Why this isn't "just another USDT deployment"

Arbitrum has bridged USDT for years. What's new is USDT0, Tether's omnichain implementation of USDT built on LayerZero's Omnichain Fungible Token (OFT) standard. Instead of yet another wrapped, fragmented representation of USDT moving around different bridges, USDT0 is a single, 1:1-backed unit of Tether liquidity that can move natively between Ethereum, Arbitrum, and a growing number of supported chains without fragmenting liquidity or introducing additional trust assumptions.

For integrators, that means supporting Spark Savings for USDT without asking users to bridge back to Ethereum, swap into another stablecoin or navigate multiple versions of USDT. Users can stay in the asset they already hold while accessing the same Spark Savings infrastructure available across supported stablecoins.

Why integrate spUSDT on Arbitrum

spUSDT is Spark's ERC-4626 USDT savings vault. Deposit USDT0, receive spUSDT, a transferable savings token that represents your position in the vault while continuing to accrue yield.
Like Spark's existing USDC and USDS savings vaults on Arbitrum, spUSDT follows the same ERC-4626 design, giving integrators a consistent way to support savings across multiple stablecoins.

USDT0 (spUSDT) is designed to be simple to integrate and simple to use:

• No lockups, deposit and withdraw at any time

• Transferable and composable with other DeFi applications through the ERC-4626 standard

• Access to Spark's programmatic allocation framework, which coordinates capital across vetted DeFi venues.

• Earn sustainable yield without relying on temporary incentives

With USDT0 now supported, users can access Spark Savings directly from one of Arbitrum's most widely used stablecoins without changing assets first.

Completing the Arbitrum savings stack

With USDC, USDS, and now USDT0 supported, Spark Savings on Arbitrum now provides savings infrastructure representing over 90% of the network's stablecoin supply, according to defillama. That gives builders access to savings infrastructure across the stablecoins their users are most likely to already hold.

For users, that means staying in the stablecoin they already hold without bridging back to Ethereum or swapping into another asset just to access savings. For wallets, treasury platforms and DeFi applications, it means broader stablecoin coverage through a consistent integration model.

That matters because USDT remains the world’s largest stablecoin by supply, while Arbitrum has become one of the deepest ecosystems for stablecoin trading, derivatives, and on-chain payments. Bringing Spark Savings to USDT0 expands that coverage, making it easier for builders to offer sustainable savings across the stablecoins their users already hold.

Whatever stablecoin you're already holding or trading with on Arbitrum, there's now a Spark vault for it.

Building on Arbitrum?

Whether you're building a wallet, treasury platform or DeFi application, Spark Savings can help make your business programmable by making it easy to offer savings across the three largest stablecoins on Arbitrum.

Talk to the Spark team to learn how Spark Savings can fit into your product. sarah@phoenixlabs.dev

Stablecoins Are Becoming Financial Ecosystems

For much of the last decade, stablecoins competed primarily on issuance, accessibility and adoption. Success depended on exchange listings, regulatory clarity and network effects.

Today, that competitive landscape is changing.

Financial platforms are increasingly building ecosystems around stablecoins rather than simply issuing digital dollars. The objective is no longer just to create a stablecoin, but to build a portfolio of financial products that encourage users, capital and liquidity to remain within that ecosystem over the long term. 

The Global Dollar Network is a good example of that shift. Rather than building another standalone stablecoin, Robinhood, Kraken, Paxos, Galaxy Digital, OKX, Bullish, Nuvei and other members are collaborating around a shared ecosystem designed to support a growing range of financial products and distribution channels. The Robinhood Earn launch extends that ecosystem directly to millions of retail users, demonstrating how stablecoin-powered financial products are beginning to move beyond crypto-native participants into mainstream financial platforms. 

Spark is already seeing this transition first hand. Through its work across PayPal's PYUSD ecosystem, Coinbase's USDC lending infrastructure, the Robinhood Earn (USDG) product and capital-efficient stablecoin liquidity through Uniswap, the same trend is emerging repeatedly: financial platforms are investing beyond stablecoin issuance towards the liquidity, credit and capital coordination required to support long-term ecosystem growth 

Viewed together, these are not isolated integrations. They demonstrate a broader market transition where competitive advantage increasingly shifts from issuing a stablecoin to building the strongest financial ecosystem around it.

The Financial Operating Model Becomes the Competitive Advantage 

As these ecosystems mature, customer experience increasingly depends on the quality of the financial operating model behind them. Capital must move efficiently between institutional investors, financial platforms and on-chain markets. Liquidity must remain available through periods of both growth and redemption. Capital allocation must balance yield generation with liquidity, redemption performance and institutional risk management.

Distribution creates adoption. The coordination of capital, liquidity and risk determines whether those products can scale. This is where specialist providers such as Spark contribute differentiated capabilities. Rather than building every capability internally, modern stablecoin ecosystems are increasingly composed of specialist providers, each contributing expertise across issuance, custody, liquidity, lending, settlement and capital allocation. By leveraging established custody, vault and settlement infrastructure, modern financial operating models can deliver scalable yield, efficient liquidity and institutional-grade resilience without requiring every participant to build the underlying capabilities themselves.

Unlike traditional yield products that compete primarily on APY, Spark competes on capital efficiency, liquidity, redemption performance and institutional resilience. Yield is the outcome of a more efficient financial operating model, not the objective in isolation. 

How Spark Creates Financial Utility 

Rather than issuing the stablecoin, operating the vault or owning the customer relationship, Spark's role begins once capital is allocated to the Spark market.

Through the Spark Liquidity Layer, Spark coordinates capital within a robust governance and risk framework. Governance defines the risk parameters, while the Spark Liquidity Layer applies allocation intelligence to coordinate capital across approved opportunities, including lending markets, Liquidity and Yield as a Service (LaaS), and capital-efficient liquidity strategies. Rather than leaving capital static within a single market, Spark continuously allocates capital to maximise financial utility while balancing liquidity, redemption performance and institutional-grade risk management. 

This approach allows capital within this framework to support multiple forms of on-chain financial activity while maintaining the liquidity, redemption performance and institutional-grade risk management expected by Robinhood's customers. As new governance-approved allocation strategies are introduced, the Spark Liquidity Layer can intelligently allocate capital towards the most efficient opportunities within its defined risk framework, increasing the financial utility of the USDG ecosystem without changing the customer experience. 

Spark's approach differs from many existing yield frameworks because it is not dependent on a single venue or strategy. Instead, the Spark Liquidity Layer coordinates capital across multiple governance approved allocation strategies within a predefined risk framework, allowing capital to move as market conditions evolve.

This creates several structural advantages:

• Native USDS minting reduces funding costs compared with sourcing liquidity externally. 

• Capital can be reallocated across multiple approved strategies rather than remaining constrained within a single protocol.

• Existing liquidity buffers and reserve infrastructure support efficient customer redemptions. 

• Spark's five-layer loss absorption framework provides additional resilience beyond the underlying strategy itself.

Rather than optimising for the highest headline APY, Spark optimises for long-term capital efficiency, liquidity, financial utility and resilience across the ecosystem. Sustainable yield is the outcome of that operating model, not the objective in isolation.

Looking Beyond Robinhood

Robinhood represents an important milestone, but it is only one example of a much broader market transition.

Alongside Robinhood, companies including Stripe and Deel are embedding stablecoins into mainstream financial products, while financial institutions such as JPMorgan, Standard Chartered, DBS, Société Générale, BBVA and others are actively investing in tokenised deposits, stablecoin infrastructure and on-chain settlement. The direction of travel is becoming increasingly clear: financial institutions are no longer asking whether stablecoins will become part of financial infrastructure, but how they can build products and ecosystems around them. The result will not be a handful of dominant stablecoins, but an increasingly connected network of financial ecosystems competing for capital, liquidity and utility. 

As the number of issuers and proprietary stablecoin ecosystems grows, particularly following regulatory developments such as the GENIUS Act, the challenge shifts from creating individual stablecoins to creating liquidity, financial utility and interoperability between them. Capital, liquidity and financial utility cannot remain isolated within individual ecosystems. They need to move efficiently between financial platforms, institutional markets and, increasingly, between stablecoin ecosystems themselves without recreating the fragmented liquidity and bridge-dependent architecture that has historically limited institutional adoption.

This is the problem Spark is designed to solve. Rather than replacing existing issuers or infrastructure providers, Spark provides the allocation intelligence that coordinates capital across governance-approved strategies within a defined risk framework. By integrating with regulated issuers, established custody providers, lending markets and liquidity venues, Spark enables capital to move efficiently across approved opportunities while supporting liquidity, redemption capabilities and institutional-grade risk management. 

USDG becomes another ecosystem connected through that operating model. Alongside integrations supporting PYUSD, USDC and capital-efficient liquidity through Uniswap, Spark is building a repeatable intelligence layer capable of increasing financial utility across multiple stablecoin ecosystems. Stablecoin-to-stablecoin liquidity is one example of that broader vision. As more ecosystems emerge, Spark's allocation intelligence can coordinate liquidity across them, helping capital move more efficiently while USDS provides the depth and liquidity required to support those markets.

Robinhood's Earn launch is another important proof point, not simply because it introduces another savings product, but because it demonstrates where financial markets are heading. As more financial platforms build proprietary stablecoin ecosystems, the intelligence coordinating capital, liquidity and risk will increasingly determine which ecosystems attract capital, create financial utility and scale over the long term. Spark is building that intelligence layer for the next generation of stablecoin powered financial products.

Everyone is focused on launching stablecoins:

• PayPal launched PYUSD.

• Ripple launched RLUSD. 

• Revolut, Deel and Robinhood are all exploring stablecoin initiatives or related infrastructure. 

• In Europe, a consortium of major banks including ING, BBVA and BNP Paribas is working towards a regulated euro stablecoin. 

• In Japan, MUFG, Mizuho and SMBC are exploring stablecoin initiatives of their own. 

• Visa, Mastercard and Stripe are investing heavily in stablecoin infrastructure. 

The market is preparing for more issuers. The next wave of stablecoin adoption will not be driven by a single issuer, it will be driven by an ecosystem of issuers of banks, fintechs, payment networks, exchanges and protocols. The question is no longer whether more stablecoins will exist. 

The question is: What happens when there are hundreds of them?

Because the challenge facing stablecoins is no longer issuance. The challenge is building the liquidity and exchange infrastructure required for a multi-issuer stablecoin economy.

Stablecoins have quietly become one of the fastest-growing settlement layers in the digital economy. According to Chainalysis, stablecoins processed more than $28 trillion in economic transaction volume during 2025. They are no longer simply a crypto product, they are becoming critical financial infrastructure. 

The growth of global value transfer is not slowing down, it’s actually accelerating. J.P. Morgan projects global cross-border payment flows will grow from approximately $194.6 trillion in 2025 to more than $320 trillion by 2032. SWIFT recently recorded the highest traffic volumes in its history, processing a record 68 million messages in a single day. At the same time, Bloomberg Intelligence projects annual stablecoin payment flows could reach $56.6 trillion by 2030. Banks are exploring digital currencies, and fintechs are building payment infrastructure around them.

The common theme is not competition, it’s scale. Money is moving faster, further and more frequently than ever before. The infrastructure supporting that movement must evolve to overcome the limitations of today's financial system. Spark, Uniswap and Sky have done just that.

This is not the launch of another liquidity pool. It is the first step towards building the exchange infrastructure a multi-issuer stablecoin economy will require. The stablecoin industry has spent years solving issuance. The next challenge is liquidity and exchange. 

The next evolution is building the FX Layer for stablecoins.

Why Today's Liquidity Infrastructure Doesn't Scale

The stablecoin industry has spent years solving issuance. Today, the challenge is no longer creating digital dollars, it’s creating the infrastructure that allows them to operate efficiently at scale. As the number of issuers grows, so do the demands placed on liquidity infrastructure, for example, A payments company may settle using PYUSD. A trading firm may hold RLUSD. A bank may issue its own regulated stablecoin. An exchange may integrate multiple stablecoins issued by different providers. Every new stablecoin creates another isolated liquidity ecosystem. Each brings new liquidity requirements, inventory management challenges and trading relationships. As the market scales, capital becomes increasingly fragmented across venues, making execution more difficult and expensive. 

The issue is not a lack of liquidity. It is a lack of coordination. Capital exists, but it is distributed across isolated pools, venues and ecosystems where it cannot be utilised efficiently. As the number of issuers grows, the challenge shifts from attracting liquidity to coordinating it.  

The problem is no longer attracting capital, it’s deploying that capital efficiently. Solving that problem requires rethinking how liquidity itself works, not as a passive asset that sits waiting for trades, but as programmable infrastructure capable of adapting to the needs of a rapidly expanding stablecoin economy.

What Changed? Liquidity Becomes Programmable

For most of DeFi's history, liquidity has been passive. Capital enters a pool, it waits, trades occur and the pool responds. That model helped create some of the most important financial infrastructure in crypto, but it was designed for a world where liquidity pools primarily acted as trading venues.

The future stablecoin economy requires something different. As issuers, assets and liquidity requirements multiply, liquidity itself increasingly becomes infrastructure. This is where Uniswap v4 changes the equation with the introduction of hooks. Built on one of DeFi's most battle-tested liquidity infrastructures, processing more than $4.4 trillion in cumulative trading volume, Uniswap provides the foundation for the next generation of programmable liquidity. Hooks allow custom logic to be embedded directly into the behaviour of a pool. The DualPool hook is one execution component within Spark's wider Shared Liquidity Layer (SLL), with Spark's governance-defined allocation frameworks determining how liquidity is coordinated across approved venues and products, while the hook provides the programmable execution path. At first glance, that sounds like a technical upgrade, but in reality, it represents a fundamental shift in how liquidity infrastructure can be designed.

For the first time, not only liquidity, but the rules governing liquidity and inventory management become programmable. Pools can operate according to predefined objectives rather than static (isolated) parameters alone. This means inventory can be managed more intelligently, with economic policies embedded directly into infrastructure. Liquidity can adapt as market conditions evolve. For example, consider a traditional stablecoin pool holding $100 million of liquidity. Whether that pool processes $1 million or $100 million of trading volume, much of the underlying inventory remains idle between transactions despite being required to support liquidity.

Programmable liquidity introduces a different model. Rather than treating liquidity as static / idle inventory, hooks create the potential for that capital to remain productive whilst continuing to support liquidity and execution. In practice, this means liquidity no longer sits idle waiting for trades. When capital isn't actively required for market execution, Spark can coordinate it across governance-approved products, liquidity venues and deployment strategies within the wider Spark ecosystem, with the DualPool hook making liquidity available to the market the moment it is required for execution.  

At this point, pools stop being passive venues, they become systems themselves. The significance is not any individual feature, the significance is that liquidity itself becomes programmable. And once liquidity becomes programmable, a new question emerges:

How should programmable liquidity behave?

The Missing Piece: Coordination

Programmable liquidity creates a new possibility, but it also creates a new challenge. Uniswap v4 solved one of the hardest problems in DeFi by making liquidity programmable. The next challenge is determining how that programmable liquidity should behave. What objectives should it optimise for? How should inventory be allocated? What happens during periods of market stress? What safeguards protect liquidity providers and users? 

The difficult challenge is governing programmable liquidity. This is where Spark enters the picture. This is precisely the problem Spark has spent years solving, coordinating billions of dollars of liquidity across savings products, lending markets and liquidity infrastructure while balancing capital efficiency, liquidity and risk.

Today, that expertise is applied through governance-defined allocation frameworks, risk parameters and one of the most extensive five-layer loss absorption frameworks in DeFi. Backed by the scale and resilience of the broader Sky ecosystem, Spark provides the coordination layer that allows programmable liquidity to operate efficiently at scale. 

This is not a theoretical exercise. Managing capital allocation, liquidity and risk across multiple products is already Spark's core competency. Programmable liquidity simply extends those same principles into market infrastructure itself. For institutions, treasuries and large allocators, the objective is simple: improve capital efficiency without compromising liquidity, execution or risk management. The opportunity is not to increase risk. It is to reduce inefficiency through better coordination of liquidity and inventory. 

