1. finance
2. personal finance
3. insurance

Zurich Insurance Company Ltd
Winning with Customers with Digital and
Big Data
Rendez-vous de Casablanca de l’Assurance, Casablanca, 15 April 2015
Salvatore Cavallaro, Deputy Head of Customer Office, General Insurance
We are a truly global Property & Casualty
business with presence in 170 countries
General Insurance
Business
Property and casualty insurance and services
Market segments
Individual, commercial and corporate customers
USD 2,894m
Business operating profit*
Distribution channels
Agents, partnerships, brokers, direct
Geography
Global
USD 36,333m
Gross written premiums and policy fees*
Results by December 31, 2014
*. Note: 2014 year-end results
Consumer trends
3
What happens in an internet minute
Note: 2013 figures. Image source: http://techwelkin.com/in-one-minute-of-internet-infographic
4
Key customer trends
Customer trends
Key Technologies
• Biometrics (e.g., facial
Hyper convenience
Anytime, anywhere, a fingertip
away
User
experience
Mass customization
• Connected sensors (e.g.,
Personalize goods and services
Share economy
Monetize spare resources or
capacity
Real and virtual
Increased fusion of both worlds
authentication)
• Speech recognition
• Geo-localization and sales force
automation
• Near Field Communication
Internet of
Things /
Big Data
Core
system
modernization
home Telematics)
• Wearables (e.g. Apple Watch)
• Advanced analytics,
integrating large data pools
• End-to-end digital platforms
• Multichannel integration
• Cloud computing and real
time processing
5
Hyper convenience
Shopping online in public places
Product photo walls in
airports and
railstations
Scan the QR code
One click shopping
Image source: https://mediawandel.wordpress.com/2013/04/25/virtuelle-shops-in-u-bahnen-s-dkorea-machts-vor/
6
Mass customization
Large-scale personalization
From
personalization of
product to 3D
printing
Consumers willing
to pay for just what
they need
Modular products
tailored to own
needs (e.g. Nike)
7
Share economy
Uber PoP
Rent a spare seat in
your car
Uber’s offer extension (200
cities, 53 countries)
Valuation ~ 40Bn $
Image source: http://www.wired.it/lifestyle/mobilita/2014/05/07/uber-milano-uberpop/
8
Real and virtual
Your health at a glance
All personal data on
health and wellness in a
single dashboard
Emergency card that can
be accessed rapidly
Several KPIs tracked
(e.g. nutrition) from
different devices (e.g.
watch, scales)
9
Zurich Response
10
Responsive website and fast quote
Responsive website
Fast quote
• Content adapts to mobile devices
• Touch navigation pattern
• Cleaner, more intuitive web design
• From 40 to 12 questions
• Pricing accuracy not impacted thanks
to sourcing from external nonconfidential data
Note: This product, and related service, are not available in all markets and, in some jurisdictions, they may be in either proto-type or pilot stage.
11
Leveraging Telematics – Zurich BluDRIVE
Innovative services bundled
in 3 distinctive BluDRIVE propositions
YOU
CAR
FULL
Focus on roadside
assistance
Focus on theft protection
Combine assistance and
theft
bCall
bCall
Engine disabler
eCall; Crash report
Note: This product, and related service, are not available in all markets and, in some jurisdictions, they may be in either proto-type or pilot stage.
12
Zurich mobile application
Personalized and location
based services for 5 LOBs:
Motor, Home, PA, Legal & Life
Personalized claim notification
direct from scene of accident
Routing to Zurich branches and
emergency facilities like
hospitals, contracted lawyers
Personal inventory of valuables
with pictures
Note: This product, and related service, are not available in all markets and, in some jurisdictions, they may be in either proto-type or pilot stage.
13
Personalized video messages at renewal
One of the first carriers
to send email with
personalized video
message to customers
Video message
includes: customer
name, policy premium,
services offered &
nearest Zurich office
+14 pts NPS score at
renewal touchpoint
Note: This product, and related service, are not available in all markets and, in some jurisdictions, they may be in either proto-type or pilot stage.
