The liquidity problems DeFi still needs to solve

DeFi has plenty of capital, but too much of it sits idle, fragmented or locked into single-purpose positions. The next step is not simply more TVL - it is liquidity that can actually work when and where demand appears.

DeFi does not lack liquidity. That may sound strange when users still face price impact, fragmented routes and pools that cannot handle larger trades efficiently. But the problem is not always the amount of capital sitting in DeFi. It is how that capital is used.

Huge amounts of liquidity are deposited in pools without doing meaningful work. Assets have been deposited on-chain, but are not consistently helping execution or earning fees.

At the same time, liquidity providers often have to divide one wallet balance across different protocols, pairs, price ranges and strategies. Once those tokens are deposited, they leave the wallet and become committed to individual pools or positions until the LP withdraws and reallocates them, or until the agreed lock period ends.

So the real question is no longer: how much liquidity is locked? It is: how much liquidity is actually usable?

Passive pools made DeFi open

The first major liquidity model in DeFi was simple: users deposit tokens into a pool, traders swap against that pool and liquidity providers earn fees.

This changed crypto markets. Anyone could provide liquidity. Anyone could trade. There was no need for a centralized order book or a traditional market maker.

The strength was openness. But the weakness was efficiency. In many pools, most capital is not close enough to the active trading range to be used often. It exists in the pool, but does not process many swaps. For liquidity providers, this creates a difficult reality: capital can be allocated, locked in a pool and still barely work.

Concentrated liquidity improved efficiency, but added complexity

Concentrated liquidity tried to solve that problem. Instead of spreading liquidity across a broad price curve, LPs place capital in selected price ranges. When trades happen inside that range, capital works harder and can earn more fees.

This was an important improvement. But it shifted more responsibility to LPs. Now they need to think about ranges, price movement, volatility and rebalancing. If the market moves outside the selected range, the position may stop earning fees. The liquidity is still deposited, but it is no longer useful for current trading.

To cover more possible price movement, LPs may split their balance across several ranges. That gives them more positions, but each position is backed by only part of the original balance.

Concentrated liquidity therefore makes capital more targeted, but it can also make liquidity more fragmented and management more demanding.

Stable pools work well until the relationship breaks

Stable pools are built for assets expected to trade close to the same value: stablecoins, wrapped assets or similar tokens.

When the relationship holds, these pools can offer deep liquidity and low slippage. But the strength of the model is also its weakness. If one asset depegs or loses market confidence, the pool can become one-sided. LPs may end up holding more of the weaker asset. What looked like a low-volatility strategy can quickly become concentrated exposure to the token everyone else is trying to sell.

Stable pools solve a specific problem well. However, they do not solve the wider issue of idle and fragmented liquidity across DeFi. Capital is still deposited into an individual pool and committed to that pool’s specific purpose.

Managed strategies reduce manual work

Managed LP strategies and vaults try to make liquidity provision easier. Instead of choosing ranges or managing positions manually, LPs deposit into a strategy that handles part of the work for them.

This can be useful. It reduces complexity and gives users access to more advanced liquidity management. But capital is still committed to one strategy. If that strategy is not capturing much flow, the capital may still sit underused. If better opportunities appear elsewhere, the LP often has to withdraw, move funds and reallocate them through additional transactions.

The interface becomes easier. The structural problem remains: liquidity is still locked into separate boxes.

Market makers help, but cannot cover everything

Professional market makers use inventory, pricing systems and risk management to quote trades. In intent-based systems, professional participants can compete to fill orders and source liquidity from different venues.

This can improve execution, especially where public pools are too shallow. But market-maker liquidity depends on inventory and risk appetite. It may not cover every asset, every chain or every market condition. During volatility, spreads can widen and available liquidity can shrink.

Market makers are important. But they are not a full answer to DeFi’s liquidity problem.

Fragmentation is the root issue

DEX trackers now count tens of millions of liquidity pools across hundreds of networks — the vast majority of them shallow or inactive.

For LPs, that creates a structural constraint: one deposited balance normally cannot back several opportunities at the same time. To participate across pools, ranges or strategies, assets must be divided into separate deposits. Once capital is split, efficiency can fall.

A simple example:

An LP provides liquidity for the same pair across three venues. One pool gets 80% of the trading volume that month. The other two share the remaining 20%.

If the LP split capital evenly, only one third of the balance sat where most fees were generated. The rest was technically allocated, but mostly watching from the sidelines.

The total deposit did not change. The fee capture did. This is why DeFi needs liquidity models that do not force LPs to divide one wallet balance before knowing where demand will appear.

TVL is not enough

For years, DeFi measured success through TVL: total value locked. TVL is easy to understand. It tells you how much capital is deposited in a protocol. But it does not tell you how much of that capital is useful.

A pool can have high TVL and still contribute little to real execution. A strategy can hold large deposits while most liquidity sits away from actual demand. A network can look liquid on paper while routing still struggles in practice.

TVL also reflects a model in which tokens are transferred into pools and contracts. That capital may be locked, but locking it does not guarantee that it is active.

That is why DeFi needs a shift from TVL to useful liquidity. The better question is: How much capital can actually be applied when trades happen?

This is the logic behind TVU - Total Value Unlocked, - a metric 1inch introduced to capture exactly this shift. The focus moves from capital that is merely deposited to capital that remains available and can support execution across more than one position.

Why LPs feel the cost first

Liquidity inefficiency affects the whole market, but LPs often feel it first. They provide the capital. They take the risk. Yet a large share of that capital may not earn meaningful fees.

The problem becomes worse once impermanent loss is included. Impermanent loss occurs when the relative price of pooled assets changes after deposit: the LP can end up with less value than if they had simply held the tokens, even after fees. Concentrated positions can amplify this effect, since capital is exposed to price movement within a narrow band. Some LPs also face more advanced risks, such as Just-in-Time liquidity (see below). 

LPs can also face unnecessary friction when they want to move capital. Tokens deposited into one pool cannot support another position unless the LP withdraws them, pays gas and reallocates them elsewhere.

This shows a larger point. LPs do not just need access to pools. They need structures that help liquidity stay active across more opportunities, remain under their control and move only when it is actually needed.

JIT liquidity weakens long-term LP economics

Not every liquidity problem comes from idle capital. Some arise because liquidity can be strategically timed.

One example is Just-in-Time (JIT) liquidity. Instead of providing liquidity continuously, sophisticated bots can detect a large pending swap, add liquidity immediately before it executes and remove it immediately afterward. The goal is to capture a share of the trading fees without keeping capital in the pool for longer than necessary.

For long-term LPs, this creates another source of inefficiency. They supply liquidity over extended periods, but some of the fees generated by large swaps can be captured by short-lived liquidity that appears only for those transactions.

This highlights another limitation of shared liquidity pools. They do not just fragment capital - they can also create opportunities for sophisticated participants to extract value from liquidity providers. As DeFi evolves, improving capital efficiency will also mean designing liquidity infrastructure that is more resistant to these kinds of strategies.

The next liquidity model

Current liquidity models have failed to fully solve a core issue: liquidity remains fragmented, underused and often locked into single-purpose structures.

The next model should change that assumption. It should let one balance support multiple positions instead of forcing LPs to pre-split capital. It should reduce idle liquidity. It should allow tokens to remain under the user’s control until they are actually needed for execution. It should help developers access useful liquidity without rebuilding the same infrastructure again and again. Most importantly, it should make existing capital work harder.

Explore 1inch to follow the next stage of DeFi liquidity infrastructure.