Webinar : Desperately Seeking Transformation - Part 2: Insights from leading insurers Data projects

1. Delivering Digital Together
Desperately Seeking
Transformation – Part 2:
Insights from leading insurers
Data projects

2. Delivering Digital Together
Disclaimer
Presentations are intended for educational purposes only and do not replace independent
professional judgment. Statements of facts and opinions expressed are those of the
participants individually and, unless expressly stated otherwise, are neither the opinion nor
position of The Digital Insurer. The Digital Insurer do not endorse or approve, and assume
no responsibility for, the content, accuracy or completeness of the information presented.

3. Delivering Digital Together
Welcome
Simon Phipps
Founder
The Digital Insurer

4. Delivering Digital Together
Today’s Agenda
75
Minutes
Welcome
Opening remarks
Data Case Studies
• Ergo
• Cathay Life
• HSBC Life
Closing reflections
Close

5. Delivering Digital Together
Housekeeping
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5
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6. Delivering Digital Together
Today’s Presenters
Theresa Lin
Senior Vice
President, Corporate
Planning Department,
Cathay Life Insurance
Pawel Bulowski
Technical Program
Manager,
ERGO Technology &
Services
Michal Denka
Senior Program
Manager,
ERGO Technology &
Services
Luis Gomes
Head of Health
Solutions HSBC Life
(International) Limited
Vincent Caldeira
Chief Technology
Officer, APAC,
Red Hat
Priscilla Dell'Orto
Partner & APAC Head
of the Customer
Strategy and Marketing
Practice,
Bain & Company

7. Delivering Digital Together
Opening remarks
Priscilla Dell'Orto
Partner & APAC Head
of the Customer
Strategy and Marketing
Practice,
Bain & Company

8. DATA TRENDS SHAPING THE FUTURE
OF INSURANCE
November 2023

9. 9
231130_TDI Webinar_Data ...
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We are witnessing a data explosion enabled by a surge in analytics and technology
More data available/
captured/created
x4 zettabytes of data to
be created by
‘25 vs. ‘20
More powerful
computing/ analytics
capabilities making ML
economical
Exponential
advancements in AI
and ML—GPTs are just
the beginning
10K+ tools for
automation/ execution,
black box learning
creating choices and
confusion
From omni-channel to
ecosystem: mobile first,
resurgence of
in store, marketplace,
metaverse, web3
E X P L O S I O N O F
D A T A S E T S
F A S T E R
C O M P U T I N G
S M A R T E R A I / M L
A N D G E N A I
T E C H N O L O G Y
O V E R L O A D
E C O S Y S T E M
E X P A N S I O N

10. ‘Data-driven’ companies outperform in key areas, and are delivering 15-20% EBITDA
margin increase through extracting value from data
Data objects accessible via self-
service interfaces by employees
75%+
Employees with basic data
literacy (advanced level for specific
roles/grades)
100%
Return on D&A spend
(i.e. D&A is fully self funded)
>3X
EBITDA margin increase through
D&A initiatives
15-20%
Data objects actively governed
by Data Owners
100%
Empowered employees driving decision
making, leveraging data in self-service mode
D&A at the centre of organization culture
with committed investment to improve D&A
skills of all employees
High share of self-funded data initiatives
via high value use cases & data monetisation
Value generation from data through scaled
and repeatable use cases
Data governed as a key asset across the
organisation, treated the same way as cash
E 2 E D A T A P O V

11. 11
231130_TDI Webinar_Data ...
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Leaders deliver more value from data, are more profitable, and grow faster
... and are more confident
they will reach their
targeted value realization
4x
% of insurers who answered “Above” or
“Well above” expectations
% of insurers who answered “Very” or
“Extremely” certain
… grow revenue faster
than competitors …
% of insurers who answered “Better” or
“Much better” than competitors
… are more profitable
than competitors ...
% of insurers who answered “Better” or
“Much better” than competitors
Leaders
Laggards
Last 3 years Next 3 years
Note: 1) Leaders are defined as those respondents who received a score equal to or higher than the calculated 90th percentile on a 5-point scale assessing 9 pre-defined metrics. Laggards had a score equal to or below the calculated 10th percentile.
Maturity scores are based on how much respondents agreed to each statement – from “Strongly disagree” (1) to “Strongly agree” (5) | Source: Bain’s Data and ML foundation survey (2023), N = 240, Insurance N = 35
Leaders1 deliver more
value from data...
n/a
I N S U R A N C E

