Lemonade is disrupting insurance. The incumbents will have to respond
New tech will bring the insurance industry into the 21st century
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Lemonade, the mobile-based insurer, was one of the most successful US IPOs of 2020 to date. The share price doubled in the first day of trading to reach a valuation of $3.9bn. Investors were excited by the potential for disruption in the huge insurance industry, shown by Lemonade’s revenue multiple of almost 37x, versus a multiple of 0.44x for Prudential Financial, a large legacy insurer.
Lemonade differentiates itself from other insurance providers by offering flexible monthly insurance and reducing the time to take out a policy or get paid. This makes their insurance particularly attractive to younger customers, with over 70% of Lemonade’s customers under the age of 35 and 90% buying insurance for the first time.
AI helps Lemonade to deliver their service, with three key use cases:
- AI Maya — A virtual assistant that collects customer information and provides quotes
- AI Jim — A bot that handles claims
- CX.AI — A bot that answers customer questions
Although Lemonade’s success is a great case study on the potential for AI to disrupt traditional industries generally, I’m more interested in the implications AI could have for the rest of the insurance market. Lemonade is a tiny player in insurance, with revenues 2% of Prudential’s, but its success might increase the uptake of AI by legacy insurers. Other insurers are likely to be more open to new technologies, either out of greed, because they see the multiples it achieves, or out of fear, because they might lose customers to a competitor with a better proposition.
The Lemonade data flywheel, with more data leading to a better customer experience and faster growth
Insurance is changing
Insurers are facing change beyond Lemonade too: mobile phone insurance is growing at 12.5% per year and is predicted to reach $32bn by 2025. Health insurers are encouraging customers to make healthier choices in exchange for cheaper premiums. Pay-as-you-go car insurance has now emerged too.
The rise of data sources, such as telematics in cars, internet of things in property and consumer wearables in health insurance and life insurance, means that insurers that can incorporate new data sources into their underwriting and claims management processes will have an advantage in a changing industry. There’s a clear opportunity for startups to help insurers understand and use these data sources.
Startups are tackling claims management and fraud prevention
The customer experience of insurance is poor, with the industry often performing badly in customer satisfaction surveys. There are many reasons for this, including outdated infrastructure, badly designed digital touchpoints and impenetrable legalese. No doubt major criticism also stems from the claims process being slow and inconvenient, even if it reduces the risk of fraud.
I’m interested in companies that can improve claims management and fraud prevention, helping insurers to provide a better customer experience and compete with new players like Lemonade.
Claims management is a great place to introduce new software, thanks to improvements in computer vision and natural language processing (NLP) technology. For example, there’s now software that can automatically extract information for a claim from unstructured data, such as images or written statements. Tractable initially used computer vision to assess damage for car insurance claims, and now also uses it in claims for floods, fires and hurricanes. Omni:us combines computer vision with NLP to rapidly process all kinds of insurance documents.
Fraud prevention is another area where startups can add value to insurers, with companies such as Shift Technology and Sprout AI using AI to identify fraudulent claims and automate the processing of low-risk claims. By screening out low-risk claims, AI lets insurers focus on high-risk claims and improves the experience for the majority of users.
There are still opportunities in the space
While the emergence of companies targeting claims management and fraud prevention mean it’s no longer blue ocean, there isn’t yet a clear winner.
There’s scope to compete on a broader range of input data, to better integrate into insurers’ processes and to move into new lines of insurance, such as life insurance. There’s also an interesting opportunity for companies to combine data from multiple insurers to better manage claims and identify fraud.
Given the size of the insurance market and the potential for AI to drive operating efficiencies for insurers, I expect more companies to hit scale over the next few years. If you’re building a company in this space, I’d love to hear from you.