For example, imagine a future where Robinhood launches a stablecoin for brokerage customers, Revolut launches a stablecoin for global payments, and PayPal continues expanding PYUSD. 

Each issuer wants users, distribution and settlement capabilities. Few want to spend years coordinating liquidity infrastructure, managing inventory across venues or bootstrapping market depth. Instead, they connect into shared liquidity infrastructure coordinated by Spark and powered by Uniswap.

The user continues interacting with the issuer's native stablecoin. The liquidity infrastructure operates beneath the surface. Capital can be allocated according to predefined objectives. Liquidity can be directed where demand is highest. Capital can remain productive while continuing to support market depth and execution.

The stablecoins remain visible. The infrastructure becomes invisible. The significance is not that liquidity can follow code. It is that liquidity can operate according to predefined objectives, risk parameters and inventory policies that respond to changing market conditions. That transforms liquidity from a passive asset into coordinated infrastructure.

The First Deployment

Every new piece of financial infrastructure starts with a first market. For the Stablecoin FX Layer, the initial deployment brings together USDS, USDT and PYUSD liquidity, with USDS providing the initial liquidity foundation across the network. Sky operates one of the largest stablecoin ecosystems in DeFi. With billions of dollars across USDS, DAI and associated savings infrastructure, it provides the scale and liquidity required to serve as the foundation for the deployment of the Stablecoin FX Layer. 

This scale matters. The future stablecoin economy will require deep, reliable liquidity capable of supporting growing numbers of users, institutions, payment providers and stablecoin issuers. Any shared liquidity framework requires a strong foundation, and USDS provides that foundation as the initial quoting asset within the network.

The first step is the migration of approximately $150 million of liquidity to Uniswap v4 across the USDS/USDT and USDS/PYUSD pools, representing one of the largest AMM liquidity migrations in DeFi. The immediate benefits are straightforward:

• Deeper liquidity.

• Lower execution costs.

• Reduced slippage.

• Improved market depth.

This makes USDS one of the easiest stablecoins to acquire, trade and integrate at scale. But the significance extends beyond a single pool. The migration establishes the first large-scale implementation of programmable liquidity coordinated through Spark and powered by Uniswap v4 for multiple pools.

It demonstrates how liquidity can be managed according to predefined objectives, inventory policies and risk frameworks rather than remaining entirely passive. Most importantly, it establishes the foundation for what comes next. A future where additional stablecoin ecosystems can connect into shared liquidity infrastructure rather than independently rebuilding liquidity from scratch.

Building the Stablecoin FX Layer

The long-term opportunity extends far beyond a single pool, a single stablecoin or a single issuer. The stablecoin industry is moving towards a future where banks, fintechs, payment providers, exchanges and protocols all operate their own digital currencies and stablecoin ecosystems. PayPal has already launched PYUSD. Ripple has launched RLUSD. Robinhood, Revolut, Deel and major banking consortiums across Europe and Asia are actively exploring stablecoin initiatives of their own.

The Stablecoin FX Layer introduces a different model.

Rather than every ecosystem independently rebuilding liquidity from scratch, issuers can connect into shared liquidity infrastructure built on programmable liquidity, coordinated inventory management and predefined risk frameworks. Removing the need to bootstrap independent liquidity networks allows issuers to focus on what differentiates them; products, distribution and users. They will be able to directly connect into a shared liquidity infrastructure coordinated by Spark and powered by Uniswap.

In this model, USDS provides the initial liquidity foundation for the network, while future implementations extend that shared liquidity infrastructure to additional issuers and stablecoin ecosystems. The issuer's stablecoin remains visible to the user. The liquidity infrastructure becomes invisible, and every additional issuer strengthens the network expanding available liquidity, improving market efficiency. This is where network effects begin to emerge.

At the same time, the market is increasingly converging around a second requirement: yield.

Fintechs, payment providers and financial institutions are not simply looking for digital dollars. They are increasingly looking for digital dollars capable of generating returns linked to short-term interest rates such as SOFR, while retaining the liquidity, accessibility and settlement capabilities users expect.

Historically, institutions have often faced a trade-off between liquidity and productivity. Capital could either remain liquid and available for use, or be deployed into productive strategies designed to generate returns. The next generation of stablecoin infrastructure aims to narrow that gap. The Spark, Uniswap and Sky programmable liquidity infrastructure creates the potential for capital to support liquidity, settlement and yield generation simultaneously within predefined allocation frameworks and risk parameters. Rather than leaving inventory idle between transactions, future implementations may allow liquidity to remain productive while continuing to support market depth and execution.

The first step starts with the migration of approximately $150 million of liquidity across the USDS/USDT and USDS/PYUSD pools. The long-term vision is far bigger. Not another stablecoin, not another liquidity pool, but a shared FX and liquidity layer capable of connecting hundreds of stablecoin issuers through programmable infrastructure.

That is the infrastructure the next generation of digital finance will require.

Institutional capital is increasingly held in custody, often sitting idle as deploying it into on-chain credit markets remains operationally complex.

For large allocators, accessing DeFi often means managing positions across multiple protocols, coordinating across wallets, signers, and custody setups, manually rebalancing capital as conditions change, navigating liquidity constraints that may only become visible under stress, and assuming direct exposure to the risk of individual markets. 

At large scale, this introduces operational overhead, fragmented exposure, and uncertainty around access to capital when it matters most. In practice, capital can be efficient to deploy, but harder to manage and exit under real market conditions.

Spark is built for this constraint

This is not just an access problem, it is a structural one. Most on-chain systems are designed around individual markets, vaults, or pools, operating independently without coordination across venues or system-level liquidity management. 

Spark takes a different approach. It coordinates capital across multiple credit venues within a single system, using predefined parameters to govern allocation, liquidity conditions, and risk. Instead of requiring capital to be actively managed across protocols, Spark allows it to be deployed within a framework structured to respond within defined parameters as market conditions change.

A direct pathway from custody into on-chain credit

Spark Savings is now available via BitGo, creating a direct pathway from custody into on-chain credit markets. Through BitGo, capital can be deployed into Spark Savings Vaults, where it is allocated across multiple credit venues within a single, structured system. 

For holders of assets such as USDT, USDC and USDS, this enables direct participation in on-chain credit markets without moving capital across multiple platforms or managing fragmented positions. 

Most on-chain credit today is accessed through individual lending markets, curated vault strategies, or credit pools. In each case, capital is deployed into a single structure, creating dependency on that market’s utilization, available liquidity, and pricing conditions and risk exposure.

Spark reduces this dependency by deploying capital across multiple venues and enabling capital to be reallocated within predefined parameters as market conditions evolve, rather than remaining fixed within a single pool, market, or curated strategy.

Designed for access to capital under stress

Spark is designed to maintain access to capital under these conditions, as market utilization increases. Spark Savings Vaults maintain substantial liquidity buffers and operate within predefined utilization and rate limits to reduce the likelihood of liquidity becoming constrained in highly utilized markets. This is intended to support immediate processing for most withdrawals, rather than making access fully dependent on market utilization at the time of exit. 

Exceptionally large redemptions are handled through structured liquidity routing, supported by additional system-level liquidity within the Sky ecosystem. This enables capital to be reallocated across venues and reduces dependence on single-market liquidity, limiting the conditions where capital becomes constrained in fully utilized markets.

Risk is structured at the system level

In most on-chain systems, risk is taken at the level of a single market, vault, or pool. Spark shifts this to a system level allocation and risk framework. Capital is allocated across multiple venues using predefined parameters covering exposure limits and liquidity conditions. This means capital is not passively exposed to the conditions of one venue, but instead is distributed and adjusted within defined bounds, limiting concentration in highly utilized or constrained markets and reducing dependency on any single source of liquidity.

Layered capital protection

At scale, the key question is not only how capital is deployed, but how it is protected under stress. 

A defining feature of Spark is its layered capital protection model, designed to absorb losses across multiple layers of capital within the system before they propagate toward user deposits. Rather than exposing capital directly to the outcomes of any single market or pool, Spark structures risk across multiple layers of capital designed to absorb losses sequentially under stress.

1. Prime Agent Risk Capital

Spark activities operate against multiple layers of dedicated risk capital, including internal junior capital, external junior capital, and external senior risk capital structured to absorb losses before broader system-level recapitalization mechanisms are engaged. These capital layers are designed to absorb losses within the system under stress before losses propagate further across the broader capital structure.

2. Surplus Buffer

Beyond Prime-level risk capital, Sky system surplus accumulated through protocol activity functions as an additional layer of loss absorption across the broader ecosystem. These surplus buffers are designed to absorb losses in more severe scenarios following the exhaustion of Prime-level risk capital and before broader recapitalization mechanisms are engaged.

3. Genesis Capital Backstop and System-Level Recapitalization

The updated Sky framework also introduces additional ecosystem-level backstop capital and broader recapitalization mechanisms designed to support system stability during severe stress events. If losses exceed Prime-level risk capital and surplus buffers, additional system-level mechanisms can be activated through governance to contain and absorb further stress. These mechanisms allow capital to be reallocated across the broader system and, where necessary, recapitalization actions to be taken to support broader system stability. 

Certain components of this framework, including the Genesis Capital Backstop, reflect pending governance updates at the time of writing.

4. Final System Resolution Layer

Only after all prior layers of risk capital, surplus buffers, and recapitalization mechanisms are exhausted would losses propagate further across broader USDS exposure within the Sky ecosystem. At this stage, USDS represents the final layer of capital within the broader Sky system. This reflects a shared ecosystem-level capital structure, where losses are absorbed across the wider Sky ecosystem rather than remaining isolated within a single vault, market, or product, before propagating further toward user deposits. 

This creates a clear loss hierarchy, where multiple layers of capital are structured to absorb losses sequentially before losses would propagate further toward user deposits.

Losses are absorbed sequentially across layers before impacting user capital.

Transparency and Risk Assessment

Spark Savings is supported by independent risk assessments from Credora, a leading crypto-native risk ratings provider. These ratings provide institutional counterparties with a third-party evaluation of vault safety, capital structure, and risk management standards.

Full reports are available via the Spark App and Credora.

Looking forward

The key constraint in scaling institutional capital on-chain is no longer simply access to yield, but reliable access to capital under real conditions. With existing distribution across leading wallets, exchanges, and institutional platforms such as Galaxy (NYSE: GLXY), Nexo, OKX, Binance Wallet, and Zerion, the integration with BitGo now opens a direct pathway for custodial capital to access on-chain credit markets through a single structured system.

Spark differentiates, not only how capital is allocated, but in how risk and loss absorption are structured across the broader system. Spark is built around a layered capital structure, where multiple independent sources of capital absorb risk before it reaches user deposits. This creates a level of protection and capital resilience that extends beyond single-market or single-vault models. 

As on-chain infrastructure has evolved, the ability to enter, manage, and exit positions reliably, particularly under stress, will define how institutional capital moves on-chain. 

Spark is designed to support this shift.

Spark is now available via BitGo institutional wallets.

Spark’s architecture is designed differently: constrained capital movement, explicit loss absorption layers, programmatic liquidity management, and bounded risk at every layer of the system.

Over the past year, Spark has expanded the security architecture across Spark Savings, SparkLend, and the Spark Liquidity Layer. This post explains how the system is structured today, how losses would be absorbed under stress, and the additional mechanisms currently being implemented across the broader Sky ecosystem.

Spark continues to evolve its security and risk framework. This post describes the current Sky loss absorption waterfall and how losses are progressively absorbed across the protocol's layered security architecture.

Spark Savings

Spark Savings is a suite of non-custodial savings vaults. Users deposit stablecoins, USDT, USDC, USDS and PYUSD into permissionless vaults designed around coordinated liquidity and transparent capital allocation.

Capital Structure and Seniority

Spark Savings operates within the broader Sky allocation framework. When users deposit stablecoins into Spark Savings vaults, Spark borrows an equivalent amount of USDS from Sky through the Allocation System Primitive* and coordinates that capital across approved liquidity venues and credit markets via the Spark Liquidity Layer.

All USD-denominated Spark Savings deposits are backed 1:1 by USDS. For each unit of stablecoin deposited, an equivalent unit of USDS is maintained within the Spark Liquidity Layer to satisfy redemptions. Spark Savings depositors share the same seniority as USDS holders within the broader Sky ecosystem. Losses are designed to be absorbed across the Sky Surplus Buffer, the Sky Protocol-owned capital reserves, the SKY Token backstop, and other protocol defined backstop facilities before propagating across broader Spark Savings exposure.

The Loss Absorption Waterfall

Spark Savings operates within a protocol-defined loss absorption framework designed to progressively distribute losses across multiple layers of risk capital and recapitalization mechanisms before losses propagate across broader Spark Savings depositor exposure.

The updated waterfall introduces the Genesis Capital Backstop as a distinct layer preceding the SKY Token Backstop, further expanding the system’s loss absorption capacity before losses would propagate across broader USDS exposure.

Layer 1: Prime Agent Risk Capital

The first layer of loss absorption sits at the Prime level and consists of three distinct sub-layers of internal and external risk capital allocated against Spark’s activities.

1. Internal Junior Risk Capital (IJRC) Spark’s treasury capital held against risk-weighted allocations. Spark absorbs losses first through the ‘Tip JRC’ mechanism before external junior capital is affected.

2. External Junior Risk Capital (EJRC) Additional junior capital sourced from other ecosystem participants, designed to absorb losses alongside remaining IJRC once the Tip JRC threshold is breached.

3. External Senior Risk Capital (srUSDS) A planned external senior risk capital layer designed to absorb losses only after all junior risk capital has been exhausted. This structure is conceptually similar to Aave Umbrella, though Spark’s framework additionally incorporates dedicated internal and external junior risk capital layers that absorb losses prior to senior capital exposure.

Layer 2: Surplus Buffer

After all Prime Agent Risk Capital has been exhausted, losses progress to the Sky Protocol Surplus Buffer. The Surplus Buffer consists of protocol surplus accumulated through stability fees, liquidation penalties, and other system revenues retained within Sky Core. This capital functions as Internal Senior Risk Capital and is designed to absorb losses before any recapitalization mechanisms are activated.

Unlike Prime-level risk capital, which is allocated directly against specific activities and exposures, the Surplus Buffer operates at the system level across the broader Sky ecosystem.

Layer 3: Genesis Capital Backstop
The Genesis Capital Backstop introduces an additional ecosystem-level layer of loss absorption positioned between the Surplus Buffer and the SKY Token Backstop.

This layer is composed of Aggregate Backstop Capital: excess Genesis Capital held across participating Sky ecosystem entities, including Spark, Grove, Keel, Skybase, and other Genesis Agents, above their Allocated Genesis Capital requirements.

The Genesis Capital Backstop is designed to expand the system’s dedicated recapitalization capacity before reliance on SKY token issuance and is activated only under predefined protocol conditions during a SKY Backstop Event.

Layer 4: SKY Token Backstop
If all prior layers of risk capital and surplus buffers are exhausted, the Sky Protocol can initiate the SKY Token Backstop to recapitalize the system and address residual bad debt.

During an active backstop event, the protocol can generate and distribute additional SKY tokens as part of the recapitalization process. This mechanism is designed to provide a scalable, governance controlled source of recapitalization capacity during extreme system stress scenarios.

The SKY Token Backstop operates as a protocol-level recapitalization mechanism rather than capital pre-allocated to any individual Prime, venue, or market exposure.

Layer 5: Final System Resolution Layer
As a final system-level resolution mechanism, residual deficits may ultimately be socialized across broader USDS exposure only after all protocol defined risk capital, surplus buffers, and recapitalization mechanisms have been exhausted.

Under this framework, Sky can adjust the USDS target price below $1 in order to resolve any remaining system deficit. This mechanism is designed exclusively for extreme tail-risk scenarios in which the SKY Token Backstop itself becomes non-functional or reaches its predefined issuance limits before the system can be fully recapitalized.

Under the current framework, affected USDS holders would also receive SKY token distributions as part of the broader recapitalization and resolution process.

This layer represents the final stage of loss resolution across the broader Sky ecosystem.

