Insurance in the digital era: use cases

Miami, August 28th, 2018

HCS Capital approach to investingInsurTech Drivers: AI and digitalization

2

CorporateVenture Capital

as-a-service

FinTech & InsurTech Fund

Machine Learning

About HCS CapitalHCS Team

3

Over 30 years of experience

managing businesses and

defining and implementing

growth and optimization

strategies

Former Director at McKinsey &

Company where he served as

the leader of the Insurance,

Banking and Technology

practices in Europe and Latin

America.

Senior executive with Allianz SE

where he led the creation of

Allianz Partners (largest B2B2C

insurer in the world). Director of

strategy and marketing at

Allianz Partners.

M.S. in Industrial and

Operations Engineering from

the University of Michigan.

Alex Horvitz

CEO

Over 10 years of professional

experience in private and public

sectors (finance, PGC and

government management).

Worked at P&G and Walmart,

and held leadership positions in

the Government of Chile during

President Piñera’s first

administration.

Led the due diligence and deal

closings of HCS Tech Fund I

investments in InsurTech and

Fintech.

M.B.A. from Harvard Business

School and M.P.A.-ID from

Harvard Kennedy School of

Government. B.S. in Industrial

Engineering from Universidad

de Chile.

Luis Felipe San Martín

Managing Partner

Extensive experience within the

public and private sectors. He

has served as a special assistant

and adviser to a U.S.

presidential candidate and has

worked in multiple

administrations.

Worked at Perella Weinberg

Partners asset management

division, where he analyzed

global hedge fund credit and

equity strategies.

Worked as an associate at

Chrysalis Ventures, where he

spent time in portfolio

operations and investment due

diligence.

M.B.A. from The Wharton

Business School. B.S. in Political

Science and Economics from

The University of Kentucky.

Ryan Smith

Associate

10 years contributing to top

corporate transformations,

incl. 3 years with McKinsey.

7 years directing data-oriented

programs for Société Générale

investment bank: Structured

finance deals migration to

Basel II, Trader fraud detection,

Global IT transformation

program.

Founder and Chief Scientific

Officer of Portendo Analytics,

HCS’s sister company,

specialized in designing and

implementing large scale &

high performance machine

learning platforms for finance,

insurance and e-commerce

companies.

M.S. in Mathematics and

Computer Science from French

Ecole Polytechnique.

