The question to ask is whether these challenges are endemic to insurtech, or whether they are specific to these three companies. My take is much more the latter. Insurance is a hard sector to enter with plenty of pitfalls, but it is a trillion dollar industry with many profitable incumbents, and tech can bring dramatic efficiencies. I stand by my article from 2015 on the challenges faced by traditional insurers and how tech companies can disrupt them.
There are a number of private insurtech businesses reaching real scale: Zego, ManyPets, Next Insurance, Ethos Life, Alan, Atbay, Coalition etc. Having seen some of their numbers I can say that their loss ratios are good, their unit economics are sensible and they are growing strongly. They are achieving this through great execution, and some combination of the following:
- Addressing new markets which didn’t exist before, such as cybersecurity
- Using telematics and novel data to meaningfully reduce losses and fraud
- Targeting underserved segments such as SMEs and the self-employed
- Operating in ‘easier’ lines of business where there is less competition and loss ratios aren’t as tight as in home and motor, such as pet insurance
At the same time I have also seen many insurtech startups which are either struggling to find product market fit, or are growing fast but with deteriorating loss ratios, unclear long term differentiation, or other issues below the surface. I have spent a lot of the last few years sitting on my hands.
Balderton’s only major investment in the sector remains Zego. From the list above they achieve real underwriting improvements with telematics and target underserved growing markets such as self-employed drivers. They also have great loss ratios, retention and unit economics.
So what have we learnt so far in insurtech?
- Underwriting is crucial. As an insurtech you start with the disadvantage of not having a base of loyal good customers. Where are you using tech to give you a real edge over incumbents? But also do you have enough actuarial talent and data to complement this?
- Telematics (real time data) works. Whether in motor or health insurance, telematics data has repeatedly demonstrated the ability to reduce loss ratios. As data collection becomes cheaper and universal expect telematics to become widespread across many insurance lines.
- GWP is not ARR, and insurtechs shouldn’t be valued in this way. Typical margins on GWP (after losses and service) are in the 20% range, and insurance is never going to have 100% or more net revenue retention.
- An insurance license is not something to be taken lightly, and is not the answer for every insurtech. Cash requirements and regulatory overhead are high.But it does given you the freedom to really improve underwriting.
- Your unit economics have to work. This starts with a good loss ratio, and requires you to have happy clients who stay with you. It also requires you to have a good customer acquisition cost, which in insurance is never easy.
- Automation will bring down expense ratios dramatically, but only at scale.
- Brokers are very hard to dislodge. Many startups have tried to bypass brokers without success. Some of the large private insurtechs above have ended up building a successful broker channel.
- If the barriers to entry are low expect competition to intensify quickly. See for example French home insurance where Luko were quickly joined by Lemonade, Lovys, Leocare and others.
- Disrupting a large sector takes time. Disruptors start off being worse than incumbents in all respects other than one really crucial one. Look at the early days of SaaS or Fintech for examples.
I would love to make an investment in insurtech in 2022. I sincerely hope that great founders haven’t been put off the sector by the share price performance of a few companies.
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*This post doesn’t at all cover companies selling tech to insurers — topic for another post some time