Liquidity Architecture

Spark Savings is designed around coordinated liquidity management rather than utilization-driven liquidity rationing. The Spark Liquidity Layer coordinates inventory across Spark Savings, SparkLend, the Sky PSM, and other approved venues in order to support predictable redemption capacity under changing market conditions.

Spark Savings vaults maintain substantial available liquidity buffers. The Spark Savings USDT vault currently maintains an immediately available liquidity buffer exceeding $10 million USDT for redemptions, while the Spark Savings USDC vault has access to billions of dollars of redemption capacity through integration with the Sky PSM.

At the vault level, Spark Savings contracts maintain dedicated liquidity buffers for standard withdrawal activity, allowing typical withdrawals to be fulfilled atomically on-chain.

For larger withdrawals, Spark provides an asynchronous liquidity intents mechanism. Users can submit signed withdrawal requests for any amount, with the Spark Liquidity Layer coordinating liquidity movement and settlement across the broader system. Under normal operating conditions, large withdrawal requests are typically fulfilled in under one minute within approximately five Ethereum blocks.

This architecture is intended to reduce dependency on static idle liquidity by coordinating capital dynamically across the broader Spark and Sky ecosystem.

Transparency and Risk Monitoring
Spark Savings operates with real-time transparency into backing assets, allocation activity, and liquidity conditions across the broader Spark and Sky ecosystem. Live system data is available through data.spark.fi, info.skyeco.com, and the Spark App, providing visibility into vault balances, allocation activity, liquidity buffers, and broader protocol metrics.

Spark Saving Vaults are also independently assessed by Credora, with full risk reports accessible directly within the Spark App as well as the Credora website. Spark is engaging with additional independent institutional risk and ratings providers to expand third-party assessment and due diligence coverage for institutional users.

Recovery Modes and Stress Events

During periods of severe market stress or potential system impairment, Spark can place Savings vaults into recovery mode as part of broader risk mitigation procedures. Recovery mode allows withdrawal coordination mechanisms to be temporarily adjusted in order to support orderly liquidity management and equitable treatment across all participants during extreme conditions.

These controls are designed to operate consistently with the broader Sky loss resolution framework applying the principle of equitable loss socialization across the system.

SparkLend

SparkLend is Spark’s permissionless money market, designed around bounded risk, constrained collateral exposure, and layered liquidity controls. The protocol operates with a deliberately narrow collateral set, multi-source oracle pricing, strict rate limits, and protocol level loss absorption mechanisms intended to reduce dependency on any single market, issuer, liquidity venue, or operational component.

The rsETH market disruption earlier this year reinforced the importance of this layered approach. SparkLend’s risk architecture is designed so that failures in any individual component, including oracle infrastructure, collateral issuers, liquidators, or secondary market liquidity, do not automatically propagate into system wide bad debt.

Restricted Collateral Set

SparkLend maintains a deliberately narrow collateral universe designed to reduce dependency on fragmented liquidity, complex redemption assumptions, and correlated market stress across long-tail assets.

ETH e-mode exposure is limited to assets with comparatively deeper liquidity and more established market structure, currently only wstETH. Spark is also in the process of fully removing BTC e-mode exposure through a publicly communicated governance deprecation process, currently scheduled for June 8, 2026. 

This approach is intended to prioritize predictable liquidation behavior, stronger market depth during stress events, and simpler dependency assumptions across collateral markets rather than maximizing collateral breadth or leverage opportunities.

Minimal Rehypothecation

Collateral supplied to SparkLend reserves remains within the reserve system and is not redeployed into external yield strategies or secondary leverage loops. This design reduces dependency on external liquidity conditions, counterparty exposure, and recursive leverage structures that can amplify stress during periods of market volatility.

Rate Limits

Every cross-module capital flow into and out of SparkLend is rate-limited at the smart-contract level. Deposits, withdrawals, cross-chain bridging, and PSM swaps each operate within predefined throughput constraints designed to bound capital movement under changing market conditions.

Rather than allowing unlimited capital to move instantly between markets or infrastructure layers, these controls enforce explicit limits on how much liquidity can enter or leave specific pathways over a defined period of time.

On top of these controls, Spark’s allocation framework enforces per market debt ceilings alongside inventory minimum and maximum bands across supported venues. Together, these mechanisms are designed to constrain how much capital can move through any individual route or operational pathway over a given period of time, reducing dependency on instantaneous liquidity and limiting the impact of localized stress events.

Three-Oracle Median

SparkLend pricing is aggregated using a multi-source oracle architecture drawing from RedStone, Chainlink, and Chronicle. When all three oracles return valid, non-stale values, the median price is used. When two valid sources are available, their average is used, with additional fallback logic available under degraded conditions.

This architecture is designed to reduce dependency on any single oracle provider or pricing source when determining collateral values and liquidation thresholds, helping mitigate risks associated with oracle outages, misconfigurations, stale pricing, or transient market anomalies.

For selected assets, Spark also incorporates TWAP-based and exchange-rate pricing mechanisms as fallback pricing systems designed to maintain pricing continuity under degraded oracle conditions or periods of market stress and liquidity fragmentation.

Killswitch Oracle for Pegged Assets

For collateral assets that rely on exchange-rate or redemption-based pricing assumptions, including wstETH, weETH, cbBTC, WBTC, and LBTC, Spark incorporates an additional peg-ratio oracle designed to independently monitor divergence between market pricing and underlying asset value.

The killswitch continuously compares an asset’s observed market price against its exchange-rate reference. When deviations breach predefined per-asset thresholds, SparkLend can halt new borrowing activity against the affected collateral type.

This mechanism is designed to prevent users from posting collateral experiencing structural pricing dislocation at stale face-value assumptions and extracting healthy debt against impaired collateral during periods of market stress or liquidity fragmentation.

The peg-ratio oracle operates independently from SparkLend’s primary multi-oracle pricing system, providing an additional layer of protection against oracle drift, redemption impairment, or severe market dislocation.

Programmatic Liquidity Injection

SparkLend’s liquidity architecture is designed around coordinated inventory management rather than static liquidity pools. Through the Spark Liquidity Layer, USDS, USDC, and USDT liquidity can be programmatically reallocated into and out of SparkLend based on utilization, target borrow conditions, available system inventory, and broader allocation constraints across approved venues.

When utilization increases, the Spark Liquidity Layer can deploy additional idle liquidity into SparkLend in order to support borrowing demand, withdrawals, and liquidation activity. If liquidity conditions or allocation opportunities elsewhere in the system become more favorable, idle capital can rotate across other approved venues within Spark’s broader allocation framework.

This is a core property of Spark’s architecture: Spark is the largest depositor in its own market, allowing liquidity to respond programmatically to system demand rather than being constrained entirely by passive depositor behavior or utilization-driven liquidity rationing.

Planned Improvements

Continuous Collateral Risk Review

Spark is expanding collateral risk assessment into a continuous review framework covering not only each asset’s standalone risk profile, but also its broader dependency structure, including issuers, custodians, oracle systems, secondary market liquidity, and redemption mechanisms.

The objective is to continuously reassess how collateral behaves under changing market structure, liquidity conditions, and cross-system dependencies rather than treating risk parameters as static.

Graduated Oracle Design

Work is underway on a more graduated oracle framework that defaults to hard-coded or exchange-rate pricing under normal conditions and shifts toward market pricing only when sustained deviations are observed.

The objective is to preserve protection against flash crashes, oracle wicks, and transient liquidity dislocations while enabling faster automated responses to genuine structural depegs or redemption impairment events.

This framework is designed to complement the existing killswitch system rather than replace it, introducing a more adaptive response layer between short-term market volatility and severe collateral failure scenarios.

Risk Steward Framework

Spark is implementing a bounded risk steward framework designed to accelerate risk parameter updates during periods of market stress or rapidly changing liquidity conditions.

Under this model, a predefined set of risk controls, including LTV reductions, supply cap adjustments, and rate model changes, can be updated within tightly constrained operational boundaries without waiting for the full governance spell process.

The framework is designed to enable faster responses to time sensitive risk events while keeping all steward actions constrained by governance defined parameters and subject to ongoing oversight from Spark and Sky governance.

Spark Isolated Markets

Pooled lending markets provide strong capital efficiency and user experience benefits, but they also introduce shared risk across participants within the same liquidity environment. For collateral with elevated, unique, or chain-specific risk characteristics, Spark supports isolated markets through Morpho-based infrastructure.

Isolated lending allows risk to be priced more precisely for each collateral type and enables specific collateral markets to be adjusted, deprecated, or removed without affecting the broader pool.

Spark also uses isolated markets as the preferred framework for non-Ethereum on-chain lending. This enables integration with exchanges, custodians, and fintech distribution partners without requiring Spark to deploy and maintain fully replicated infrastructure across every chain environment.

Going forward, Spark intends to prioritize isolated markets with multi-source oracle resilience rather than dependency on any single oracle provider and expand native Spark App support for participating in lending markets across additional chains.

The Spark Liquidity Layer

The Spark Liquidity Layer (SLL) is a non-custodial capital allocation system operating across approved DeFi, CeFi, and TradFi liquidity venues. The system has operated continuously since November 2024.

The core security property of the SLL is constraint by design. All allocation venues must be pre-approved through governance and operate within predefined rate limits and allocation constraints. Automation wallets can only move capital between approved venues and within governance-defined operational boundaries. This is designed to constrain how quickly capital can move from any individual venue and cause allocation changes to occur gradually rather than reflexively during periods of market stress. 

The SLL is explicitly designed around constrained automation. Even under the assumption that an automation wallet becomes compromised, capital movement remains restricted by predefined venue whitelists, throughput limits, and allocation controls. The framework is designed so no single operational component can independently create unbounded system exposure.

Spark has already reduced or deprecated exposure across multiple external markets as part of a broader derisking effort and intends to remain proactive as liquidity conditions, market structure, and risk-adjusted opportunities evolve. The protocol is also developing more adaptive monitoring and automation systems designed to detect broader market stress events and coordinate defensive risk responses across the allocation framework.

Bridges

The Sky and Spark ecosystem currently operates two live cross-chain bridge systems designed around constrained trust assumptions, redundancy, and bounded cross-chain risk exposure.

SkyLink

SkyLink is the official Sky governance and token bridge, responsible for cross-chain Sky governance messaging alongside cross-chain USDS transfers. The governance bridge currently operates with a 4-of-7 DVN configuration designed to provide diversified verification and redundancy across independent validation providers. The token bridge currently operates with a 2-of-2 DVN configuration, with planned upgrades.

SkyLink is currently deployed on Solana and Avalanche.

Spark Governance Bridge (Avalanche)

Spark operates a dedicated governance bridge supporting Spark Savings USDC on Avalanche. The bridge currently operates with a 2-of-2 DVN configuration and is expected to transition toward the broader SkyLink 4-of-7 verification model as part of ongoing bridge hardening efforts.

There is no associated token bridge connected to this system, and cross-chain capital exposure remains intentionally limited, currently approximately $2 million.

Conclusion

Spark’s security architecture is the product of deliberate system design rather than any individual mechanism or control. The loss absorption waterfall, constrained capital movement, oracle systems, liquidity coordination mechanisms, and bounded governance and risk frameworks are intended to operate as a cohesive stack, reducing dependency on any single market, oracle, venue, or operational component.

The objective is not to eliminate risk entirely, but to ensure that failures remain bounded, observable, and progressively absorbed rather than cascading uncontrollably across the system.

As Spark continues to expand across savings, lending, and liquidity coordination, the underlying design principle remains the same: scalable on-chain credit infrastructure requires predictable liquidity, transparent risk architecture, and constrained system behavior under stress.

This is not a shift in demand. It is a shift in how systems are required to handle capital.

Where Scale Changes the Dynamics

At smaller sizes:

• liquidity appears continuous

• rates are relatively stable

• execution is immediate

At larger sizes:

• Liquidity becomes conditional on utilization, timing, and the behavior of other participants, determining whether the system can absorb sizable movements. 

• Rates respond to allocation flows, adjusting with large inflows (diluting yield) and outflows (repricing as liquidity is freed to support withdrawals and rebalancing). 

• Execution depends on timing and structure. Entering too quickly can lead to slippage and rate declines, while exiting during periods of high utilisation constrains available liquidity and introduces delays. Routing also matters — poor execution paths can significantly impact outcomes. In one recent case, a $50M transaction resulted in a materially worse outcome than expected due to thin liquidity along the execution path and MEV dynamics. 

• What mechanisms exist to absorb stress and maintain system resilience under changing conditions.

The larger the position, the more its movement influences the system itself.

Beyond Yield: The Emergence of Execution as a Constraint

At early stages, markets are optimized around yield. Capital flows to the highest return, and systems are evaluated accordingly. At scale, a different constraint emerges. The key question becomes:

Can capital move through the system without distorting it?

This introduces a new set of considerations:

• depth of available liquidity

• responsiveness of rates to large flows

• ability to enter and exit without fragmentation

• Loss absorption mechanics

Yield remains relevant, but it is no longer sufficient as a decision variable on its own.

Where Systems Are Being Tested

2026 has already seen over $450M lost across dozens of incidents. The important point is not the number, it’s where those failures are coming from. 

They are not concentrated in one area. They are happening across control layers, pricing, and execution.

A few examples:

• Key and permission compromise
  In the Step Finance incident, attackers gained access to privileged internal systems rather than exploiting contracts directly, draining around $40M. The failure wasn’t code, it was control mechanisms.

• Minting and logic failure
  In the Resolv case, around $80M of unbacked assets were minted due to missing constraints between issuance and collateral. The system allowed supply to expand beyond what it could support.

• Execution failure under liquidity constraints
  A $50M transaction routed through thin liquidity resulted in an outcome closer to $36k. No exploit occurred, but routing logic, liquidity depth, and MEV dynamics led to a catastrophic execution result.

• Oracle and pricing sensitivity
  Moonwell ($1.8M loss) and Aave’s CAPO misconfiguration ($27M liquidation impact) both highlight how reliance on specific pricing configurations can introduce instability when conditions shift.

Across these cases, the pattern is consistent. Systems are not failing because capital is leaving. They are being tested by how capital moves. The important element in many cases was that nothing was broken, but the outcome is still wrong.

What These Failures Point To

These are not isolated incidents. They point to a set of design requirements that become necessary as capital scales:

• Redundancy in critical inputs
  Reliance on a single pricing source creates fragility. In underlying lending markets, multiple oracle sources with validation and fallback mechanisms (such as TWAP) are used to reduce dependency on any one input.

• Defined constraints on issuance and allocation
  Systems must enforce limits on how capital is created and deployed, rather than relying on open-ended logic that can be pushed beyond safe bounds.

• Liquidity buffers and diversified deployment
  Capital cannot be fully utilised at all times. Maintaining buffers and spreading deployment across venues improves the system’s ability to accommodate withdrawals, without forcing reactive rebalancing.

• Execution-aware design
  Routing, liquidity depth, and transaction timing are not external concerns, they are part of the system itself.

At scale, these are not optimisations, but are reflected in how Spark Savings Vaults are designed to operate.

From Isolated Markets to Coordinated Systems

At scale, the problem is not just where capital is deployed, but how the system is designed to handle it. In isolated markets, liquidity is fragmented and reactive. Each venue operates independently, with utilization, pricing, and access determined locally.

As capital grows, this structure introduces friction:

• liquidity becomes unevenly distributed

• execution depends on navigating multiple venues

• access to capital becomes conditional rather than predictable

This is what drives the shift towards coordinated systems. Instead of deploying capital into a single venue, capital is structured across multiple environments, with allocation and access managed as part of the system itself.

In practice, this changes how the risks outlined earlier are handled:

• Liquidity is not concentrated in a single market
  Spark Savings Vaults deploy capital across different types of credit environments, which are selected and monitored against defined risk parameters and independent assessments, including on-chain lending markets and other structured strategies, rather than relying on a single source of liquidity. This reduces dependency on any one venue and limits the impact of local utilization spikes, pricing dislocations, or execution constraints.