Raphael Geronimi

Machine Learning Expert

InsurTech

Money transfer and payments

Personal loans

Mortgages

Savings and investments

SMEs credit

Budgeting and financial planning

Risk & compliance

FinTech

Distribution of specialty insurance

Claims, fraud and risk management

Retail property & casualty

Industrial processes

SME insurance

Travel & expat health insurance

Underlying Technologies

Artificial Intelligence

Machine Learning & Predictive Analytics

Digital, big data driven platforms

Internet of Things

Geographic Scope: North and South AmericaSectors

HCS Capital approach to investingTarget Sectors: FinTech and InsurTech

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Sectors: InsurTech &

Underlying Technologies

Focus: Series A and later

stage firms that are prepared

to scale globally

Sectors: InsurTech,

FinTech & Underlying

Technologies

Focus: Series A and later

stage firms that are

prepared to scale to North

and South America

North America

South America

P2P insurance platforms

Credit default insurance for P2P

credit and factoring platforms

Pet & equine insurance

Car collectors insurance

Renters & security deposit

Travel and expat health insurance

HCS Capital approach to investingInsurTech: Drivers and opportunities

▪ Machine learning is transforming client

interaction, churn management, fraud

detection, micro pricing/lower loss ratios

▪ Cognitive processing (natural language

processing) and robotics will optimize all

operational areas leading to greater

productivity and quality

Shifting

behavior

towards

insurance

▪ The explosion of connected devices (from 23

billion today to 75 billion in 2025) generates

tremendous amounts of new data and, when

combined with analytics, can produce

distinctive risk management insights

▪ IoT will impact all areas of insurance

From value-in-

service to

value-in-use

Internet of

Things (IoT) for

risk

management

▪ Digital interaction is transforming

distribution, product structure, and client

interaction, leading to lower client and

servicing costs

▪ Customer understanding and continuous

engagement create the opportunity for

micro products

A.I. and

Machine

Learning

InsightsDrivers

Specialty

insurance

marketing and

distribution

Insurance

products for SMEs

5

Investment opportunities in the US & Latin America

▪ Customers are looking for solutions rather

than specific products or services, leading to

the emergence of platform-based

ecosystems

▪ Clients (individual or companies) expect

high quality digital interaction

Internet of Things

(IoT) enabled &

telematics

Claims processing

platforms

AI-based automated claims

processing platforms

Fraud detection

Low complexity industrial

processes

Internet of Things monitoring and

automation

Optimized data based risk transfer

mechanisms

Connected car insurance

1

2

3

4

HCS Capital approach to investingMachine Learning: Core techniques

Family Application examples

Supervised

learning

Traditional insurance underwriting

Fraud detection

1

Customer segmentation

Error detection

Unsupervised

learning

Description

The algorithm learns with past data how context

variables (e.g., user age, marital status, revenues) are

linked to an outcome (e.g., did he purchase or not),

and use it to predict future outcomes on new data

The algorithm discovers the structure of data set

(e.g., the various “categories” or “topics”). From there it

can also detect changes in real-time new data

2

Merchandising optimization

Pricing optimization

Reinforcement &

bandit learning

The algorithm determines optimal action plan

toward an objective (e.g., maximize revenues),

balancing exploration and exploitation of

opportunities

3

Insurers can create substantial value by using Machine Learning in 3 key areas: Churn and sales optimization, Micro Pricing and Fraud Detection

Area

Churn and sales

optimization1

Fraud Detection3

Impact

▪ Higher revenues

▪ Better call centers profitability

▪ Uncovering and resolution of pockets of

anomalies

Micro

Pricing2

Description

Optimize different sales channels (including

remote) through automatic machine learning

models

Apply a broad range of machine learning

techniques to identify different types of fraud,

from identity fraud at application to false

insurance claims

Optimize on a personalized basis:

▪ Each contract price based on signup-time

price elasticity and later churn behavior

▪ Expected losses from different types of

insurance claims

▪ Each contract price based on behavior of

client across channels (e.g., second call with

agent)

▪ Better technical and commercial pricing

▪ Identification of pockets of “good risk” within

“bad risk” segments

▪ Reduce costs from false claims

▪ Prevent application fraud

HCS Capital approach to investingInsurTech Drivers: AI and digitalization

The transformation of the P&C value chain from Artificial Intelligence (AI) and Digitalization.

P&C Insurance Industry value chain: Present and Future. Costs and margins disaggregation (%)

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The Future:

Technology-

enabled

modern

insurance value

chain with

intensive AI

adoption, an

MGA, and a

single risk taker

The Present:

Traditional

P&C insurance

value chain

with an MGA

in the front, an

underwriter,

and a reinsurer

100

22

56

12

Written

Premiums

Sales &

MarketingDistribution

Admin &

ClaimsLoss Ratio

MGA

Margin

Re Insurer’s

Margin

The MGA controls the end to end

consumer journey in a more

efficient way by leveraging digital

distribution, automating claims

processing and even pricing

110

90% of the revenue can be optimized using AI based and digital

technologies to lower acquisition costs, reduce fraud, increase

client satisfaction, and improve risk pricing

▪ A Managing General Agent (MGA)

assumes oversight of marketing,

distribution, and claims processing. By

optimizing the brand and user

experience, an MGA lowers customer

acquisition costs and boosts retention.

▪ MGA’s margins are increased by

leveraging AI in areas such as:

▪ Customer Service (cost

reduction)

▪ Claims & Fraud (loss reduction)

▪ Sales Optimization (CAC

reduction)

▪ Cross Selling (revenue increase)

▪ Introducing advanced Machine Learning

algorithms allows MGAs to support the

risk carrier (value sharing model) by

improving pricing, thus reducing the loss

ratio. That extra margin is shared among

both the MGA and the risk carrier.

▪ As MGAs take control of distribution,

claims processing, and customer

journey, risk carriers can provide

insurance capacity directly to the end

customer, thus reducing overhead.