12. 12
231130_TDI Webinar_Data ...
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Some insurance companies are already leveraging policy holders’
personal data on a wide range of use cases
N O T E X H A U S T I V E
Targeted
marketing
Customer
acquisition/
conversion
Customer
retention
Cross-sell Advanced risk
selection/ price
optimization
Risk assessment/
claim prediction
and prevention
Claim
management
Fraud prevention
• Provides a single
easy-to-use
dashboard to help
advisors and
agents listen and
share content
across social
networks including
Facebook, LinkedIn,
Twitter, Google+
• Creates complex
customer
segments and
models predictive
behavior by
segment
• Designs targeted
emails and
personalized
product
recommendations
• Offers a Social CRM
solution, including
management of social
media activity and
measure of marketing
campaign/ actions
ROI
• Predicts churn and
Customer Lifetime
Value prediction
through internal and
external data (e.g.
social media)
• Determines customer
life stage and
behavioral patterns
through multichannel
analysis and AI,
correlated with a new
need of service
• Adjusts premium to
driving behavior
data analysis (e.g.
breaking,
acceleration)
• Adjusts premium to
social media profile
screening (aborted)
• Adjusts premium/
grand rewards or
discounts through
health/fitness data
monitoring
• Monitors Smart
Home data to
prevent/ anticipate
risk occurrences
• Prevents acute
disease risks
through health data
monitoring
(partnership with
Cardiogram)
• Improves actuarial
risk assessment to
advanced machine
learning applied on
personal data
• Uses chatbots to
collect client data
and initiate claims
process
• Uses geo-location
data to improve
assistance services
in case of car crash
• Assesses fraud
risks on claims,
leveraging internal
and external
customer data
• Leverages facial
recognition to
prevent identity fraud
Source: Bain experience, lit search
Sell insurance products Improve risk profile Improve claim processes

13. 13
231130_TDI Webinar_Data ...
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Behavior
Customer propensities
Channel Propensity
Discount Propensity
Customer Segment
Product Propensity
Offer Propensity
Risk score
Retention score
Attitudinal
Preferences, opinions,
desires and sentiments
pNPS
NPS insights (sentiment)
Opinion about product features
Social media sentiment
Source: Bain experience
Raw data Inferred Signals
Life moments
Related to family
and career
Credit Need
Know Me Index
Identity Resolution/ Householding
Transactional
Data collected
during interactions
Service Interactions
CRM, Profile
Loyalty and Rewards
Credit and Risk
Marketing Interactions
Transactions
N O N E X H A U S T I V E
Environmental
Data collected from
other sources
Lifestyle Preferences
Open Banking
Credit Bureau
Life Events
Customer
DNA
Descriptive
Informed profile and
demographics
Gender
Age
Style
Address
Marital status
Contact information
Income level
Credit Score
Driving value from data use cases requires harnessing relevant customer
data – capture, manage and activate both owned data & customer signals

14. Delivering Digital Together
Opening remarks
Priscilla Dell'Orto
Partner & APAC Head
of the Customer
Strategy and Marketing
Practice,
Bain & Company

15. Delivering Digital Together
ERGO
Pawel Bulowski
Technical Program
Manager,
ERGO Technology &
Services
Michal Denka
Senior Program
Manager,
ERGO Technology &
Services
.

16. Michał Denka, Paweł Bulowski
#futureisnow
Data & AI at ERGO Group AG

17. What do we stand for
What do we stand for
Data & AI at ERGO Group AG | Michał Denka, Paweł Bulowski 17
1. For true digital transformation, you first need to
undergo cultural transformation. You have to
take staff on the journey with you and create a
new, agile mindset which paves the way for
digitalisation.
2. The business models need to be transformed in
a second step. This includes adapting old
business models to the needs of customers and
revamping them; creating new, purely digital
offers; and paying greater attention to and being
actively involved in the ecosystems that are
developing around customers.
3. Last but not least, we of course have to have a
good command of new technologies and use
these effectively. Keywords here include artificial
intelligence, robotic process automation,
applications for smart speakers, phone bots,
smart devices and virtual reality.
//Digitalisation at ERGO