• Access is supported by liquidity buffers
  Not all capital is deployed at once. Allocation operates within governance-defined parameters that set limits on how and where capital can be deployed, with a portion of liquidity intentionally retained to support withdrawals and reduce reliance on immediate rebalancing under changing conditions. This is complemented by system-level buffers, including protocol-level risk capital (Junior Risk Capital), designed to absorb losses within the system under defined conditions, alongside additional backstop capacity from the broader Sky ecosystem, strengthening the system’s ability to maintain resilience under changing conditions, including periods of increased withdrawal demand, without relying on reactive rebalancing or forced position adjustments.

• Allocation follows defined constraints
  Deployment is governed by parameters defined at the system level, setting limits on where and how capital can be allocated. This prevents unrestricted concentration in a single venue, while allowing allocation to adjust within those defined boundaries as conditions change.

• Governance enforced system behavior
  System parameters and allocation constraints are defined through governance-approved ‘spells’, with execution handled through established mechanisms (including multisig where required). This is reinforced by independent audits, third-party risk assessments, and fully transparent configuration and governance.

• Critical inputs are validated across multiple sources
  Pricing is not dependent on a single oracle. Where applicable, pricing relies on multiple feeds with fallback mechanisms (such as TWAP), reducing sensitivity to individual data points or misconfigurations.

• Execution is treated as part of the system
  Capital is not deployed or withdrawn through a single transaction against a single venue. Positions are managed across multiple venues, with adjustments and rebalancing occurring within defined constraints over time. This reduces dependence on any single pool or moment in time, limiting the impact of slippage, liquidity gaps, and timing when moving larger positions.

This does not remove dependency on underlying markets. It changes how capital interacts with them, reducing reliance on any single venue, pathway, or condition.

How Capital behavior Changes at Scale

At larger position sizes, capital is no longer optimized for yield in a single venue. Capital is structured across multiple venues, with a focus on maintaining access to liquidity, managing execution risk, and preserving flexibility under changing conditions. 

In practice, this means Spark positions are increasingly managed around:

Entry and exit are planned, not assumed. Deploying or withdrawing capital is no longer treated as a single action, but as a process that depends on liquidity, timing, and market conditions.

Execution becomes a constraint, not an afterthought. How capital moves, routing, timing, and venue selection becomes as important as where it is allocated. This is also why capital at scale tends to concentrate in highly liquid, well-established assets. Stablecoins and blue-chip collateral provide the depth, pricing reliability, and market integration required to support large movements without introducing additional execution risk. At size, asset selection is not just about return, it is about whether the market can support the position.

Positions are managed across venues over time rather than through single-point execution. Within Spark, capital is not deployed or adjusted through a single transaction against a single market. Instead, positions are maintained across multiple venues, with rebalancing and adjustments occurring as conditions change. This reduces reliance on any one pool or moment in time, and allows capital to move without requiring direct interaction with each underlying market.

This shifts the model from direct, execution-dependent interaction with individual markets to a system that manages allocation, execution, and capital movement across venues within defined constraints.

What $1B Represents

Spark’s USDT Savings Vault has recently surpassed $1B, with total capital across Spark Savings Vaults now exceeding $4.5B. At this level of scale, system behavior is no longer theoretical, it becomes visible in how capital moves through the system in practice. 

This is not just a milestone in growth. It is a point where system dynamics begin to change. At smaller scales, inefficiencies are harder to detect. Liquidity appears continuous, execution feels immediate, and withdrawal assumptions are rarely tested. At larger scales, these assumptions break down. Capital movements begin to influence the system itself. Liquidity becomes conditional on utilization, timing, and the behavior of other participants, determining whether the system can absorb sizable movements.

This is where differences between systems become more apparent. Not in headline yield or short-term incentives, but in how liquidity is maintained, how positions are adjusted, and how capital moves under real conditions.

$1B is not the ceiling. It is the point where allocation frameworks are tested, execution design becomes observable, and system constraints begin to define outcomes. At this stage, execution is no longer separate from the product, it becomes part of it. And the ability to manage it becomes the defining characteristic of a truly scalable system.

This is how contagion manifests in these systems: not through direct failure of assets, but through shared dependence on liquidity under stress.

Under normal conditions, liquidity appears abundant. Capital can be deployed and withdrawn with minimal friction, and utilization remains comfortably below its limits. Under stress, those assumptions break down. Liquidity becomes path dependent, shaped by the order and behavior of participants attempting to exit.

At scale, this introduces a different kind of risk. It is no longer sufficient to evaluate yield, collateral quality, or market size in isolation. The central question becomes whether capital can be accessed when it is most needed.

For allocators, this is not theoretical. It directly impacts position sizing, venue selection, and capital allocation strategy. It is the defining constraint of utilization-driven systems. The industry’s focus over the past cycle has been on efficiency: maximizing capital deployment, increasing utilization, and optimising yield. While effective in steady-state conditions, this approach reduces the amount of available liquidity in the system.

Liquidity buffers are what allow markets to absorb stress. Without them, even relatively contained shocks can lead to rapid liquidity exhaustion. When capital is fully deployed and utilization is maximised, there is little capacity to absorb large, simultaneous exit flows. Liquidity is not gradually reduced. It disappears entirely. 

Rather than treating liquidity as a passive pool that is continuously deployed, Spark is designed around liquidity as a resource structured to remain available across market conditions, including periods of stress. As detailed in Sam MacPherson’s overview of Spark’s security framework, this is implemented through a combination of:

• Accessible liquidity buffers and asynchronous withdrawal mechanisms

• Coordinated allocation across multiple venues

• Explicit exposure limits and risk parameters governing capital deployment 

• Governance-enforced constraints on capital movement

• Conservative collateral selection and minimal rehypothecation

• Multi-oracle pricing frameworks

• Robust cross-chain infrastructure and bridge security assumptions

• A multi-layered system of risk capital and loss absorption, spanning multiple independent backstop layers within the Sky ecosystem (as detailed in Sam MacPherson’s overview of Spark’s security framework) 

Risk at Spark is constrained through predefined parameters and exposures, which evolve as market conditions change.  

The objective is not to eliminate risk, which is neither realistic nor desirable in a functioning market. It is to ensure that risk is structured, contained, and absorbed within predefined parameters, rather than propagating uncontrollably through the system.

This distinction becomes critical under stress. 

In utilization-driven systems, liquidity is implicitly dependent on borrower behavior. Withdrawal capacity can collapse abruptly, and exit becomes a function of timing rather than entitlement. When multiple participants attempt to exit simultaneously, this dependency becomes a constraint.

In coordinated systems, liquidity is structured through predefined parameters. Buffers are designed to support demand, capital is distributed across venues, and risk exposure is managed within defined limits. Outflows are constrained to reduce the likelihood of reflexive cascades. Where losses occur, they are addressed through predefined layers of capital rather than transmitted directly to users.

This is not a marginal improvement in design. It reflects a fundamentally different approach to how liquidity is structured, accessed, and protected. 

Recent conditions have demonstrated how pressure materialises in utilization-driven systems. Liquidity becomes constrained, demand shifts across assets, and exit conditions deteriorate,  not because of a single failure point, but because of how liquidity is structured and accessed.

For allocators, the implication is clear.

Liquidity is not defined by conditions in normal markets. It is defined by what remains when those conditions no longer hold. Systems that optimize for utilization will continue to perform well in steady state. But under stress, they expose a structural constraint: liquidity is conditional, and exit is uncertain.

Systems designed with liquidity as a managed resource behave differently. They preserve access, absorb stress in layers, and avoid the reflexive dynamics that turn contained events into system-wide constraints.

As liquidity conditions become more volatile, the ability of systems to maintain access under stress is likely to become a more important differentiator.

Below is the Q1 2026 financial report.

1. Executive Summary

Spark closed Q1 2026 in a profitable position. The quarter was characterized by a shift in revenue composition, with distribution rewards emerging as the protocol’s largest net return contributor, reflecting the continued scaling of USDS distribution infrastructure across multiple chains and products. The Spark Liquidity Layer maintained disciplined capital allocation across a diversified venue set under tighter spread conditions, while SparkLend continued to support institutional-grade borrowing activity, including the expansion of its USDT Savings Vault, built on Spark’s allocation infrastructure. 

Q1 Financial Highlights

• Gross protocol returns: $31.5M (QoQ -31%) (aggregate returns across all protocol components) 

• Net protocol returns: $6.91M (QoQ -30%) (gross returns less cost of capital)

• Net protocol surplus: $3.46M (QoQ -47%) (gross returns less operating expenses)

• Spark Protocol treasury (end of quarter): $46.1M (QoQ +5.7%)

• SPK token buybacks: $986k (new program: capital returned via open-market purchases)

Overall, Q1 demonstrated the diversification and resilience of Spark’s protocol-level revenue streams. While unfavorable DeFi lending conditions compressed SLL spreads, Spark’s distribution business scaled meaningfully, with USDS well positioned as a scalable savings based return mechanism within the SKY ecosystem under precisely these market conditions. Spark remains well positioned to benefit from an eventual recovery in lending activity while continuing to grow its distribution footprint.

2. Product Line Performance

Spark comprises several components that generate protocol-level returns accrued to the treasury pursuant to governance-defined mechanisms.

These are (i) Spark Liquidity Layer (ii) distribution rewards (iii) SparkLend (iv) Treasury Management & Financial Operations.

Spark coordinates capital through these components via programmatic allocation, distribution, and lending infrastructure.

2.1 Spark Liquidity Layer (SLL)

The Spark Liquidity Layer is a smart-contract system in which assets are allocated in a programmatic manner into return-generating allocations across supported venues. Thanks to this system, the protocol may generate returns subject to market conditions, smart-contract execution, and governance-defined risk parameters.

Revenue model: The protocol captures net returns across allocated positions, including spread between lending rates and funding costs where applicable, subject to market conditions.

Q1 highlights: During Q1, the SLL operated across a broader and more diversified venue set, with an average allocated capital of $1.93B. A key focus of the quarter was over-collateralized crypto lending, both onchain and offchain through institutional counterparties. Alongside lending, allocations involving PYUSD across supported venues became the single largest deployment category at $13.1M in gross returns, reflecting the growth of Spark’s stablecoin infrastructure.

Spark Institutional Lending (Spark’s OTC lending structure) continued to scale during the quarter, generating $2.27M in gross returns with $150M deployed at quarter-end. Governance approved a $1B ceiling for this structure, reflecting confidence in the institutional custody framework and the quality of the underlying lending activity. This structure extends Spark’s capital coordination into custody-supported institutional credit markets beyond onchain venues. 

Spread compression was evident across the quarter, with the capture spread narrowing from 0.83% in January to 0.41% in March. This reflected softer DeFi lending conditions and rising Savings V2 borrow costs as Spark’s USDT savings product grew.

Under weak market conditions, Spark did not increase its risk profile in search of additional returns. Importantly, allocation parameters remained consistent despite spread compression. The SLL remained net-positive throughout the quarter.

KPIs:

• Average deployment: $1.93B

• Average APY: 5.8%

• Gross returns: $27.62M

• Net protocol returns: $3.05M

• Captured spread: 0.64%

2.2 Distribution rewards

Spark functions as a distribution layer within the SKY ecosystem, routing capital into Savings Vaults, allowing users to get exposure to USDS and the SKY savings rate. Distribution revenue reflects Spark’s role in facilitating access to these savings mechanisms, where returns originate from underlying balance sheet and allocation frameworks within the SKY ecosystem. 

Q1 highlights: Distribution rewards became the largest single contributor to Spark’s net protocol returns during Q1, surpassing net SLL revenue for the first time. This structural shift underscores the scalability of Spark’s distribution infrastructure, particularly under market conditions where lending spreads compress but demand for savings based deployment remains robust.

sUSDS generated $1.66M in distribution revenue, the largest single token contributor, followed by stakedUSDS (stUSDS) at $710k. sUSDC contributed $315k and spUSDT, reflecting the growth of the Spark USDT Savings Vault, contributed $145k in its first full quarter. Revenue grew from $894k in January to $1.27M in March, demonstrating continued month-over-month acceleration.

USDS is well positioned as a scalable savings based return mechanism under unfavorable market conditions: as DeFi lending yields compress, users increasingly seek predictable savings exposure rather than variable lending returns, and Spark’s distribution channels benefit directly from this dynamic. The growth of the USDT Savings Vault in particular demonstrates Spark’s ability to expand its distribution footprint into new stablecoin denominations.

KPIs:

• Distributed supply: $4.5B

• Q1 revenue: $3.31M

2.3 SparkLend

SparkLend is a core lending protocol within the Spark ecosystem, operating as one of the largest and secure lending platforms in DeFi (DefiLlama), with only blue-chip collateral. It supports institutional borrowing activity, with liquidity supplied through the SLL as the governance-approved protocol mechanism.

Revenue model: Spark collects a reserve factor on interest accrued by borrowers.

Q1 highlights: During Q1, SparkLend continued to operate as one of the largest money markets in DeFi, with the SLL allocating $688M into SparkLend markets at quarter-end across DAI, USDS, USDT, pyUSD, USDC, and WETH.

A key development during the quarter was the continued growth of the Spark USDT Savings Vault. SparkLend USDT balances reached $285M by March 31, establishing SparkLend as one of the largest USDT lending venues on Ethereum. This reflects the integration of USDT-denominated savings flows into Spark’s lending infrastructure, supporting both borrowing demand and broader distribution growth.

Activity and utilization metrics reflected broader DeFi market softness, with reserve factor revenue declining to $156k from $215k in Q4.

KPIs:

• SparkLend SLL deployment (end of quarter): $688M

• Q1 revenue (reserve factor on yield, excluding SLL): $156k

2.4 Treasury Management & Financial Operations

Spark’s treasury represents the protocol’s operational capital. It both pays for the operational expenses as well as acts as junior capital required by SKY to fulfill the risk-required capital needs for accessing the SKY credit line. It serves as a core component of Spark’s risk framework, providing capital support and absorbing potential volatility within the system. 

Revenue model: The protocol may generate returns on treasury assets through SKY’s savings rate and other financial operations.

Q1 highlights: During Q1, the treasury generated $354k in net positive returns, with returns from USDS denominated savings exposure on the treasury balance partially offset by negative returns from volatile asset exposure.

Additionally, the protocol initiated its first SPK token buyback program during Q1, allocating $986k in USDS to open-market purchases of SPK tokens. This represents Spark’s first direct capital return mechanism and reflects governance confidence in the protocol’s financial position and long-term value creation.

3. Consolidated P&L

Summary of Spark’s total revenues, costs, and net results across all protocol components for the quarter. It combines returns generated through capital allocation (SLL), distribution rewards, SparkLend reserve factor revenue, and treasury operations, net of the cost of capital, curator fees, grants and operating expenses, to illustrate Spark’s protocol-level net results for the quarter.

Accounting note: The consolidated statement of earnings represents Spark’s internal, accrual-based estimation of revenues, costs, and net results for the quarter, based on protocol-level data and internal calculations. Settlement flows from SKY may differ in timing or amount and are reconciled over subsequent settlement periods.

Link to the glossary here

4. Consolidated balance sheet

Snapshot of assets held by Spark’s protocol-controlled smart contracts and treasury addresses at quarter-end, expressed in USDS terms across both treasury-held and allocated positions.

Links to the treasury address here.

A snapshot of Spark’s assets and liabilities at quarter-end, based on onchain balances and settlement determinations by SKY, the parent protocol.

5. Quarterly Insights and Commentary

Growth drivers

Q1 was defined by the scaling of Spark’s distribution business and the diversification of its SLL allocation venues. Distribution rewards grew to $3.31M for the quarter, overtaking net SLL revenue as the protocol’s primary net return driver. This reflects a structural shift in how the protocol generates returns under different market conditions. This growth was supported by continued demand for USDS-denominated Savings Vaults across multiple chains and token types.

On the SLL side, Spark Institutional lending continued to mature, with $150M deployed at quarter-end under a governance-approved $1B ceiling. This structure broadens Spark’s exposure beyond onchain money markets into institutional custody-supported lending, while maintaining conservative risk parameters.