▪ Economic surplus will increase by 30 to

40%. And 2/3 of this value will be

captured by the MGAs and 1/3 by the

risk carrier.

1

2

3

AI allows better

pricing and reduces

loss ratios

Single risk

carrier

2

3

4

100

24

60

10

Written

Premiums

Sales &

MarketingDistribution

Admin &

ClaimsLoss Ratio

MGA

Margin

Margin for

risk carriers

6

Margin for

insurer and

reinsurer

HCS Capital approach to investingInsurTech Drivers: Leveraging data collected from IoT

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Car Insurance Home Insurance

Health Insurance Industrial Insurance

The volume of data generated by the Internet of Things is staggering.

Users are increasingly willing to share their data in exchange for greater value.

More accurate insurance pricing

Identification of good risk in

pockets of bad risk

Enhanced customer satisfaction

Higher loyalty and stickiness

Higher revenues and margins

Sources: IoT and the State of Insurance Industry Study – LexisNexis, 2018.

Insurers need to plug into the IoT (or risk falling behind) – McKinsey and Co., 2016.

IoT main benefits

▪ Accurate driver risk

assessment

▪ Driver behavior modification

and risk reduction

▪ Lower customer premiums

IoT main benefits

▪ Real time proactive alerts that

prevent major damage

▪ Higher customer engagement

▪ Faster claim processing

▪ Personalized risk ratings

IoT main benefits

▪ Higher drug adherence and

behavior modification

▪ More accurate health risk

assessment

▪ Higher patient engagement

▪ Lower treatment costs

IoT main benefits

▪ Real time monitoring

▪ Ability to remotely control

and automate processes

▪ Predictive maintenance

▪ Operating cost savings

▪ Accurate risk assessment

Benefits for InsurTech companies

Value in useFigo Pet Insurance

Company 2016 2017 GWP growth % growth

Nationwide 314,400,000 374,600,000 60,200,000 19%

Trupanion 160,200,000 191,600,000 31,400,000 20%

Healthy Paws 81,300,000 123,200,000 41,900,000 52%

Embrace 45,300,000 61,700,000 16,400,000 36%

Crum & Forster 58,000,000 69,200,000 11,200,000 19%

Pets Best 41,800,000 51,000,000 9,200,000 22%

Figo 2,500,000 8,500,000 6,000,000 240%

Pet Plan 78,200,000 83,600,000 5,400,000 7%

Pet First 19,500,000 24,900,000 5,400,000 28%

Pet Partners 11,600,000 14,000,000 2,400,000 21%

Pet Health Inc 26,200,000 27,700,000 1,500,000 6%

Total 839,000,000 1,030,000,000 191,000,000 23%

Pure Digital player, born in a Google

incubator

MGA model, thus no balance sheet

exposure, and a very high EBITDA

margin on steady state

Distictive tech platform: the Pet Cloud,

allowing for the creation of a digital

ecosystem

Customer acquisition costs are 50%

lower than industry leaders

Young, millennial focused and

distinctive brand with a superior

digital experience

Model (operations and IT) can be

easily expanded to Europe, Asia and

Latin America (2 to 3 month per

country)

Outstanding digitally oriented CEO

and leadership team

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In-Force GWP (USD) per company (US)

North American Pet Health Insurance Association (NAPHIA)

What’s unique about Figo?

Value in useFigo’s Pet Cloud

Figo’s first-of-its-kind Pet Cloud

is designed to give customers

the tools they need to manage

their pet’s life

Value in useFigo’s Pet Cloud

Increase the frequency of contact pointsImproving the digital relationship and knowledge of the insured

Predict Consumer BehaviorTo Customize the Value Proposition and Generate New Services

Connecting cars is only the first step, the real value comes from the

use of data and applied intelligence to offer customized connected

services and micro products

J

Mechanical Diagnostic

Safe Driving

GeolocationServices

CrashDetection(E-Call)

Maintenance

Reminders

MechanicalSupport(B-Call)

ContextualDiscounts

Rewards Smart Pricing

Smartcar Insurance & ServicesChanging the way we relate with our consumer

JooycarCopywrite

Insurance in the digital era: use cases