18. Data & AI at ERGO Group AG
How to effectively support P&C Underwriters
in an international insurance company?
Data & AI at ERGO Group AG | Michał Denka, Paweł Bulowski 18
Program MARS (Managing of Systemic Risks) was initiated
in August 2020 following the COVID-19 pandemic with the aim to
reduce the volatility of ERGO's P&C loss ratio by reducing
underwriting leakage (e.g., inadvertent coverages).
MARS forms a global collection of individual or unique
policy wordings and establishes a clause library to enable
underwriters to review and negotiate (draft) wordings via
verification of wording and clause compliance with guidelines.
MARS supports the ERGO Group in the analysis of major loss
scenarios and further reinforcement of best practices.
Reduced Loss
Ratio Volatility
/ Reduced UW
Leakage
Facilitation of
individual
wording
analysis
Risk mitigation
via systematic
global wording
analytics
Global management of
systemic risks
Facilitate underwriting
excellence
Efficient wording
development and negotiation

19. Data & AI at ERGO Group AG
What’s behind MARS and why it’s GWR?
Data & AI at ERGO Group AG | Michał Denka, Paweł Bulowski 19
MARS evolved into the Global Wording Repository
The GWR is a cloud-based enterprise content management solution (ECM)
established to store all unique insurance wordings (P&C) in a centralized
repository for efficient governance, facilitation of the terms & conditions
and consistency in Underwriting.
Benefits:
✓ Ensures central availability of all wordings for users worldwide
✓ Enables AI analyses for translation and search facilitation
✓ Helps identify product conditions that drive risk
✓ Facilitates more frequent product condition updates
✓ Promotes efficient adaption of product conditions
to react to changing requirements
Capabilities
Clause
libraries
Context-based
search
Cloud and
global storage
Automatic
translation
Collaboration
& reporting

20. Data & AI at ERGO Group AG
GWR is a truly global solution for 20 affiliates in 16
countries, storing 50k+ unique documents for 600+ users
Data & AI at ERGO Group AG | Michał Denka, Paweł Bulowski 20
3 ERGO Direkt
4 ERGO Estonia
5 ERGO Greece
6 ERGO Hestia
2 ERGO Austria
1 DAS Belgium 8 ERGO Lithuania
9 ERGO Singapore
10 ERGO Thailand
13 ERV Czech Republic
12 ERGO Versicherung
11 ERGO Travel UK
15 ERV Germany
16 ERV Italy
17 ERV Poland
18 ERV Spain
19 ERV Sweden
20 NEXIBLE
7 ERGO Latvia 14 ERV Denmark

21. Data & AI at ERGO Group AG
Ambition 2024 – How to enhance our data capabilities
with well-designed AI solutions?
Data & AI at ERGO Group AG | Michał Denka, Paweł Bulowski 21
How do we contribute
• The AI Factory establishes a common and compliant
platform for running production ready AI Use Cases
as well as providing a flexible model development
and testing environment
• With introduction of VectorDB to the digital landscape
of ERGO Group we are in avantgarde of digitalization
efforts
• Large Language Model POC for Global Wording
Repository gives us high hopes regarding further
enhancement of search and analytical capabilities
• As there is no status quo we are not focusing on
one tech stack only – ie. ERGO GPT initiative

22. Delivering Digital Together
ERGO
Pawel Bulowski
Technical Program
Manager,
ERGO Technology &
Services
Michal Denka
Senior Program
Manager,
ERGO Technology &
Services
.

23. Delivering Digital Together
Theresa Lin
Senior Vice
President, Corporate
Planning Department,
Cathay Life Insurance
Cathay Life

24. Getting Value from Data to Boost Distribution Strategies
- Creating Tailored Customer Journey with CARE
Cathay Life Insurance Ltd.

25. 25
About Cathay Life Insurance
Founded in 1962
⚫ With 8+ million customers and 20+ million in-force policies
⚫ One of the only two financial institutions in Taiwan listed on Global Fortune 500
Implement dual transformation to transform into a “technology company
providing financial services“
Challenges and opportunities Dual transformation
New Environment
Changing consumer
preferences and
expectations
New Competition
Emergence of disruptors that
challenge the status quo
New Technologies
New technologies that
unleash imagination.
Data-driven
technology and data-driven
changes
technology company
providing financial services
Innovation
bold pursuit for innovation models

26. 26
We change, because we CARE
Top down Outside in War room Empower PO Review
Transformation
Committee Meeting
• TCM biweekly review
• Quick decision-making
• Empower Product
Owner
• Cross-functional teams
• Organizational innovation
• Agile culture
Visit leading international
companies
⚫ Spirit of “What if We Could” and the TOWER principle
⚫ Reshape employees in thinking how to use innovative technologies to improve core business procedures.
⚫ CARE – an AI system that optimizes the insurance experience
Cathay Life Insurance, as a people-oriented organization.
Cathay AIMs, used to measure customer marketing potential.
Cathay Relationship Score, used to rate service satisfaction.
Cathay Eye, used to rate customers' health status.