The growth of Spark USDT Savings Vault, while compressing short-term SLL net returns, represents a strategic investment in capturing institutional USDT demand and expanding the protocol’s stablecoin distribution footprint. As lending spreads compress, distribution-driven returns scale with demand for predictable savings exposure, providing a natural counterbalance within the system. 

Challenges

Market conditions during Q1 were characterized by reduced DeFi lending activity and compressed spreads. The SLL capture spread narrowed from 0.70% in Q4 to 0.64% in Q1, driven by softer lending demand and rising Savings Vault's borrow costs associated with the USDT Vault ramp. Average SLL allocation capital declined from $2.8B in Q4 to $1.93B in Q1, reflecting reduced lending demand across the protocol’s venue set.

Despite these headwinds, the protocol remained profitable every month during the quarter, with net protocol surplus ranging from $990k to $1.29M monthly. The structural shift toward distribution revenue provided a natural hedge: as lending spreads compressed, demand for savings based capital deployment increased, and Spark’s distribution infrastructure captured this flow. This demonstrates the system’s ability to adapt to changing market conditions without increasing risk exposure. 

Risk management

Throughout Q1, Spark continued to prioritize security and capital preservation. SparkLend maintained a high-quality collateral mix, while the Spark Liquidity Layer remained predominantly allocated to over-collateralized lending strategies, both onchain and through carefully selected institutional counterparties including the Anchorage tri-party structure.

During the quarter, low-borrow-activity collateral types were removed from SparkLend, whose risk-adjusted contribution did not justify the additional risk surface they introduced to the protocol. Additionally, Spark initiated the wind-down process of the SparkLend Gnosis Chain instance, removing tail risk and reducing operational overhead. These actions reflect a deliberate risk reduction and a focus on maintaining a streamlined, defensible protocol surface as the system scales. 

The protocol’s treasury stood at $46.1M at quarter-end, continuing to serve as junior capital for the system and providing an additional buffer against adverse market conditions. Conservative risk parameters remain central to Spark’s approach as it scales into its institutional product suite.

Appendix

Glossary

Spark addresses:

• Spark Treasury: 0x3300f198988e4C9C63F75dF86De36421f06af8c4

• Spark Liquidity Layer:

  • Ethereum: 0x1601843c5e9bc251a3272907010afa41fa18347e

  • Base: 0x2917956eFF0B5eaF030abDB4EF4296DF775009c

  • Unichain: 0x345E368fcCd62266B3f5F37C9a131FD1c39f5869

  • Arbitrum: 0x2B05F8e1cACC6974fD79A673a341Fe1f58d27266

  • Optimism: 0xe0F9978b907853F354d79188A3dEfbD41978af62

  • Avalanche: 0xecE6B0E8a54c2f44e066fBb9234e7157B15b7FeC

Disclaimers

This communication is provided for informational purposes only, without warranty of any kind, express or implied, including but not limited to implied warranties of merchantability, non-infringement, or fitness for a particular purpose. This communication has been prepared based on data and information that has not been independently verified and Phoenix Labs makes no representations about the accuracy of the information or appropriateness for a given situation. This content is not intended or offered as advice of any kind including financial, investment, legal, regulatory, or tax advice, and users should seek qualified professional advice where appropriate. References to assets or protocols are provided for informational purposes only, and this communication is not an offer to sell, solicitation of an offer to buy, or inducement or recommendation to engage with any asset or protocol. For the avoidance of doubt, Phoenix Labs prepares this report solely in its capacity as a nested contributor and does not control, own, or operate Spark or its protocol treasury. This communication has not been prepared by a professional accounting service provider, and figures and calculations may not conform to GAAP or other international standards for financial reporting. This communication is not intended for residents or nationals of the United Kingdom, or for other prohibited or restricted jurisdictions and persons including those listed on US, EU, UK, or UN sanctions lists.

More than $150 billion in stablecoins now circulate across public blockchains, with a growing share used as operational liquidity rather than speculative capital. Yet the infrastructure used to deploy stablecoin capital has not evolved at the same pace.

Much of DeFi still relies on architectures designed for smaller, fragmented flows where liquidity is deployed into isolated markets and adjusts reactively to borrowing demand. These systems work well when capital moves gradually. They become far less predictable when large deposits or withdrawals occur.

As vault-based systems have emerged, the question is no longer whether vaults are better than pools, but how different vault designs handle liquidity, risk, and capital allocation under scale.

The next phase of stablecoin adoption requires liquidity systems designed to coordinate capital across markets, rather than simply react to utilisation within them.

From Yield Markets to Liquidity Infrastructure

Early DeFi lending systems were primarily designed for yield discovery. Capital entered liquidity pools, borrowing demand drove utilisation, and interest rates adjusted automatically. This structure created efficient markets for lending crypto assets and helped bootstrap liquidity across the ecosystem. But as stablecoins increasingly function as treasury liquidity rather than speculative capital, the priorities of large allocators begin to shift.

Institutional capital tends to evaluate liquidity systems in a different order:

1. Withdrawal certainty

2. Liquidity depth

3. Rate stability

4. Yield

Yield still matters, but it is rarely the first variable considered. For large capital allocators, the primary questions are risk, liquidity access, and capital protection: what is generating the yield, how risk is managed across deployments, and how the system behaves under stress. This includes whether capital can be withdrawn predictably, whether liquidity remains available during large flows, and whether the system can absorb withdrawals without destabilising markets. In systems managing billions in stablecoin liquidity, liquidity design and risk structure become as important as return itself.

Beyond liquidity, institutions increasingly evaluate how losses are absorbed and where risk ultimately sits within the system. In Spark, risk is structured across multiple layers of capital, rather than relying solely on collateral and liquidations to absorb losses.

At the first layer, protocol-level capital buffer (currently $36m USDS) acts as a first loss buffer, designed to absorb losses before impacting users. This is followed by system-level aggregate backstop capital of $43.5M from within the broader Sky ecosystem, designed as an additional layer of support under stressed conditions. Additional layers, including external junior capital modules and token based mechanisms, provide further protection as losses escalate.. Together, these buffers form a predefined loss hierarchy, where risk is absorbed by dedicated capital layers before reaching end users. Allocation decisions are therefore not only governed by predefined rules, but backed by capital explicitly designed to absorb losses.

This multi-layered approach, combined with one of the largest stablecoin balance sheets in DeFi (over $11.5B), reflects a shift from isolated yield generation toward structured, system-level credit infrastructure.

Not All Vaults Are the Same

The shift from pools to vaults is often presented as a clear upgrade. In practice, the underlying vault structure is similar, but how capital is managed within those structures varies significantly.

For institutional allocators, the distinction is not whether a system uses a vault, but how capital is allocated, how liquidity behaves under large flows, and how risk and losses are managed across the system.

Rather than representing fundamentally different structures, most vault-based systems can be understood as different allocation models, defined by their mandate, constraints, and how capital is deployed.

Broadly, these allocation models can be grouped into three categories based on how they manage capital, liquidity, and risk:

1. Yield-maximising allocation models
Designed to optimise for competitivethe highest possible returns by dynamically allocating capital across higher-risk strategies. These systems can deliver higher yield, but often introduce more variable risk profiles, less predictable liquidity, and limited structured approaches to loss absorption beyond the performance of the underlying strategies.

2. Market-based allocation models
Vaults that allocate capital into specific lending markets or isolated opportunities, with outcomes largely determined by utilisation, borrower demand, and collateral dynamics within each market. These systems improve capital efficiency, but liquidity and withdrawal conditions remain dependent on the underlying market-level behaviour. Risk is primarily managed within individual positions rather than across the system.

3. System orchestrated allocation models (Spark Vaults)
Capital is managed at the system level across markets through predefined allocation rules, liquidity buffers, and risk parameters. Rather than relying on individual markets, these systems coordinate capital deployment across multiple venues, allowing liquidity and risk to be managed at the system level, enabling more predictable withdrawal access while introducing structured approaches to risk management and loss absorption.

As a result, the relevant comparison is no longer between pools and vaults, but between how different allocation models manage liquidity, risk, and loss absorption under real capital flows.

Comparing Allocation Models

These differences become most visible when comparing how each model handles capital allocation, liquidity access, and risk:

As capital scales into the hundreds of millions and billions, these differences move from theoretical to operational. Systems that rely on individual markets or strategy-level allocation become increasingly constrained during times of stress, i.e. large inflows or withdrawals. At this scale, the focus shifts from maximising yield to maintaining liquidity access under constraints, controlling risk, and determining how losses are absorbed at the system level.

How Spark Savings Implements Coordinated Liquidity

Spark Savings is designed as a coordinated liquidity system that manages capital at the system level rather than within individual markets. Instead of allocating capital into opportunistic markets, Spark deploys funds according to predefined allocation rules that balance liquidity availability, risk constraints, and capital efficiency.

Capital is allocated programmatically across a range of approved deployment venues, including lending markets, system-level treasury and RWA exposure, and other liquidity venues. Crucially, not all capital is deployed at once. A portion is maintained in dedicated liquidity buffers to support withdrawal requests under normal and stressed conditions, subject to system constraints, reducing reliance on immediate market liquidity.

This separation between deployed capital and reserved liquidity is what allows the system to support more predictable withdrawals, even during periods of large inflows or outflows. Allocation is governed by predefined system-level parameters that determine how capital is distributed, the minimum available liquidity required, and how exposures are adjusted as market conditions change. These constraints are enforced programmatically within the system ensuring that deployed capital remains within the defined risk and liquidity limits without external discretionary intervention.

Rather than losses being determined solely by outcomes within individual markets, losses are absorbed through predefined system-level buffers and backstops, distributing risk across the system rather than within isolated positions.

The result is a system where liquidity, risk, and capital allocation are coordinated together, enabling stablecoin capital to be deployed at scale while maintaining predictable access to liquidity. This model has already attracted significant capital. The USDC Savings Vault recently surpassed $1 billion in TVL, while the USDT vault has quadrupled over the last 3 months to $675M+. Across the broader system, Spark now coordinates more than $11.5B in stablecoin liquidity across DeFi markets. This growth reflects increasing demand from institutions, protocol treasuries, and capital allocators seeking predictable and transparent infrastructure to deploy stablecoin capital.

Capital Growth

The Orchestration Layer Behind Spark Savings

At the centre of Spark’s architecture is the Spark Liquidity Layer (SLL), which acts as the orchestration layer governing how capital is deployed across the system.

Rather than leaving allocation decisions to individual markets or strategies, the SLL enforces predefined rules that determine how capital is distributed, the minimum liquidity maintained for withdrawals, and how risk is managed across deployments. These parameters are defined through governance and updated as conditions evolve, ensuring that capital allocation remains consistent and transparent under system wide liquidity and risk constraints.

This structure allows Spark to operate as a unified system for capital deployment, rather than a collection of independent markets, where liquidity access and risk are managed at the system level rather than determined by individual market conditions

Making Risk Legible for Institutions

For institutional allocators, standardised risk frameworks are a prerequisite for capital deployment. Traditional credit markets rely on comparable metrics to quantify potential loss exposure and evaluate assets across portfolios. DeFi has historically lacked an equivalent, making it difficult to evaluate and compare on-chain risk in a consistent way.

Spark Savings vaults have been independently assessed by Credora by Redstone, providing model-driven credit analysis, with risk metrics surfaced directly within the product interface.

Across the currently rated Spark Savings vaults:

• 6 vaults rated between A+ and B+

• Probability of Severe Loss (PSL) ranges from 0.25%-1.03%. The ratings are produced independently using Credora’s proprietary risk models.

These ratings are produced independently using Credora’s risk models and a combination of on-chain and external data sources, providing a standardised framework for evaluating risk across vaults. This allows institutions to assess capital deployment using comparable, model-driven metrics, rather than relying solely on yield or inferred risk assumptions.

The Next Phase of Stablecoin Infrastructure

Stablecoins are increasingly being used as financial infrastructure rather than purely speculative assets. As this transition continues, the systems that manage stablecoin liquidity must support flows at scale, while maintaining predictable access to capital and clearly defined risk.

At the same time, regulatory frameworks for stablecoins are beginning to take shape across major jurisdictions, providing clearer operating environments for institutions and financial platforms integrating digital dollars as part of their infrastructure. At a smaller scale, liquidity can move between markets in search of yield. At institutional scale, this becomes too fragile as capital cannot rely on liquidity being available in individual markets, and risk cannot be managed in isolation.

The next phase of stablecoin infrastructure is defined by systems that coordinate liquidity at the system level, maintain dedicated buffers for withdrawals, and enforce risk constraints across all capital deployments. Within this model, yield becomes a byproduct of how capital is deployed rather than the primary objective. The defining characteristic of these systems is not how much yield they generate, but how predictably they manage liquidity and risk at scale.

For institutions evaluating stablecoin infrastructure, the focus is shifting from yield optimisation to liquidity orchestration. As capital scales, the ability to manage liquidity predictably and enforce system-level risk constraints becomes the defining requirement. Spark represents one implementation of this model, where stablecoin liquidity is orchestrated across markets through predefined rules and constraints. As on-chain capital continues to grow, systems built around liquidity orchestration and risk management will define the next generation of on-chain credit markets.

This content is for informational purposes only.

This infrastructure supports a framework for yield-bearing USDS deployments, sourcing returns from institutional delta-neutral strategies executed within Spark Prime, while maintaining transparency and risk controls.

DeFi lending markets like SparkLend have demonstrated resilience in adverse market conditions, thanks to their over-collateralized lending model. However, this lending method is extremely capital-intensive. Borrowers need to post excessive collateral to ensure they won’t be liquidated. Also, positions in DeFi lending markets are unaware of collateral that may be held at external locations, such as centralized exchanges.

A naive approach to circumventing these capital inefficiencies is to engage in unsecured lending, which can yield higher returns but requires significant trust in the borrowing entity. Lending unsecured is easy when things are going well, but DeFi needs to be resilient even in hostile conditions. The 2022 collapse proved that lending unsecured can go very wrong.

Spark Prime addresses this gap by combining protocol-allocated liquidity governed by Spark’s risk frameworks with Arkis’ margin and execution platform.

Spark Prime’s Approach

Spark Prime combines the best of both worlds by providing the capital efficiency of unsecured lending structures while maintaining collateralization controls within defined execution environments like the brokerage's walled garden.

Spark Prime is designed to support new institutional lending workflows, including:

• More resilient delta-neutral lending supported by over-collateralized positions.

• Enhanced capital efficiency relative to traditional DeFi lending markets.

• Improved DeFi transparency. Opaque funds can lead to hidden risks, but with Spark Prime, positions are visible in real time through protocol-level data and transparency mechanisms.

Spark Prime leverages protocol-allocated liquidity governed by Spark’s risk management frameworks. This draws on the protocol’s long history and experience operating large-scale, resilient DeFi systems.

How Spark Prime works

Arkis’ margin technology enables borrowers to distribute collateral custody across smart contracts, qualified custodians, and centralized trading venues via a direct market access (DMA) setup. Liquidity allocation and risk parameters are defined through Spark’s governance frameworks and enforced by the Arkis platform.

Margining is supported across:

• CeFi

  • Binance

  • Bybit

  • OKX

  • Hyperliquid

• DeFi

  • Pendle

  • Curve
    
    

Who is Spark Prime for

Hedge funds are one of the largest borrowers in DeFi, accounting for the majority of market activity. Spark Prime enables these strategies by combining on-chain transparency with access to CeFi liquidity and execution venues through the Arkis platform.

Use Cases

1. Basis Trading with cross margin across CEX/DEX venues

Spark Prime enables funds to collateralize positions across governance-approved venues. Funds that want to take advantage of yield farms in DeFi can now take long exposure in DeFi or qualified custody, and short perpetual futures on CEXs.

Arkis’ risk engine, integrated into Spark Prime, recognizes the long-spot vs. short-perp hedge across multiple venues in CeFi and DeFi, so margin is set on net risk, not gross notional. This lowers initial/maintenance margin and unlocks higher effective leverage than siloed venues.

2. Qualified Custodian Support

Spark Prime supports collateralization of positions held with qualified custodians through defined tri-party enforcement structures. Institutions maintain compliance with internal mandates while gaining real-time access to credit in DeFi and CeFi.

