October 2016

1

The new age of insurance marketing

Rob Moffat

Agenda

• Introduction

• Emerging models of insurance marketing & distribution

• An investor’s perspective on where the potential lies

• How this could help or challenge market incumbents

Balderton Capital: What we do

• Europe’s leading early stage tech investor

• Invest £1-20M into technology companies

• Look for potential for £1B outcomes

A selection of our portfolio

SOLD $1.0B IPO/EXIT $2.2B SOLD $0.9B

SOLD $0.9B IPO/EXIT $2.0B SOLD $0.6B

Agenda

• Introduction

• Emerging models of insurance marketing & distribution

• An investor’s perspective on where the potential lies

• How this could help or challenge market incumbents

Micro-insurance at point of sale: Zhong An

• Founded 2013• 4B policies sold• 200 insurance

products sold• 400M customers

served• Investors: Ping An,

Alibaba, Tencent

Shipping insurance for returns embedded into Taobao, Tmall

See also for example Simplesurance, Asurion, Cover Genius

Insurance ‘roboadvisors’: Embroker, Policygenius

Insurance wallets: Knip, FinanceFox, Safe, Clark>600K

downloads of Knip alone

Snapchat generation: Trov (see also Cuvva, usecover)

• $46M of funding to date• Partner with AXA, Suncorp, Munich Re• UK launch imminent

Aiming to change insurance from a grudge purchase to an emotional one

New mutuals: Lemonade (also Guevara, Friendsurance)

• …

Long tail, demand-driven: Bought By Many• … • Build social groups for niche

risks and push ‘group deals’ to them

Automation to serve smaller clients: Meteo Protect

Allows small businesses to purchase weather insurance, making it cost-efficient through online sales, integrated systems and automated claimsClimate Corp offered a similar model before its $1B acquisition by Monsanto

Agenda

• Introduction

• Emerging models of insurance marketing & distribution

• An investor’s perspective on where the potential lies

• How this could help or challenge market incumbents

A VC’s view on the insurance marketMarketing

Sales and Service

Data(users, claims,

external)

Underwriting=>

Machine Learning

Capital and license

ClaimsAdministration

Opportunities for startups Marketing

Sales and Service

Data(users, claims,

external)

Underwriting=>

Machine Learning

Capital and license

ClaimsAdministration

OpportunityOpportunity

Disadvantage(unless new proprietary data)

Disadvantage

Table stakesTable stakes

Which are the biggest opportunities in distribution?Micro-insurance at point of sale Proven model, maturing market

Insurance ‘roboadvisor’ Will take time to crack customer acquisition, but many IFAs are replaceable with AI

Insurance wallets Could have huge impact. Competition fierce, can they continue to take trail commission?

Snapchat generation Exciting but unproven. Pricing challenge? Acquisition challenge?

New mutuals Do people get concept? Will fraud/ claims reduction be significant?

Long tail, demand-driven Technology unlocks new market. Challenge is lack of historical data, will insurers take risk?

Automation to serve small clients Interesting model but limited to niches where parametric approach can replace loss-based

Agenda

• Introduction

• Emerging models of insurance marketing & distribution

• An investor’s perspective on where the potential lies

• How this could help or challenge market incumbents

What are the opportunities and threats?Marketing

Sales and Service

Data(users, claims,

external)

Underwriting=>

Machine Learning

Capital and license

ClaimsAdministration

Opportunity to open or revitalise segments if can be a good partner

Commoditised where data is plentifulReinsurers, hedge funds

Avoid drag factorBiggest advantage?

What are the opportunities and threats?• The VC funding into fintech is now moving to

‘insuretech’• Majority of the money will be for new distribution

models and MGA models (hard to see a $B exit in B2B sales to insurers, license and balance sheet are off-putting to build from scratch)

• Tech entrepreneurs have 20 years of practice at innovating front end, they will move fast and find new opportunities

• These startups will sometimes open up new segments, but more often will take the place of existing brokers/channels

• Startups will look to partner, but if they cannot find a good partner they will go it alone or backward integrate over time

• Reinsurers are making a real effort here (e.g Munich Re)

Startups’ wish list from insurance partners • Allow flexibility on policy terms, wording and price• Acceptance that this may result in small losses in

early years• Clear path from ‘innovation division’ into production• Minimise ‘integration headwind’: do you have good

APIs?• Need help on claims and fraud, not always willing to

admit it• Open to equity participation, but not exclusivity• Profit share models not introducer fees