The Magic Metrics of Insurtech
Under the hood, Insurtech businesses don’t look like most tech startups. There are unique characteristics and a handful of metrics specific to insurance that all insurtech founders & VCs should know (Part II of a three part series; Part I here).
The insurtech path is not easy. Notwithstanding the hockey stick-like growth of many first movers mentioned in Part I (Insurance is having its (neo) moment), questions remain around profitability, customer retention, high capital requirements and incumbent competition. Despite these challenges (which we will address in part III), we believe the path to insurance success is possible for early stage insurtech challengers. While every VC has their own investment criteria, there are a certain set of metrics and characteristics VCs seek when making insurtech investments.
Insurtech taxonomies for dummies (or VCs)
To help frame our discussion, we created a taxonomy within our self proclaimed ‘NeoInsurance Moment’. We break down insurtech businesses in three categories:
1 — Full Stack Insurtechs: companies that offer insurance products either as a managing general agent (MGA), leasing a balance sheet from an insurance company for a set commission, or companies who underwrite insurance policies using their own balance sheet. Often, the full stack insurtechs start as MGAs and transition to writing their own policies and accepting the subsequent risk and reward. In this category, these insurtechs address all parts (or at least the majority) of the insurance stack shown in figure 1 below (don’t worry, more about this value chain later). These full stack’s also typically start in specific sectors of insurance (auto, renters, life, commercial etc) before expanding across insurance verticals. Think of these companies as the challenger banks, but for insurance. There are many successful examples of full stack insurtechs listed below. Today, because this space is saturated, VCs look to back full stack insurtechs with an extremely unique acquisition strategy or a nuanced preferential take on underwriting.
2 — Tech Enabler Insurtechs: companies that solve specific portions of the insurance stack. These companies, instead of offering a full stack insurance product, address one or two components of the insurance value chain. We define a simplified insurance stack in figure 1 below:
Normally, these ‘enabler’ companies sell directly to insurance companies or full stack insurtechs and charge a software subscription fee or API fee. Throughout the first wave of Neoinsurance most insurtechs focused on applying artificial intelligence to the underwriting process on the front end of the stack (many listed below). Since then companies like ProNavigator or EvolutionIQ have started to address other parts of the insurance stack including policy workflow and claims. We also include ‘API first’ insurance companies in this category. This emerging field of embedded insurance has many nuances, but for purposes of this taxonomy we include all API companies who enable tech companies or insurance providers to build digital insurance products. The best examples of these companies include Sure, Boost, or Tint.ai (more on these in Part III).
3 — Insurance Aggregators & Marketplaces: companies that serve as lead generation for traditional insurers and full stack insurtechs. Often, these companies aggregate policies across multiple providers and take a broker commission on each policy sold. These comparison tools were part of the first Neoinsurance moment, taking insurance policies previously sold in local offices or golf courses online. Differentiation among aggregators has become hard, as growth stage insurtechs begin to master customer acquisition.
Key benchmarks and metrics VCs use to evaluate insurtechs
Once we understand the basic category an insurtech falls into, VCs look to key metrics to judge their value and growth potential. Some of these metrics only apply to certain taxonomies of insurtechs (like full stack insurtechs), but nevertheless they should be part of the lexicon of all insurtech founders and VCs. The table below describes these metrics, highlights the relative importance of each, and shares examples of an insurtech leader’s recent metrics (NYSE:LMND).
Comparisons are hard in insurance, but these metrics give VCs a sense of the size, traction, and profitability of an insurtech. We highlight Lemonade to show what’s possible for an insurtech challenger. It’s important to note that many of these metrics still cower in comparison to the magnitudes we see from insurance incumbents (State Farm did $66.2B in GWP in 2020) and that lemons shouldn’t be compared to oranges. Renters insurance looks different from auto insurance (as does life, commercial, home, pet etc.). So when comparing a loss ratio of Next to Root (auto insurance) one should apply a skeptical eye, but when comparing Next to Thimble (both focus on commercial insurance) stark differences should be cause for concern.
Our Magic Metrics
We want to highlight three metrics that we care about most: gross written premiums (GWP), gross loss ratio, and customer acquisition cost (CAC). To us, these magic metrics must be viewed in unison when evaluating an insurtech company. For instance, if a full stack insurtech has high GWP, a low CAC, but an abysmally high loss ratio, more customers and more premiums necessarily won’t lead to higher profits. Root ran into this problem as they scaled to go public in 2020. As they continued to grow GWP and acquire customers like crazy, their loss ratios continued to stay above 100% (see figure 2 below).
Thus, early stage companies should seek to improve all three of these metrics in tandem as they grow. While we like to see strong CAC, GWP, and loss ratios, the gradual improvement overtime is more important than a single monthly number. This shows venture investors that the insurtech company is getting better at the core principles of insurance, pricing and placing risk, not just acquiring customers.
The terms and taxonomy are important, but telling the future is more fun. In Part III of The NeoInsurance Moment, we will cover our predictions for what the next ten years of insurance will look like. If you have an insurtech prediction or want to be included in our seminole analysis reach out to Connor at clove@lsvp.com or on twitter @ConnorLoveCA.
— This was a joint post authored by Connor Love and Justin Overdorff, Lightspeed.