14
Big Data
15
Our ability to utilize new sources of data
is expanding
Unstructured /
external
Real Estate
records
Conference
presentations
Call center
interactions
Websites
• Customer
• Suppliers
Unstructured /
internal
Emails
Macro
Economic
• GDP
• BLS
• Housing
starts
Construction
Protection
Weather
• NOAA
• FEMA
• NWS
Legal /
Legislative
• Class action
history
SharePoint
CAT models
• RMS
• SLOSH
Exposures
Online
forums
Claims
notes
Audit
reports
Scanned
images
Technical
drawings
• Construction
documentation
• Floor plans
Demographic
• Census
• BLS
Engineering
reports
Structured /
internal
Occupancy
Beaureu
/ Industry
• ISO
• Permits
Municipal
• Building codes
• Permit filings
Structured /
external
Research
papers
Policy
binders
Financial data
• EDGAR / 10K
• Market data
CMS
transactional
data
Trade
publications
Credit history
Geospatial
• Elevation
• Land cover
Note: Use of data sources is subject to legal and regulatory requirements.
16
Individual underwriter pattern recognition
is insufficient
Management
Tenure
Number of
Subcontractors
Roof
age
New or
Renewal Account
Financial
Rating
Claims
Underbillings
Driver Incentive
Program
Policy Age
Vacancy
Rate
Number
of
stories
Payment
timeliness
Continuity
Planning
Number of
Endorsements
Owner Operator
Amount of
Payroll Change
Year
built
Size of Job
Class Fit
Exposure
states
Number of
Cancellation Notices
17
Approximately 1/3 of the time, individual pattern
recognition results in poor decisions
PREDICTIVE
COUNTER PREDICTIVE
66%
34%
Note: Graphics shown in each category (Predictive, Counter Predictive) are purely illustrative.
18
Workers’ Compensation example: Initial expected
loss is calculated using industry data
~2,000
Low
High
Initial Expected Loss (Using Industry Data Only)
19
Zurich’s view of expected loss can vary significantly
from a basic view
Zurich’s relative expected loss
60%
~25%
0%
(60%)
Low
High
~(40%)
Initial Expected Loss (Using Industry Data Only)
20
Our policy level expected losses are ~40% lower to
~40% higher than using industry data only
60%
Zurich average diff. from Industry
Decile Number
Zurich’s relative expected loss
10 44%
9 17%
8
0%
7%
7 (1%)
6 (7%)
5 (12%)
4 (17%)
3 (22%)
2 (29%)
1 (43%)
(60%)
Initial Expected Loss (Using Industry Data Only)
21
Resulting ‘lift curve’ shows how Zurich can
appropriately price for the risk
Zurich average diff. from Industry
Decile Number
60%
Zurich’s relative expected loss
44%
17%
9 17%
8
7%
0%
1
2
3
4
5
6
(7%)
(12%)
(17%)
(1%)
7
10 44%
7%
7 (1%)
8
9
10
6 (7%)
5 (12%)
4 (17%)
3 (22%)
(22%)
(29%)
2 (29%)
(43%)
1 (43%)
(60%)
Deciles
22
We’ve calibrated our underwriters to drive
consistent risk assessment and pricing
5/5/5 RESULTS1
WHAT IS 5/5/5?
If we give the same five files …
A
B
C
Prior to 5/5/5
D
E
38%
62%
… to five underwriters …
Current calibration
9%
… they should be able to come within
+/- 5% of the Technical Price
-5%
0%
Technical Price
for file A
1
+5%
91%
Not Calibrated
Calibrated
Commercial Markets only
23
Thank you
24
Legal Notice
©Zurich Insurance Company Ltd. All rights reserved. You are not
permitted to create any modifications or derivatives of this presentation or to
use it for commercial or other public purposes without the prior written
permission of Zurich Insurance Company Ltd.
Although all the information used was taken from reliable sources, Zurich
Insurance Company Ltd does not accept any responsibility for the accuracy
or comprehensiveness of the details given. All liability for the accuracy and
completeness thereof or for any damage resulting from the use of the
information contained in this presentation is expressly excluded. Under no
circumstances shall Zurich Insurance Company Ltd or its Group companies
be liable for any financial and/or consequential loss relating to this
presentation. The information contained in this presentation reflects the
speaker’s own personal view and does not necessarily reflect the opinion of
Zurich Insurance Company Ltd.
25