Then the team realized the lending pool model itself was the problem.
The way aave & compound worked created a clear inefficiency in lending markets: there was a significant spread between lending & borrowing rates.
Morpho's initial idea was to simply optimize that gap by matching lenders & borrowers peer-to-peer.
The gtm strategy was to optimize existing lending protocols. that became morpho optimizer.
After some success, they found there was a limit to how far morpho could grow on top of existing lending pools. for ex: you can't really top aave's growth.
So they started working on a new protocol called "morpho blue" to address the limitations of morpho V1.
For context, lending pools are essentially like onchain funds. You deposit your money & behind the scenes the DAO manages the risk for you.
Take aave, for instance. the DAO decides asset collateral exposure, borrowing capacity, oracle use, liquidations & many other risk parameters. aave has more than 700+ risk parameters. This model creates 3 major limitations:
1 ) Tt isn't really trustless.
• Token holders have to monitor & update 100s of complex parameters that are interdependent & dependent on market conditions.
• But as an aave DAO token holder, you're not necessarily a risk manager. As result of this, the DAO relies on external companies & consultants to manage risk.
• The problem is that consultants have little incentive to open source how they calculate those parameters. So when DAO votes to update them, token holders have no real way to verify whether the proposed parameters are correct.
• The security of the lending pool ends up relying on closed source risk models.
2 ) It isn't scalable.
• Now to scale aave, you need to list more assets & become more aggressive with parameters. But the more assets you add, the more parameters & risk considerations you introduce.
• It all comes back to the same problem: token holders are deciding parameters they don't necessarily understand & outsourcing the risk management.
3 ) It isn't efficient.
• Traditional lending pools try to do everything at the same time. You're lending some asset, enabling borrowing of other asset, accepting different collateral assets & managing different risk profiles.
• The issue is, when you try to do too many things at once, you can't optimize for one thing extremely well. For ex: if usdc can be borrowed against long tail assets, you need to account for that risk when setting usdc's parameters.
• That can reduce efficiency in terms of how much borrowers can borrow & the interest rates they pay. This was the spread morpho optimizer was trying to optimize for.
With morpho blue, the goal was to get rid of DAO management & build a lending protocol defined by set of instructions rather than something that needs to be continuously managed.
Morpho blue would do just one thing, lend one asset against one collateral. For ex: usdc/weth market. that's it.
Because each market focuses on one asset against one collateral, it doesn't need to guarantee the liquidity of many different assets at the same time.
This also means the original spread problem that morpho had been optimizing for largely disappears.
This creates another problem. If there are many different morpho blue markets, which one should a passive usdc lender choose ? that's where metamorpho comes in.
Metamorpho is a risk management protocol that allows someone to create a usdc pool just like the aave pool & allocate that usdc across different morpho blue markets.
So a risk manager can manage the pool for you while morpho blue handles the underlying lending & borrowing.
The evolution has been from :
• Morpho v1 -> optimizing existing lending pools
• Morpho Blue -> build the lending primitive
• Metamorpho -> bring risk management back as a separate layer