3. Portfolio Margin with Multi-Collateral Diversification

Spark Prime allows borrowers to post multiple, low-correlated assets, like LSTs, LP tokens, RWAs, and stables. Because these assets exhibit diverse risk profiles and cross-asset hedging effects, the margin engine assigns reduced risk weights at the portfolio level rather than penalizing each asset individually.

This diversification improves the account's health score, enabling greater borrowing power, lower liquidation risk, and optimized margin utilization without adding net directional exposure.

4. Less Volatile Borrowing Costs

Borrow rates using interest rate models based on the expected yield of the posted collateral, not just on pool utilization. This creates a target spread: borrowers always guarantee a minimum yield-to-borrow cost gap. As a result, looping or hedging strategies gain predictable funding and can scale with confidence.

Borrowers still leverage low-cost collateral and borrow stables or crypto in real time. Rate spikes become less likely because the model reduces dependence on volatile utilization. This improves ROE and reduces tail risk from rapid cost escalation. This is ideal for institutional strategies that require risk-budgeted lending and repeatable outcomes.

Partners & AUM

Spark Prime is launching with the biggest institutional participants in the space. Initial launch partners include:

• Edge Capital ($600 million AUM)

• M1 ($180 million AUM)

• Hardcore Labs ($100 million AUM)

An allocation of $15 million has been made, but this list is just a start. The total addressable market for delta-neutral strategies in crypto is in the tens of billions, and Spark Prime is well-positioned to capture a significant share.

Roadmap

Spark Prime has started small to ensure all components operate reliably and safely, with a clear path toward scaling:

1. Contract Upgrades and Market multi-party approval

The process for upgrading the code and adjusting market risk parameters will shift to a multi-party approval process, involving relevant contributors and stakeholders across Arkis, Spark, and Sky ecosystem.

2. Off-exchange Settlement

Off-exchange settlement is the process of holding collateral assets with qualified custodians rather than holding them directly on the exchange. It has become an industry standard to protect against exchange hacks.

3. Liquidation Fallback

To provide stronger assurances of solvency, a backup liquidation method is being included to take over in the event of the core margin engine's failure.

4. High-Yield Vault

A governance-defined USDS deployment framework is expected to launch, providing junior tranche exposure to Spark Prime.

It is expected that these changes will be progressively added in Q2/Q3 of 2026. Each upgrade reduces the protocol's risk and allows Spark to progressively increase its exposure accordingly.

Spark Prime represents an evolution in how DeFi and CeFi infrastructure can interoperate to support institutional lending protocols. Building on Spark’s governance-defined risk frameworks and Arkis’ execution technology, Spark is poised to raise the bar on CeDeFi lending.

To learn more about Spark’s institutional offering, visit here or contact the team at contact@spark.fi

Below is the Q4 2025 financial report.

1. Executive Summary

Spark closed Q4 in a strong financial position, based on internal estimates derived from onchain data and governance-defined mechanisms. The quarter reflected sustained yield generation and efficient capital deployment across Spark’s core protocol components, with distribution rewards, the Spark Liquidity Layer, and SparkLend representing the primary contributors to protocol-level returns despite a more challenging market environment in the latter part of the period.

Q4 Financial Highlights

• Gross protocol returns: $45.4M (aggregate returns across all protocol components)

• Net protocol returns: $9.87M (gross returns less cost of capital)

• Net protocol surplus: $6.57M (gross returns less operating expenses)

• Spark Protocol treasury (end of quarter): $43.22M

• $4M strategic investment in Arkis

All figures represent internal, non-GAAP, protocol-level estimates and do not represent profits of Phoenix Labs or any legal entity.

Overall, Q4 demonstrated Spark’s resilience and scalability as an onchain protocol infrastructure. The protocol remains well positioned under the potential of improving market conditions while preserving capital efficiency and balance sheet strength going into the next quarter

2. Product Line Performance

Spark comprises several protocol components that generate protocol-level returns accrued to the treasury pursuant to governance-defined mechanisms.

These are (i) Spark Liquidity Layer (ii) distribution rewards (iii) SparkLend (iv) Treasury Management & Financial Operations.

2.1 Spark Liquidity Layer (SLL)

The Spark Liquidity Layer is a smart-contract system in which assets are allocated in a programmatic and non-custodial manner into yield generating opportunities. Thanks to this sophisticated system, the protocol may generate returns subject to market conditions, smart-contract execution, and governance-defined risk parameters.

Revenue model: The protocol captures spread between the investment’s APY and the SSL’s borrowing cost, subject to market conditions.

Q4 highlights: During Q4, Spark was able to capture the highest spread on the Morpho Spark USDC vault on Base, where it deployed $594M, allocated via protocol mechanisms to support Bitcoin-backed lending activity for Coinbase users and made $6.1M in gross protocol returns.

KPIs:

• Average deployment: $2.818B

• Average APY: 5.9%

• Gross returns: $40.48M

• Gross revenue: $4.95M

• Captured spread: 0.7%

2.2 Distribution rewards

Spark functions as a governance-approved distribution mechanism within the SKY ecosystem, allowing users to get exposure to USDS, and the SKY savings rate, 

Revenue model: The protocol accrued a 0.6% accessibility reward on all USDS routed through its distribution channels, via onchain referral codes.

Q4 highlights: During Q4, Spark saw a substantial increase in USDS distribution, driven primarily by the continued expansion of the Spark sUSDC vault. Total USDS distribution grew to $2.071B by quarter-end, up from $773M at the start of the quarter. sUSDC increased from $452M to $1.385B, while sUSDS expanded from $184M to $305M. In parallel, Avalanche supply grew to $225M, reflecting broader multi-chain adoption across Spark’s distribution channels. StakedUSDS distribution generated $1.208M in revenue during the quarter.

KPIs:

• Distributed supply at end of Q4: $2.07B

• Distribution reward rate: 0.6% APY

• Q4 revenue: $4.472M

2.3 SparkLend

SparkLend is a core lending protocol within the Spark ecosystem, operating as one of the largest and most secure lending platforms in DeFi, with only blue-chip collateral. It supports institutional borrowing activity, with liquidity supplied through the SLL as the governance-approved protocol mechanism.

Revenue model: Spark collects a reserve factor on interest accrued by borrowers. 

Q4 highlights: During Q4, SparkLend total value locked peaked at $6.4B, reflecting continued usage of the protocol despite a more challenging market environment for lending markets. Activity and utilization metrics trended lower over the course of the quarter in line with broader market conditions, while SparkLend maintained its position as one of the largest and most liquid money markets in DeFi, supported by governance-defined conservative risk parameters and blue-chip collateral.

KPIs:

• Total deposits: $6.4B

• Q4 revenue (reserve factor on yield, excluding SLL): $215k

2.4 Treasury Management & Financial Operations

Spark’s treasury represents the DAO’s protocol-controlled operational capital. It both pays for the operational expenses as well as acts as junior capital required by SKY to fulfill the risk-required capital needs for accessing the SKY credit line.

Revenue model: The protocol may generate returns on treasury assets through SKY’s savings rate and other financial operations.

Q4 highlights: During Q4, the protocol experienced losses arising from volatile asset exposure, which was offset by the USDS yield generated by the treasury balance. Overall, Spark realized $117k in net positive returns during Q4.

3. Consolidated P&L

Summary of Spark’s total revenues, costs, and net results across all product lines for the quarter. It combines investment returns, treasury operations, distribution rewards, SparkLend reserve factor, net of the cost of capital, curator fees, grants and operating expenses, to illustrate  Spark’s protocol-level net results for the quarter.

Accounting note:
The consolidated statement of earnings represents Spark’s internal, accrual-based estimation of revenues, costs, and net results for the quarter, based on protocol-level data and internal calculations. Actual cash settlements received from SKY may differ in timing or amount and are reconciled over subsequent settlement periods.

4. Consolidated balance sheet

Snapshot of assets held by Spark’s protocol-controlled smart contracts and treasury addresses at quarter-end, expressed in USDS terms across treasury and deployed positions.

A snapshot of Spark’s assets and liabilities at quarter-end, based on onchain balances and settlement determinations by SKY, the parent protocol.

5. Quarterly Insights and Commentary

Growth drivers

Q4 was characterized by continued expansion of Spark’s institutional-grade protocol infrastructure and strong growth across its distribution business. During the quarter, USDS distribution scaled significantly and emerged as one of Spark’s key revenue drivers, supported by sustained demand across multiple chains and products.

Alongside this growth, the Spark Liquidity Layer reached $2.022B deployed across multiple stablecoins into SparkLend, reinforcing its role as the primary liquidity mechanism within the system. Spark governance approved additional institutional-focused lending strategies, including tri-party lending via Anchorage-supported custodial workflows. These initiatives marked an important step in broadening Spark’s exposure beyond on-chain money markets while maintaining a conservative risk profile. Additionally, Spark seeded one of the largest and highest-volume Curve pools, supporting pyUSD liquidity and further strengthening Spark’s role in stablecoin market infrastructure.

Challenges

Market conditions during Q4 were less favorable than earlier in the year, with reduced activity and softer yield environments across DeFi. Despite this backdrop, Spark maintained a high level of deployed liquidity, preserved capital efficiency, and closed the quarter with a healthy profit. Yield compression and utilization changes were reflected through governance-defined allocation parameters and disciplined cost control, allowing the protocol to remain profitable without loosening risk parameters.

Risk management

Throughout Q4, Spark continued to prioritize security and capital preservation. SparkLend maintained a high-quality collateral mix, while the Spark Liquidity Layer remained predominantly allocated to over-collateralized lending strategies, both on-chain and through carefully selected institutional counterparties. All new deployments and asset listings underwent rigorous governance-defined screening criteria to meet institutional-grade standards.

Spark’s treasury was maintained during the quarter and continues to serve as junior capital for the system, providing an additional buffer against adverse market conditions. Audited, non-custodial smart contracts and conservative risk parameters remain central to Spark’s approach as it scales into institutional lending and active liquidity provision strategies.

_________

Appendix

Glossary

Spark addresses:

• Spark Treasury: 0x3300f198988e4C9C63F75dF86De36421f06af8c4 

• Spark Liquidity Layer:

  • Ethereum: 0x1601843c5e9bc251a3272907010afa41fa18347e

  • Base: 0x2917956eFF0B5eaF030abDB4EF4296DF775009c

  • Unichain: 0x345E368fcCd62266B3f5F37C9a131FD1c39f5869

  • Arbitrum: 0x2B05F8e1cACC6974fD79A673a341Fe1f58d27266

  • Optimism: 0xe0F9978b907853F354d79188A3dEfbD41978af62

  • Avalanche: 0xecE6B0E8a54c2f44e066fBb9234e7157B15b7FeC

Dune queries:
https://dune.com/sparkdotfi/spark-accessibility-rewards
https://dune.com/queries/6517419/10313178
https://dune.com/queries/5441979/9493327
https://dune.com/queries/6517340/10313028
https://dune.com/queries/5449746/8891165

Disclaimers

This communication is provided for informational purposes only, without warranty of any kind, express or implied, including but not limited to implied warranties of merchantability, non-infringement, or fitness for a particular purpose. This communication has been prepared based on data and information that has not been independently verified and Phoenix Labs makes no representations about the accuracy of the information or appropriateness for a given situation. This content is not intended or offered as advice of any kind including financial, investment, legal, regulatory, or tax advice, and users should seek qualified professional advice where appropriate. References to assets or protocols are provided for informational purposes only, and this communication is not an offer to sell, solicitation of an offer to buy, or inducement or recommendation to engage with any asset or protocol. For the avoidance of doubt, Phoenix Labs prepares this report solely in its capacity as a nested contributor and does not control, own, or operate Spark or its protocol treasury. This communication has not been prepared by a professional accounting service provider, and figures and calculations may not conform to GAAP or other international standards for financial reporting. This communication is not intended for residents or nationals of the United Kingdom, or for other prohibited or restricted jurisdictions and persons including those listed on US, EU, UK, or UN sanctions lists.

SparkLend is the largest institutionally-focused lending market on Ethereum, with over $5 billion in deposits.

Spark Savings provides the ultimate treasury management solution with deep on-chain stablecoin liquidity ($4.2 billion) and competitive risk-adjusted rates (4%).

Spark Liquidity Layer provides capital to the DeFi ecosystem, such as Maple, to service off-chain OTC crypto loans ($200 million deployed).

Spark is expanding its institutional offerings through an integration with Anchorage Digital, America's first federally regulated crypto platform, via Atlas, Anchorage Digital's rapid settlement infrastructure, to extend its existing crypto-backed lending to institutional borrowers that are not yet comfortable coming on-chain and prefer custodial workflows. Anchorage Digital is a leading qualified custodian and provides tri-party OTC collateral management services to clients, enabling Spark to lend directly to counterparties while maintaining collateral monitoring and risk controls. 

Initial borrowers under this structure include three institutional counterparties, which have borrowed $150 million USDC against $222 million of BTC collateral. The Spark Data Dashboard allows for real-time tracking of assets to ensure loans remain collateralized.

The size of the off-chain crypto lending market is estimated at around $33 billion, reflecting sustained institutional demand for crypto-backed loans outside of DeFi. Through its lending infrastructure and integration with qualified custodians, Spark provides institutions with access to large-scale liquidity. For more information, email contact@spark.fi.

Below is the Q3 2025 financial report, covering Spark’s first full quarter under its own P&L.

1. Executive Summary

- The start of Q3 marked a pivotal moment for Spark, with the official launch of Spark’s P&L on July 1st, 2025. Prior to this, Spark operated under SKY, which covered all expenses while retaining the revenues generated by Spark
- At launch, Spark received an initial seed allocation of 25M USDS, establishing a robust foundation for future growth.
- During Q3 2025:
→ Gross revenue: $53.02M (aggregate returns across all product lines)
→ Gross profit / net revenue: $19.2M (gross returns less cost of capital)
→ Net profit: $12.12M (gross revenue less operating expenses)
→ Spark Protocol treasury (end of quarter): $38.8M

Spark closed Q3 in a strong financial position, with $53.01M in total earnings and $12.12M in net profit. The quarter reflected robust yield generation, efficient capital deployment, and continued growth across Spark’s core product lines.

2. Product Line Performance

Spark has a diverse set of product lines that stream revenue into the treasury.

These are (i) Spark Liquidity Layer (ii) distribution rewards (iii) SparkLend (iv) market curation (v) Treasury Management & Financial Operations.

2.1 Spark Liquidity Layer (SLL) The Spark Liquidity Layer is a  smart-contract system in which Spark deploys assets in a programmatic and non-custodial way into yield generating opportunities. Thanks to this sophisticated system, Spark is able to access competitive risk-adjusted returns in multiple chains in an efficient manner.

Revenue model: Spark earns revenue by capturing a spread between the investment’s APY and the SSL’s borrowing cost.

Q3 highlights: During Q3, Spark was able to capture the highest spread on the Morpho Spark USDC vault on Base, where it deployed $607M at it's peak to service Bitcoin-backed loans for Coinbase users and made $8.59M in gross revenue.

KPIs:

• Average deployment: $3.141B

• Average APY: 5.8%

• Gross returns: $44.03M

• Gross revenue: $10.21M

• Captured spread: 1.14%

2.2 Distribution Rewards Spark acts as SKY distribution agent, allowing users to get exposure to USDS, and the SKY savings rate,

Revenue model: Spark collects a 0.6% accessibility reward on all USDS routed through its distribution channels, via on-chain referral codes.

Q3 highlights: During Q3 Spark experienced a significant increase in USDS distribution, mainly through the Spark sUSDC vault. This distribution was amplified by integrations with other distribution channels and grants on a number of blockchains. Notably, sUSDC on Ethereum grew to $487M.

KPIs:

• Distributed supply at end of Q3: $682M

• Distribution reward rate: 0.6% APY

• Q3 revenue: $2.65M

2.3 SparkLend SparkLend is Spark’s native money market, operating as one of the largest and most secure lending platforms in DeFi, with only blue-chip collateral. It services institutional borrowers with the SLL as the primary lender.

