Through Processing • Data driven propositions

BIG DATA

• Market trends • Strategic choices • Challenges

STRATEGY

• Please feel free to ask any further details

QUESTIONS

Agenda

1 2

4 3

Business background

5

“The whole claims process at one company”

6

• Founded in 1971

• Number of employees 1.150

• Offices in 14 European countries

• Partners in 28 countries worldwide

• Handles approx. 1 million claims per year

• With a total claim cost of more than 2bn euro

• Revenue FY2013: 105 million euro

Key figures

7

Core businesses

LOSS ADJUSTMENT DIRECT REPAIR MANAGEMENT

CLAIMS MANAGEMENT

Strategy

9

• Due to safer infrastructures and safer cars.

• Consumers demand high service standards and web/mobile channels.

• Due to Solvency II and the will to improve Combined Ratios.

• Other forms of damage assessment e.g. based on statistics and big data.

Substitutes Cost

savings

Less

damages

Role of the consumer

“Market trends demand a shift in strategic focus”

10

Loss adjustment

Claims Management

Direct Repair

“Market trends demand a shift in strategic focus”

Loss adjustment

Cla

ims

Ma

nag

em

en

t D

irec

t Rep

air

Visual representation current revenue distribution

Visual representation future revenue distribution

11

• The integration of Claims Management with Loss adjustment and Direct Repair

• First Contact Resolution

Full service provider

• Decision making at FNOL

• Up to 80% automation (simple claims)

• Manage the exceptions (complex claims)

Automated Claims

Handling (STP)

Strategic choices

12

Changing something we (successfully) did for the past 40 years

Cannibalizing part of our core business by developing another

Fighting a market image, based on our strong history

Dealing with unilateral employee competencies

Batteling our IT legacy

Strategic challenges “Disrupt yourself before someone else will”

13

Strategic challenges “We are not alone…”

Big Data

15

Big Data Maturity mobel

Current business

model now dependent on Big Data

First project(s) show clear

ROI

How does this work? We’re OK

thanks

Where do we start?

Continuing to learn and

enhance

Creating a new

business model

0 1 2 3 4 5

Level of Big Data Maturity

Increasing Big Data Maturity

In the dark Catching up First pilot(s)

Tactical value

Strategic value

Optimize & extend

Source: Radcliffe Advisory

16

• Receipt and registration of the Claim

• Verification of the Claim coverage and liability

• Evaluation and assessment of the Claim

• Financial settlement and/or Repair in kind

• Client data • Premiums paid

Main Claims process

Notification Verification Assessment Settlement

and/or Repair

Coverage check (1)

• Business rules • Claim history • External sources

- Credit bureaus - Kadaster - Social media

Fraud check

Straight Through Processing

17

• Receipt and registration of the Claim

• Verification of the Claim coverage and liability

• Evaluation and assessment of the Claim

• Financial settlement and/or Repair in kind

• Event and policy

Main Claims process

Notification Verification Assessment Settlement

and/or Repair

Coverage check (2)

• Decision service for multiple party car accidents

Liability check

Straight Through Processing

18

• Receipt and registration of the Claim

• Verification of the Claim coverage and liability

• Evaluation and assessment of the Claim

• Financial settlement and/or Repair in kind

• Based on statistical and technical filters estimation of the damage

Main Claims process

Notification Verification Assessment Settlement

and/or Repair

Evaluation of claim

• Based on business rules initiate payment or repair service

Settlement service

• Based on business rules decide the repair type and available and specialized repairer

Repair service

Straight Through Processing

19

Data driven propositions

Core business process

Data generation

Data driven propositions

20

Data driven propositions

Damage history check for cars

•(eg. website or app)

Claim sensitive locations

•(eg. Insurers or local government)

Calculate your damage

•(eg. Consumers: car or property)

Claims data for improving creditscore

•(eg. Banks or insurers)

Perform fraud analytics and/or define fraud rings

•(eg. Insurers or lease companies)

21

“From gameshow rockstar to worlds best claims handler?”

22

“From gameshow rockstar to worlds best claims handler?”

“From gameshow rockstar to worlds best claims handler?”

24

25

Google Glass concept

26

Google Glass concept

27

Google Glass concept

28

Google Glass concept

29

Google Glass concept

30

Google Glass concept

31

Google Glass concept

32

Google Glass concept

33

Google Glass concept

34

Conclusion

Recognize the strategic importance

Organize innovation the right way

Start with business models in mind

Combine internal and external sources

1

2

3

4

Rietbaan 40 – 42

Postbus 393

2900 AJ Capelle aan den IJssel

The Netherlands

T +31 (0)10 284 34 34

info@ced-claimexperts.nl

Thank you for your attention

Jochem Davids