27. CARE Scoring System
27
1. Go beyond traditional
insurance pricing
models.
2. Design new products
based on segmented
pricing.
3. Pre-underwriting
mechanism to improve
customer insurance
experience.
5. A new way to predict customers‘ NPS
• “One Customer Multiple Scores”
• Customers’ needs in terms of Health, Marketing, and Service.
4. Customer demand-oriented marketing guidance

28. CARE Scoring System
28

29. CARE Scoring System: 1-Cathay Eye
Risk segmentation pricing model
• Client data in eight major categories
• Apply data science technology to build models and to develop predictions
H
M
L
Cathay Eye Development Risk Ranking & Clustering Healthy Risk View
12
Models
440
Features
Training Data
6.5 Million
Ensemble
Learning
29
Cathay Eye allows us to better understand customers’ health status, with the ability to identify a
500% mortality risk difference between the high and low risk segments.

30. 30
Application of Cathay Eye
Predicts incidence to achieve risk segmentation management in marketing services, underwriting
experience, product pricing, etc.

31. 31
CARE Scoring System: 2-Cathay AIMs
Upselling potential scoring model
➢ We are able to predict upselling potential for each customer in next 3 months.
➢ Prediction includes 7 protection types, implemented in our agent’s marketing tool/platform.
• Extracting the most critical information from hundreds of millions of data points.
• Use AI to mimic the sales patterns and to analyze the complex purchasing behavior and the sales experience.
• Accurately met 80% of customer needs.
Life
Surgery
Critical
Illness
Accident
Hospital
Reimbursement
Long Term
Care
Upselling
potential
Hospital
Surgery
Reimbursement
Critical Illness
Accident
Long Term Care
Life
9
6
8
4
3
5
1
Protection
Score
Protection
type
Agent tools
7 Sub-models According to Potential Types Customer Profile
modular structure Strategical
precision medical
products upsell
list
Basic information
Relationship history
Health information
Customer segmentation
Behavioral information
Insurance history
Financial status
Claims history
Cathay AIMs Development
Surgery
Hospital
Modeling

32. 32
Application of Cathay AIMs
Identify Target Customers Recognize Customer Needs
AGE
0 -
9
10 - 19 20 - 29 30 - 39
50 - 59 60+
Cathay AIMs ?
High Medium
Upsell Potential
Product Type Hospital Surgery
Reimburse
ment
Accident
Critical
Illness
Long Term
Care
Life
Customer Filtering
40 - 49
Cathy 25 years old
Customer Tags
High Income
Protection
Preference
R A M L D
H S
Cathay AIMs
Customer Profiles
Visit
Salespeople utilize customer filtering tools to identify target
customers with high upselling potential.
Transform upselling potential into marketing signals, which assist
salespeople in recognizing customer needs before visiting them.
Time cost
50%
Sales rate
400%

33. 33
Combined Use of Scores – Cathay AIMs and Cathay Eye
• Hit ratio 94%
• Sales rate trippled
• Claim ratio decreased by 33%
• NT$ 4.4 billion FYP raised
• Almost 900,000 customers were visited
Results
Testimonials
“Use the precision target list to
increase
customer-visiting frequency.”
-from Senior Vice President
“Formulate the company business
strategy,
thereby acquire low-risk customers and
raise the Mortality Savings.”
-from Executive Vice President
• Boost agent productivity and optimize profit.
• Targeting high upsell potential and low-risk customers for our agents to visit.
Target
Marketing Group
X
Cathay AIMs Cathay Eye
Protection products
find higher upsell potential customers
Mortality Risk
find low-risk customers

34. 34
We grow, as we CARE
People-oriented focus
• Continuously enhance customers' health
• Provide the products and services they truly need
Cathay AIMs
Cathay Eye
low
low
high
high
Target
Marketing Group
Wellness Program-FitBack App
• 1M members
• 120K monthly active users (MAU)
Testimonials
“After I retired, I had lost my focus in
living. The agent suggest me to use the
Fitback App to develop a habit of
exercise and make me healthier.”
- 67 years old retired customer
“The agent introduced me to use the FitBack
App, and I can get value-added service and
strengthen the connection with Cathay
Life Insurance.
- 60 years old alienated customer
For customers' needs,
we offer:
• Product Recommend System
• Customer and Agent pairing system
• Personalized Service Recommendations
For customers' health,
we offer:
• Wellness Program (e.g. FitBack)