Revenue model: Spark collects a reserve factor on interest accrued by borrowers.

Q3 highlights: In Q3, SparkLend expanded the SparkLend USDT and SparkLend pyUSD markets to $800M and $500M respectively, making SparkLend the second-largest USDT market on Ethereum and the largest pyUSD market.

KPIs:

• Total deposits: $7.35B

• Q3 revenue (reserve factor on yield, excluding SLL): $305.5k

2.4 Market Curation Spark is one of the largest curators in DeFi, curating vaults across Ethereum and Base (USDS, DAI, USDC) and directing liquidity into high-quality collateral markets. By curating markets, Spark ensures efficiency, depth, and security for lenders and borrowers.

Revenue Model: Spark collects a reserve factor on all interest accrued within its curated markets. This share of borrower interest flows directly to Spark’s revenues.

Q3 highlights: During Q3, Spark became the #1 curator in DeFi, taking the top spot on the Morpho leaderboard. Spark also positioned itself to potentially qualify for the Morpho Olympics, which should grant incentive packages.

KPIs:

• Total Curated Value (end Q3):$799.5M

• Q3 revenue (curator fee): $176.5k

2.5 Treasury Management & Financial Operations

Spark’s treasury is the DAO’s operational capital. It both pays for the operational expenses as well as acts as junior capital required by SKY to fulfill the risk-required capital needs for accessing the SKY credit line.

Revenue model: Spark is able to monetize the assets in the treasury through SKY’s savings rate and other financial operations.

Q3 highlights: During Q3, Spark realized $861.6k in net positive returns.

3. Consolidated P&L

Summary of Spark’s total revenues, costs, and net results across all product lines for the quarter. It combines investment returns, treasury operations, distribution rewards, SparkLend reserve factor, net of the cost of capital, curator fees, grants and operating expenses, to show Spark’s overall profitability.

4. Consolidated balance sheet

Snapshot of all assets held by Spark at quarter-end, expressed in USDS terms across treasury and deployed positions.

5. Quarterly Insights and Commentary

Growth drivers
Q3 marked a period of strong expansion for Spark, driven by new integrations and deeper capital deployment across its core markets. Spark integrated PayPal’s PYUSD on SparkLend and the SLL and grew deposits in SparkLend to $500M, reaching a peak SparkLend allocation of $1.52B. The expansion of the USDT market to $550M enabled a new class of institutional borrowers to operate on SparkLend and broadened the SLL’s investable universe.

A key revenue driver, and where Spark captured its largest spreads, were the DAI and USDS Morpho vaults, along with the syrupUSDC allocation, which increased to $630M during the quarter.

Challenges
The crypto market experienced heightened volatility throughout Q3. While Spark captured strong yields during the first half of the quarter, market conditions softened in the second half, leading to a moderation in returns. Despite this, Spark remains well positioned to benefit from a potential market rebound, with a diversified portfolio, active liquidity management, and conservative risk parameters ensuring resilience across market cycles.

Risk management
Spark prioritized security and capital preservation. This is reflected on SparkLend’s high-quality asset composition, and the SLL’s deployment, which remained mostly allocated to over-collateralized onchain loans, in both SparkLend and Morpho deployments

All deployments and asset listing are thoroughly screened for institutional-grade standards. The Spark Liquidity Layer operates through audited, non-custodial smart contracts, ensuring transparent and programmatic capital deployment. Spark grew its treasury to $38.8M, which serves as junior capital for the system.

6. Appendix

Spark addresses:

• Spark Treasury: 0x3300f198988e4C9C63F75dF86De36421f06af8c4

• Spark Liquidity Layer:

  • Ethereum: 0x1601843c5e9bc251a3272907010afa41fa18347e

  • Base: 0x2917956eFF0B5eaF030abDB4EF4296DF775009c

  • Unichain: 0x345E368fcCd62266B3f5F37C9a131FD1c39f5869

  • Arbitrum: 0x2B05F8e1cACC6974fD79A673a341Fe1f58d27266

  • Optimism: 0xe0F9978b907853F354d79188A3dEfbD41978af62

Dune queries: https://dune.com/sparkdotfi/spark-accessibility-rewards

Disclaimer:

This communication is provided for informational purposes only, without warranty of any kind, express or implied, including but not limited to implied warranties of merchantability, non-infringement, or fitness for a particular purpose. This communication has been prepared based on data and information that has not been independently verified and Phoenix Labs makes no representations about the accuracy of the information or appropriateness for a given situation. This content is not intended or offered as advice of any kind including financial, investment, legal, regulatory, or tax advice, and users should seek qualified professional advice where appropriate. References to assets or protocols are provided for informational purposes only, and this communication is not an offer to sell, solicitation of an offer to buy, or inducement or recommendation to engage with any asset or protocol. This communication has not been prepared by a professional accounting service provider, and figures and calculations may not conform to GAAP or other international standards for financial reporting. This communication is not intended for residents or nationals of the United Kingdom, or for other prohibited or restricted jurisdictions and persons including those listed on US, EU, UK, or UN sanctions lists.

Initially launching with support for USDC, USDT and ETH on Ethereum mainnet, Savings V2 will be progressively rolled out to more chains and stablecoins over the coming months.

A More Secure Approach to Savings

Spark Savings takes a conservative approach to collateral composition. Exposure to riskier collateral, such as perpetual futures, is deliberately minimized to insulate from market stress. The October 10th Auto-Deleveraging (ADL) event underscores the importance of this issue more than ever.

Despite this conservative stance, the Savings Rate is often able to deliver better performance due to integrations with RWAs. Currently anchored at the Sky Savings Rate (SSR) of 4.75%, this rate outperforms Aave USDC/USDT by ~75bps.

Institutional-Grade Liquidity

While this rate was already available for USDC in Savings V1, there was friction in moving between USDT and USDS. Savings V2 will leverage the massive liquidity of Spark Liquidity Layer to reduce swapping frictions and provide 1:1 liquidity with the underlying asset. This is especially valuable for institutions where swapping $100 million at a time can be costly and inefficient.

Expanding to ETH

In addition to USD stablecoins, Savings V2 is expanding access to cover ETH. This enables users to earn a low-risk yield on their ETH. Initially, this yield will be sourced from the SparkLend ETH market and will be expanded to include blue-chip LSTs, such as Lido stETH, in the coming weeks.

The rate for Savings ETH will start at 1.35% APY + 50k Spark Points per ETH. This rate is expected to increase as market efficiencies improve.

Initial supply caps are limited to 50m for USDC/USDT and 10k for ETH.

Start saving

2025 has been a busy year for Spark.

The year started with the launch of the Spark Liquidity Layer (SLL). This cross-chain, multi-asset allocation system enables Spark to access new lending opportunities, such as the Coinbase BTC Borrow product, which now supports $500 million of onchain loans directly to Coinbase users on Base.

Coinbase kicked things off, but it is expected that most exchanges/fintechs will follow suit as the world races to get onchain. This is due to the cheap capital provided by stablecoins. Spark is well-positioned to capture all this new demand via the SLL, which has grown to $3.15 billion allocated, generating an average of 5.8% APY across many different protocols.

Spark retains 100% of the spread above the 5.05% Sky Base Rate. The estimated annual recurring revenue of the SLL stands at $26 million.

June marked the launch of the SPK token across most major exchanges, including Coinbase, Binance, OKX, Bybit, and others, with over 320m tokens staked by 5k+ stakers.

Starting July 1st, Sky enabled full Profit and Loss calculations, which means Spark is now retaining the revenue it earns. The first payments closing out the months of July and August were made on September 22, totaling 5,927,944 USDS paid to the Spark Treasury.

What’s Coming

2025 has been a transitional year for institutional adoption, marked by the passage of legislation such as the GENIUS Act. DeFi is maturing to a place where web2 fintechs are coming onchain with examples such as PayPal, Stripe, Robinhood, and others.

Spark is well-positioned to capitalize on this institution-driven growth by providing high-quality lending infrastructure, such as SparkLend and Spark Savings, as well as newer offerings detailed below.

Here are the protocol updates that will be proposed in the coming months to Spark governance:

SparkLend

SparkLend is the second-largest lending market on Ethereum with over $7.7 billion in total deposits. While Spark has external lending operations in protocols such as Morpho, SparkLend remains one of the safest places to lend or borrow with your blue-chip crypto assets at scale.

Institutions consider risk-adjusted yield when evaluating investments, and SparkLend has consistently differentiated itself by not chasing the highest yield available in a single pool. Instead, Spark curates isolated higher-risk opportunities on Morpho. This allows for more user choice without sacrificing liquidity.

Recently, Spark has been ramping up support for USDT and PYUSD markets on SparkLend. USDT has demonstrated strong growth over the past year, increasing its market capitalization from $119 billion to $174 billion. Users can now borrow USDT at scale from the USDT market, which stands at $550 million in deposits, with plans to continue growing.

SparkLend is one of many institutional-grade lending options available for lenders and borrowers.

Savings V2

Spark Savings started as frontend support for access to Sky’s Savings USDS, but has since evolved to include Spark’s USDC vault. This enabled easy access to the Sky Savings Rate (SSR) by combining the USDC swap in the PSM with USDS staking.

Spark Savings has been highly successful, growing to a $620 million TVL across five chains in six months. Savings V2 expands upon this success by offering the same vaults for USDT and ETH, powered by the Spark Liquidity Layer cross-chain infrastructure.

With Savings V2, swap liquidity is no longer a concern. Use your favorite asset on your favorite chain and earn the governance-determined universal savings rate on it. Spark will have a universal rate for USD assets and a separate rate for ETH assets. These yields are generated using the same conservative strategy that Spark Savings has employed from the beginning. ETH yield will start with SparkLend ETH and Lido stETH for yield.

Pending governance approval, Savings V2 will launch in October on Ethereum Mainnet. Existing V1 USDC vault depositors will not be required to take any action, but migrators will receive Spark Points. You can keep funds deployed in the Savings V1 contracts indefinitely.

Spark Institutional Lending

Spark’s strength lies in institutions; however, some features are not covered by Spark’s existing capabilities. In particular, institutions are seeking fixed-rate loans and established counterparties. Spark Institutional Lending is the latest offering from Spark, utilizing Morpho’s V2 architecture.

Unlike pooled variable rate lending, Morpho V2 works by matching lenders with borrowers directly for a fixed term. This approach was attempted early on, but with limited success due to the fragmentation of lenders and borrowers. Spark solves this problem by providing an evergreen list of offers at a scale exceeding $100 million. Borrowers can select the desired duration and proceed without permission.

The Spark Liquidity Layer will ensure that liquidity is always available at market rates, just as it does with SparkLend and Morpho V1.

Spark Institutional Lending is set to launch with Morpho V2 towards the end of this year, pending approval by Spark governance, with the expected loan size to grow rapidly to over $1 billion.

Spark Mobile

While the Spark Liquidity Layer has been great for covering B2B2C use cases, it is important to have a Spark-first curated consumer experience for distribution. Spark Mobile is launching in the new year to provide a way for users to save, borrow, and pay with ease.

Stablecoin Liquidity as a Service

Launching stablecoins and chains has one thing in common – a need for liquidity. Spark is uniquely positioned to bootstrap this liquidity using the cross-chain Spark Liquidity Layer. Operating at the scale of billions, this system can support giants like Coinbase and PayPal.

For stablecoins, Spark provides lending infrastructure (SparkLend/Morpho/Aave), liquidity (Spark Liquidity Layer), and DEX support (Uniswap/Curve) to bootstrap any stablecoin to a size of billions. PayPal’s PYUSD is a good example, with the SLL having allocated $500 million to PYUSD, which will grow to a total allocation of $1 billion in the coming weeks.

For chains integrating with fintechs/exchanges, it is common for borrowing demand to mismatch earn suppliers. Spark can bridge this gap as organic demand is filled. In the case of Coinbase, they launched a borrow product without the earn side. Spark was able to fill this gap.

Similarly, chains have to run large incentive programs to keep deposits to ensure there is enough liquidity to bootstrap lending markets. With Spark, this is no longer necessary, as Spark imports the universal savings rate to all chains. As organic demand grows along the chain, Spark will move liquidity alongside borrowing demand without the negative user experience of spiking interest rates.

Spark Automated Trading Operations

The Spark Liquidity Layer is already covering most of the lending opportunities in DeFi Money Markets, RWAs, and Basis Trade. With the expansion of stablecoin coverage to include USDT and PYUSD, Spark is now holding over $900 million of non-USDC stablecoins across the DeFi ecosystem.

Spark will expand its coverage of automated trading operations in Q4 to include integrations with OTC Desks, Exchanges, and Uniswap V4, covering $100m+ stablecoin swaps. This will not only be a new source of revenue for Spark, but also a significant improvement in onchain liquidity between stablecoins, with USDS serving as the hub for onchain swaps.

While these types of operations are not new to hedge funds, high-frequency traders, and market makers, what is new is running these operations in a non-custodial manner with complete blockchain transparency, ensuring that assets are always visible. No need to trust, verify.

Spark - Institutional-grade DeFi for everyone

Spark is the first of its kind. Operating at the scale of billions while adhering to principles of transparency and openness. 2025 is a year of reaching scale within DeFi, but the size of the market opportunity is so much larger.

The Spark Bootstrapping Strategy for Stablecoins

Spark has developed a systematic approach to help new stablecoins grow:

1. Add the token in SparkLend The first step is for governance to add the stablecoin in SparkLend, creating a lending market for supply and borrowing.

2. Integrate with the Spark Liquidity Layer (SLL) The SLL provides liquidity to the new pool, making the stablecoin available for use in the broader market.

3. Set a supportive base rate Borrowing rates are configured to encourage usage in the early phase, creating natural demand for the stablecoin.

4. Support Onchain Liquidity with DEXs The SLL can supply DEX liquidity against USDS, which can leverage other stablecoins on the balance sheet, such as USDC and USDT, to facilitate large swaps.

This approach gives new issuers the critical infrastructure needed to move beyond issuance: a lending market, liquidity provision, and an incentive framework that drives adoption.

Institutional-Grade Lending Backed by Blue-Chip Collateral

SparkLend is built with institutional standards. Every new market goes through a rigorous risk assessment before being onboarded by governance. For PYUSD, this means borrowers must post blue-chip collateral currently supported by SparkLend.

Since onboarding, deposits in the PYUSD pool have exceeded $200 million. Of this, 60% remains idle PYUSD liquidity ready to be borrowed, while the rest is actively backed by collateral: 26.8% cbBTC, 6.9% wstETH, 5.8% ETH, alongside smaller shares in sUSDS (4.6%) and others (1.7%).

This mix of idle liquidity and secured borrowing demonstrates how Spark not only attracts deposits but also provides immediate depth and safety for market participants.

Building the Lego-Structure of DeFi

By combining lending infrastructure, liquidity injection, and incentive alignment, Spark enables new stablecoins to scale. This creates movement in the market, unlocking attractive borrowing opportunities and reinforcing DeFi’s modular structure—where individual components, when connected, generate systemic growth.

Institutional-Grade DeFi for Everyone

The success of PYUSD demonstrates how Spark supports stablecoin issuers through their bootstrapping phase, offering both infrastructure and liquidity.

Spark is building a foundation where new assets can thrive. Institutional-Grade DeFi for Everyone.

Spark has long relied on Morpho vaults for the Spark Liquidity Layer (SLL), deploying assets whenever a high-yield strategy requires isolated execution. Over time, these vaults have grown into major capital hubs within DeFi with over $1 billion in deposits.

Within just seven months of its launch, Spark’s USDC Morpho vault on Base has grown to become the largest in the Morpho ecosystem, attracting over $650 million in deposits. Notably, more than $200 million of that comes from third-party participants, showing the organic demand for the Spark Morpho vaults beyond internal use.

In parallel, Spark has launched high-yield DAI and USDS Morpho vaults on Ethereum mainnet to support high-yield strategies for the Spark Liquidity Layer. Today, the Spark DAI Morpho vault holds roughly $540 million, much of it deployed into PT-USDe looping strategies.

