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The new age of insurance distribution

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A brief overview of current startup trends in insurance distribution.
A talk given to the Insurance Institute of London at Lloyd's
18 October 2016.

Published in: Internet
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The new age of insurance distribution

  1. 1. October 2016 1 The new age of insurance marketing Rob Moffat
  2. 2. 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
  3. 3. Balderton Capital: What we do • Europe’s leading early stage tech investor • Invest £1-20M into technology companies • Look for potential for £1B outcomes
  4. 4. 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
  5. 5. 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
  6. 6. 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
  7. 7. Insurance ‘roboadvisors’: Embroker, Policygenius
  8. 8. Insurance wallets: Knip, FinanceFox, Safe, Clark >600K downloads of Knip alone
  9. 9. 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
  10. 10. New mutuals: Lemonade (also Guevara, Friendsurance) • …
  11. 11. Long tail, demand-driven: Bought By Many • … • Build social groups for niche risks and push ‘group deals’ to them
  12. 12. 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 claims Climate Corp offered a similar model before its $1B acquisition by Monsanto
  13. 13. 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
  14. 14. A VC’s view on the insurance market Marketing Sales and Service Data (users, claims, external) Underwriting => Machine Learning Capital and license Claims Administration
  15. 15. Opportunities for startups Marketing Sales and Service Data (users, claims, external) Underwriting => Machine Learning Capital and license Claims Administration Opportunity Opportunity Disadvantage (unless new proprietary data) Disadvantage Table stakes Table stakes
  16. 16. 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
  17. 17. 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
  18. 18. What are the opportunities and threats? Marketing Sales and Service Data (users, claims, external) Underwriting => Machine Learning Capital and license Claims Administration Opportunity to open or revitalise segments if can be a good partner Commoditised where data is plentiful Reinsurers, hedge funds Avoid drag factor Biggest advantage?
  19. 19. 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)
  20. 20. 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

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