Unlike traditional investors, investors in the crypto space must analyse and underwrite a series of stacked risks when investing in projects:
- Will the project create value and attract users?
- Will the project be able to capture value from those users and establish a long-term, defensible moat?
- Will the value captured accrue to the token?
The first test is the easiest in the sense that it’s one investors in traditional markets are already used to making. Is the product useful? Does it have product-market fit? Is the team experienced and capable? While in traditional markets a strong product and team get you most of the way there, in crypto this is only the beginning.
The second test is tougher in that it requires an analysis of the network effects present in the project’s particular product and sector. Ideally, as investors we want projects with multiple, compounding, unforkable moats that cumulatively mean the project has some form of increasing returns to scale, meaning it gets more difficult to unseat the bigger it is. In traditional markets, investors can get away with being less rigorous about this test as proprietary technology and strong teams can pose moats even absent strong network effects. The open nature of the crypto space means only network effects can provide reliable long-term defensibility.
The third test is the one traditional investors have the least experience with. Unlike equity which is generally likely to be valuable provided the project passes the first two tests, the value of a token depends entirely on how it was designed. While it’s possible to change the token model later, it isn’t always easy to insert a token into an ecosystem after the fact.
Good investments must pass all three tests, a daunting task made more difficult by the open, forkable nature of projects in the space. We believe few in the space currently think about investments in these terms, leading to significant mispricings and inefficiencies both in particular projects but also in entire sectors.
We will now dig into an example, using our framework to demonstrate why we believe the exchange space is currently relatively overvalued compared to the insurance space. To be clear, we believe both sectors have tremendous room to grow given the overall growth see happening in DeFi and crypto markets more broadly. However, as fundamentals focused investors it’s important to keep in mind the relative dynamics as well as the long-term ability to establish a defensible moat.
Applying The Framework
We will now apply our framework to two different sectors: decentralised exchanges and insurance.
In terms of value creation, this will depend on the specific products and is difficult to analyze in the abstract. At a high-level, it’s clear both these sectors represent core financial primitives likely to be extremely important and widely used long-term. The winners in these sectors will also be extremely important and widely used, but this does not mean they will be equally valuable.
In terms of value capture, as I argued in my piece on DEX Wars and Aggregation Theory, DEX liquidity is what Ben Thompson calls “undifferentiated supply”, meaning it is highly price elastic as most traders care only about best execution. While some users may interact with their favourite DEXes directly, we feel aggregators such as 1inchexchange, Debank will increasingly dominate since they allow users to get best execution on trades across all active DEXes.
While the supply side provides greater opportunity for differentiation on things like algorithm optimisations (Dodo), flexibility (Balancer), types of assets (THORChain), LPs are still primarily interested in optimising yield.
As such, an exchange’s primary moat is its liquidity since this will mean better execution for traders, higher trading fees and better yield for LPs. The problem with this is, as DeFi summer showed us, liquidity is hyper fluid and will go wherever the highest yield is. Any excess rent extraction to tokenholders will directly hamper execution and thus the exchange’s moat.
Now let’s compare this with insurance. Liquidity is also a moat for insurance in that more liquidity means greater capacity. However, insurance has several additional moats:
(1) Differentiated supply – Since insurance cover is underwritten for a given period of time, supply-side liquidity is less fluid as there must always be enough capacity to pay out existing claims (i.e. NXM’s MCR). In addition, supply-siders have skin in the game and must accurately assess claims to ensure the long-term growth of the platform. This is very different from an LP passively providing liquidity in an AMM
(2) Non-linear liquidity network effect – Unlike exchanges in which the liquidity network effect scales more or less linearly (more liquidity means better execution), the liquidity network effect for an insurance product scales non-linearly in that a platform with more liquidity does not just offer better pricing but is also capable of underwriting entirely new types of risks (e.g. protocol insurance for large treasuries). Large capital pools are able to underwrite a much greater variety of demand-side use cases and generate proprietary revenue, not to mention diversifying their liabilities and enabling greater diversification. This in turn provides greater efficiency, generating the familiar network effect flywheel.
(3) Diversification & Efficiency – Unlike exchanges in which efficiency depends almost solely on liquidity, for insurance protocols efficiency relies on leverage: using $1 of capital to underwrite >$1 worth of risk. Leverage, in turn, can only be achieved by underwriting a diversified set of risks. As such, not only is stealing liquidity difficult as we showed previously, new entrants will struggle to compete on price even if they attract liquidity as they will not have the diversified liabilities necessary to enable leverage.
(4) Differentiated Demand – Unlike exchanges in which traders care primarily about best execution and have little to no brand loyalty, insurance platforms are chosen based not just on pricing but also on a user’s trust in their ability to pay out. This brand moat can only be developed over years of paying out claims and cannot be forked or vampire attacked away.
As a result, we believe while both exchanges and insurance are important sectors that will spawn successful products, insurance is much better positioned to capture value long-term. While an imperfect comparison, this is also borne out in traditional markets, as insurance is the largest segment within financial services alongside banking. For reference, insurance is a $6.3T industry as measured by premiums paid and 30/100 of the world’s largest financial services companies by revenue are in the insurance sector. The world’s largest insurance company (Allianz) generates $172B in annual revenue and commands an $80B market cap. By comparison, the world’s exchange group (ICE) generates $6.5B in revenue and commands a $60B market cap.
In crypto, on the other hand, exchanges dominate insurance, with the cumulative market cap of decentralised exchanges being $2.7B compared to only ~$230M for insurance.
While the exchange sector is today clearly far more developed and possesses superior product-market fit compared to insurance platforms, we still see this as a significant mispricing given what we consider to be the relative future importance of the two sectors.
If you’re a founder building a product in the decentralised insurance space, please reach out.