While SparkLend is focused on blue-chip collateral to provide the safest, at-scale money market in DeFi, these Morpho vaults have been critical in accessing high-yield markets not covered by SparkLend, while showcasing how efficiently Spark can allocate capital.

What’s New

Spark is launching a blue-chip USDC Morpho vault on Ethereum, expanding the range of opportunities for users to deploy capital within the Morpho ecosystem.

This new vault builds on Spark’s growing suite of offerings, Spark Savings and SparkLend, and leverages the Spark Liquidity Layer to automatically allocate USDC across the best opportunities in decentralized lending markets on Morpho.

In addition to optimizing onchain lending, Spark will extend vault participation into exchange and fintech earn programs, further broadening the liquidity pathways available. At the same time, Spark will support borrow integrations with platforms like Coinbase, ensuring that the vault plays a central role in powering both sides of the market.

Access the blue-chip USDC vault here:

https://app.morpho.org/ethereum/vault/0x56A76b428244a50513ec81e225a293d128fd581D/spark-blue-chip-usdc-vault

With this launch, Spark’s curated Morpho vaults now include:

USDC (Ethereum) -New: Spark blue-chip USDC vault. Lending against the lowest risk crypto and real-world assets (RWAs). Curated by SparkDAO which allocates billions in assets across all of DeFi.

USDC (Base) -Existing: Spark blue-chip USDC vault. Lending against the lowest risk crypto and real-world assets (RWAs). Curated by SparkDAO which allocates billions in assets across all of DeFi. https://app.morpho.org/base/vault/0x7BfA7C4f149E7415b73bdeDfe609237e29CBF34A/spark-usdc-vault

DAI (Ethereum) -Existing: Spark high-yield DAI vault. Lending against higher risk crypto and real-world assets (RWAs). Curated by SparkDAO which allocates billions in assets across all of DeFi. https://app.morpho.org/ethereum/vault/0x73e65DBD630f90604062f6E02fAb9138e713edD9/spark-dai-vault

USDS (Ethereum) -Existing: Spark high-yield USDS vault. Lending against higher risk crypto and real-world assets (RWAs). Curated by SparkDAO which allocates billions in assets across all of DeFi. https://app.morpho.org/ethereum/vault/0xe41a0583334f0dc4E023Acd0bFef3667F6FE0597/spark-usds-vault

Why It Matters

The launch of this USDC vault on Ethereum marks a natural evolution for Spark. What began as a way to meet internal liquidity needs has grown into a multi-billion-dollar engine that now anchors liquidity for some of the largest players in DeFi.

By combining blue-chip assets, automated allocation, and deep integrations with both DeFi and fintech platforms, Spark is setting a new standard for how stablecoin liquidity can flow across ecosystems.

After many years of hard work, Spark has gone live in most aspects as of July 1. This article will cover what this means in full detail, including revenue projections, the Sky/Star relationships, the long-term case for Spark, as well as an overview of this new type of decentralized governance structure.

Sky Ecosystem Overview

Sky has split itself into a subDAO structure to address the issues of scaling governance. DAOs as they exist today are largely decentralized in name only, with a select group of insiders controlling the parameters. While this is fine as a business, existing DAOs will not work for global infrastructure that needs to remain as neutral as possible.

Sky is solving this problem by outsourcing all growth-oriented decision-making to a competitive marketplace to maintain the properties of decentralization while not losing the agility of centralized companies. It achieves this by defining a general risk framework that the subDAOs (aka Stars) need to follow. This includes all kinds of offchain rules to cover many types of risk such as: smart contract risk, counterparty risk, credit risk, market risk, etc.

Within the rules of the risk framework, Stars can borrow as much USDS as they want to deploy into any opportunities available, provided the Star pays the “Base Rate” to Sky. This means all Stars retain 100% of the spread earned above the Base Rate.

Sky Base Rate

Having access to a large credit line is an extremely powerful thing. SparkLend was bootstrapped to the second-largest money market in less than a year because of this access. The Sky ecosystem opens up this access by allowing all the Stars to borrow as much as they want to. We will cover how risk is handled later, but for now, you can think of Stars as yield-seeking engines that will deploy as much capital as possible, provided the yield is higher than the Base Rate.

So how is the Base Rate determined? You can think of it similar to a Compound-style utilization rate curve, but covering the entire balance sheet instead of just one asset. Assets that count as Actively Stabilizing Collateral (ASC) are things like USDC and USDT which have strong onchain liquidity. These assets are treated as reserve cash to maintain the peg.

The rule for the Base Rate is if the utilization is below 75% (ASC is 25% or higher) then decrease the base rate every X time interval. The magnitude of the decrease depends on how far away from 75% the balance sheet is. Similarly, if utilization is above 75%, then the Base Rate will tick upwards over time.

While this is not precisely true, as the Base Rate goes down or up slowly over time rather than having immediate effects, the effect will mirror the above curve due to market forces.

Let’s run over some examples to see why this is the case:

Scenario 1: Base Rate is below T-Bill rate

If the Base Rate is below the T-Bill rate, then all Stars are incentivized to mint as much USDS as they can and deploy it into T-Bill products such as BUIDL or others. There is virtually infinite capacity in treasury bills so the Stars will capture any positive spread. This feedback mechanism ensures that there is a Base Rate floor at around the USD risk-free rate.

Scenario 2: Base Rate is above T-Bill rate

This is the most common case and the one we are currently in. At the time of writing, the Base Rate at 5.05% and so deploying into T-Bill products has a negative spread. In this case, Stars will compete to allocate to the best spread available up to around the 75% utilization mark. Interestingly, this has already happened just a few weeks in!

See the screenshot below. Market forces are keeping the ASC just above 25% so utilization is just below 75%.

Stars do not want to go above this number because the Base Rate will increase, but a competitive marketplace keeps this number around 75% with the Base Rate settling at just below the undifferentiated yield threshold.

Sky Risk Framework

Stars can deploy into many opportunities, but not everything is of equal risk. For example, an unsecured loan generally carries more risk than a secured one. To account for these differences in risk, Sky requires Stars post junior capital to cover any potential losses. This puts the Star’s equity at risk for every decision, so they have skin in the game.

As shown in the screenshot above, the “% of Exposure” is the junior capital requirements. For Ethena, the Star is required to put up 3m USDS as first-loss to cover every 100m of Ethena exposure.

This exposure comes entirely from “Financial RRC” which means it is based on things like counterparty risk, market risk, and credit risk. “Admin RRC” comes from things like multisigs with arbitrary control over the protocol. “SC RRC” comes from smart contract safety — things like code complexity, audits, Lindy, etc.

As expected, Ethena carries a higher risk than crypto lending. Within crypto lending, you can see that onchain (SparkLend) carries a lower risk in general than something offchain (Maple).

Note: the above numbers are a work-in-progress and subject to change as the risk framework evolves.

Spark Revenue Sources

As of July 1st, 2025, Spark and Grove became financially autonomous. With a one-time capital injection of $25 million from Sky, both Stars are now responsible for generating their own revenue and managing their operations without additional funding from Sky.

Spark earns revenue in 3 ways.

1. Spark Liquidity Layer

The Spark Liquidity Layer (SLL) currently generates the largest amount of revenue at ~51m USD annually (note: Ethena revenue is split between Spark and Grove). It earns this primarily from a mix of SparkLend, Ethena, Maple, and Coinbase (labelled Morpho - USDC).

This revenue is calculated by taking the yield generated by the protocol and deducting the Base Rate paid to Sky. Typical bull market spreads are around 1% for SparkLend, 2-3% for Crypto Lending, and 5%+ for Basis Trade.

2. Spark Savings

Sky also runs a longer-term program called the Accessibility Rewards program, which rewards Stars for finding new users to deposit USDS. Stars earn 0.2% (0.6% until the end of 2025) on the TVL placed into deposits. While this amount is initially lower than SLL revenue, it is a sustained long-term revenue source for Spark.

Spark is already earning 6.4m / year from this program by facilitating ~1.8b in deposits to sUSDS.

3. SparkLend

Finally, SparkLend also generates revenue for Spark on the reserve factor inside the market. This is included in SLL revenue above for USD markets, but ETH is another market that is heavily utilized with over $1 billion USD of outstanding loans.

Sky and Star Flywheel

You can think of a Star as a machine that converts undifferentiated yield sources into benefit for sUSDS holders. The Sky Savings Rate is anchored to be 0.3% below the Base Rate. This means that the margin for Sky is 0.1% (after the accessibility reward incentive of 0.2%). The structure of the system ensures that Stars can be successful, but they need to find unique differentiation and keep innovating.

This system provides some very positive feedback loops that provide users with confidence in sUSDS’s multiple sources of yield while giving Stars a robust set of tools to start on third base if they find a differentiated business line.

Spark’s Long-Term Differentiation

So what are the differentiators for Spark? It’s important to note that Stars will be more ‘divide and conquer’ to start, but here is where some long-term moats exist today.

1. SparkLend

SparkLend is the second-largest money market in DeFi with ~$7 billion in total deposits. Other Stars are free to tap into SparkLend’s liquidity, but they need to pay reserve factor fees to Spark for the privilege.

The biggest differentiated factor is that SparkLend is home to the second-largest amount of ETH in lending markets, with over $1 billion in total deposits.

2. Spark Savings

Spark has its own vault called sUSDC as a wrapper on top of sUSDS. sUSDC is the largest holder of sUSDS at 325m on mainnet. Similar vaults will soon be deployed to do the same thing for USDT — offering 1:1 liquidity to USDT with yield-generation via the SLL.

3. Brand

Spark is an emerging, globally-recognized brand. The Spark brand stands for transparency and individual empowerment. It aspires to drive the future of decentralized finance and tradfi forward by making finance and capital accessible to all, including both retail and institutions seeking stable, reliable, and trustworthy yield and lending options.

4. More to Come

Spark has some big announcements coming over the rest of 2025.

Fully Onchain Loans, Seamless UX

The borrowing process is simple: users select their collateral, review terms, and receive USDC into their account in just a few clicks. Everything runs onchain through Morpho, while Coinbase retains full control of the user experience.

Spark supplies the liquidity, making funds available when users borrow. Repayments are flexible, and rates remain competitive thanks to the efficiency of onchain execution.

Elastic, Programmatic Liquidity

Spark acts as the liquidity engine behind this integration. Through the Spark Liquidity Layer, capital flows programmatically where it's needed, without intermediaries..

Liquidity is elastic: as demand grows, Spark can allocate more USDC into Morpho markets. This ensures scalability and makes it possible for institutions to offer lending products at size.

This approach has proven effective. Since launch (January 2025), allocated USDC has grown rapidly, reaching over $600 million and continuing to climb:

The chart shows consistent and accelerating demand for onchain loans powered by Spark. It’s a clear signal of product-market fit and infrastructure reliability.

Any Platform Can Build This

This model is modular: Morpho provides the lending protocol, Coinbase delivers the user experience, and Spark powers the liquidity.

Other exchanges, wallets, or fintechs can adopt the same approach. Build the front end, integrate with an open protocol like Morpho, and tap into Spark for deep, reliable capital.

Spark is here to power the next generation of onchain financial products, securely and at scale.

Now, Spark is proud to announce that it is live on both Optimism’s OP Mainnet and Unichain, laying the liquidity foundation for the next phase of Ethereum’s evolution: the Superchain.

But this isn’t just another deployment. It’s a coordinated strategy in partnership with the Optimism Collective to make native interoperability real — turning the fragmented L2 landscape into a unified and composable financial system.

Based on the momentum and learnings from Base, Spark is ready to scale with the Superchain.

Spark launches on Unichain & Optimism Mainnet

Spark has expanded to Optimism’s OP Mainnet and Unichain, bringing savings yield to USDC and USDS, and establishing foundational liquidity infrastructure through the Spark Liquidity Layer (SLL).

This deployment includes the launch of sUSDC and sUSDS. sUSDC is a yield-bearing representation of USDC. Users can directly deposit USDC into the USDC Savings Vault and receives sUSDC, which accrues yield based on the Sky Savings Rate (SSR), currently set at 4.5% by Sky governance. This rate reflects returns from over-collateralized DeFi loans and real-world investments. You can track it in real-time here: https://data.spark.fi/savings. sUSDC can be redeemed at any time for the underlying USDC plus earned yield. There are no additional fees, and users may withdraw up to the available amount in Sky reserves, which currently total $2.61 billion. While sUSDS is a yield-bearing representation of USDS. Users can deposit both USDS and USDC into the USDS Savings Vault and receive sUSDS, which similarly accrues the yields based on the SSR.

In parallel, Spark brings liquidity to the system through the Spark Liquidity Layer. Ensuring that users can always exit their positions in sUSDC and sUSDS with immediate settlement and no slippage.

On Unichain, Spark introduces a new use for the ~$150M of USDC liquidity already present on the network. sUSDC gives holders a native way to earn yield on their stablecoins while keeping their capital composable across lending markets, savings vaults, and DEXs. For both Optimism and Unichain, Spark brings stablecoin yield and collateral efficiency without requiring users to bridge or leave their chain.

Why sUSDC Matters

sUSDC represents a fundamental evolution of the centralized stablecoin model, specifically USDC. Unlike traditional stablecoins such as USDC, sUSDC natively accrues yield. This enables users to supply yield-generating collateral directly into lending protocols like Euler, unlocking improved capital efficiency from the outset.

Key advantages of sUSDC:

1. sUSDC functions as a dual-purpose asset. It generates yield while simultaneously serving as productive collateral within DeFi applications.

2. Its design simplifies user experience. There is no need to wrap, stake, or interact with external protocols to activate yield — the accrual is native and composable across the ecosystem.

3. It also aligns with growing liquidity on Unichain. As integrations deepen between sUSDC, USDT0, and other yield-capable stable assets, composability is preserved across lending markets, DEXs, and collateral frameworks.

The initial integration with Euler marks sUSDC’s entry into Unichain’s lending ecosystem. This sets the foundation for a more unified DeFi environment, where users can mint, save, borrow, and swap using yield-generating collateral — all without requiring complex or fragmented workflows.

A Strategic Alliance: Spark & the Optimism Collective

Spark and the Optimism Collective are joining forces with a shared vision: to accelerate the growth of the Superchain — a network of chains that functions as a unified, composable ecosystem.

Optimism is contributing 2 million OP tokens to support aligned ecosystem growth. In parallel, Spark brings its core infrastructure and capital efficiency engine to the table - activating liquidity and delivering savings yield to USDC and USDS holders across the Superchain.

Spark is already live across OP Mainnet and Unichain with the following incentives rolling out:

• Spark Savings already live on both chains  — earn Spark Savings yield and OP rewards on sUSDC in app.spark.fi

• Superstack XP incentives (launching soon):

  • Providing liquidity & trading sUSDC/USDT0 on Velodrome (OP & Unichain)

  • Providing liquidity & trading sUSDC/USDT0 on Uniswap V4 (Unichain)

• Ecosystem Reward Programs (launching soon):

  • Velodrome’s rewards specifically for sUSDC/USDT0 pool on Unichain

  • Euler’s rewards for using sUSDC as collateral and borrowing USDT0

Timelines for these upcoming rewards will be announced on @sparkdotfi.

Spark’s Vision

Spark is building the liquidity layer for a unified, chain-abstracted Ethereum — where capital moves freely, applications compose across chains, and users access yield without friction.

As part of our Superchain rollout, Spark is partnering with the Optimism Collective to implement native interoperability — the core infrastructure that enables single-block, cross-chain message passing across Superchain L2s.

The infrastructure will unlock:

• Assets like sUSDC, sUSDS and USDS can move cross-chain with native mint/burn mechanics

• Protocols can compose across chains, integrating Spark liquidity from any Superchain L2

• Apps can tap Spark’s savings, liquidity, or PSM modules, regardless of chain origin

Launching soon, native interoperability will allow users to deploy capital on one chain and earn yield on another, this will unlock new possibilities across the DeFi space, and Spark is ready to power the liquidity revolution on Day 1.

This is how we scale Ethereum: not one chain at a time, but all at once.

Spark is where it begins.

The job’s not done.