35. 35
CARE Scoring System: 3-Cathay Relationship Score
Customer service
segmentation strategies
AI models that quantify the perceived quality of customer service.
(AI Model) Cathay Relationship Score
AI Model predict and amplify
scale of marked
NPS
• Customized segmentation service strategies with NPS predictive model
• Predict customers' likelihood of being Promoters, Passives, or Detractors
• Customer information from eight major areas generates over 1000 model features, resulting in 3.7x accuracy
Reviewing the customer
service history information
and proactively caring
about Detractors.
Detractors
1. Personal attributes
2. Customer segmentation
3. Marketing interactions
4. Service interactions
5. Underwriting
6. Policy administration
7. Premium
8. Claims
Training needs
Passives
Detractors
Promoters

36. 36
What if We Could
We Grow, as We CARE

37. Delivering Digital Together
Theresa Lin
Senior Vice
President, Corporate
Planning Department,
Cathay Life Insurance
Cathay Life

38. Delivering Digital Together
Luis Gomes
Head of Health
Solutions HSBC Life
(International) Limited
HSBC

45. Delivering Digital Together
Luis Gomes
Head of Health
Solutions HSBC Life
(International) Limited
HSBC

46. Delivering Digital Together
Closing reflections
Priscilla Dell'Orto
Partner & APAC Head
of the Customer
Strategy and Marketing
Practice,
Bain & Company
Vincent Caldeira
Chief Technology
Officer, APAC,
Red Hat

47. Delivering Digital Together
Thanks to Today’s Presenters
Theresa Lin
Senior Vice
President, Corporate
Planning Department,
Cathay Life Insurance
Pawel Bulowski
Technical Program
Manager,
ERGO Technology &
Services
Michal Denka
Senior Program
Manager,
ERGO Technology &
Services
Luis Gomes
Head of Health
Solutions HSBC Life
(International) Limited
Vincent Caldeira
Chief Technology
Officer, APAC,
Red Hat
Priscilla Dell'Orto
Partner & APAC Head
of the Customer
Strategy and Marketing
Practice,
Bain & Company

48. Delivering Digital Together
Interested in discovering more on the topic?
If the role of data in the digital transformation of insurance is a topic of interest,
then you might like to also take a look at the following items:
• On-demand Webinar:
Desperately Seeking Transformation – Part 1: Why data will make or break your
transformation plans - we explore the importance of having the correct data
architecture as a critical enabler for digital transformation success.
• Thought leadership Article:
Data lies at the heart of transformation - In this article, we look at how insurers need
to shift towards a distributed data-centric architecture, to respond effectively to
customer needs, whilst maintaining strict regulatory compliance when working with
partners.
48
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49. TDI Updates
Global Awards Finals
7th December 2023
(Global Award only)
Regional Awards
Asia Pacific
Award Finals: 29th June 2023
Europe, Middle East and Africa
Award Finals: 14th September 2023
The Americas
Award Finals: 9th November 2023
We are looking for most innovative insurance projects and the
most innovative InsurTechs in three different regions. The
regional winners will qualify for the global finals in their
category.
Global Awards
The winners of the regional innovation awards will be
competing for the global award in their category. In addition,
we have a gobal only award, the Insurer Transformation
Award.
Global winner
of the Insurer
Innovation
Awards
Insurer
Transformation
Awards
Visit the TDI Awards
page to see all the
regional finalists
Sign up for the Global
Awards (7th Dec – 6 PM SGT
/ 5 AM EST / 12 AM CET)
Delivering digital together.

50. Delivering Digital Together
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51. Delivering Digital Together
Desperately Seeking
Transformation – Part 2:
Insights from leading insurers
Data projects
Thanks for your time today!
(feedback please)

52. Delivering Digital Together
Contact Details
Priscilla Dell'Orto https://www.linkedin.com/in/priscilladellorto/
Pawel Bulowski https://www.linkedin.com/in/pawel-bulowski-ai-finops-cloud-tech-manager/
Michal Denka https://www.linkedin.com/in/mdenka/
Theresa Lin https://www.linkedin.com/in/theresa-lin-4b86b9152
Luis Gomes https://www.linkedin.com/in/luisalexandregomes/
Vincent Caldeira https://www.linkedin.com/in/caldeirav/
Simon Phipps https://www.linkedin.com/in/simon-phipps-0a627a/