1. Abstract

2. Primer

3. Coverage Lifecycle

4. Stakeholder Interactions: Coverage Across the Stack

   1. Catalysis <> SSPs

   2. Catalysis <> CoverPool Curators (Llamarisk, Chaos Labs, etc)

   3. Catalysis <> Delegators (Restakers, LRTs)

   4. Catalysis <> Coverage Clients/Policy Holders (eg. DeFi Protocols)

   5. Delegators <> Curators

5. Examples: Lending, Yield-Bearing Stablecoins, & Vaults

   1. Reaching Equilibrium

6. Risks & Paths to Mitigation

7. Comparison to Legacy Onchain Insurance

8. Conclusion

DeFi has scaled into a global financial substrate, yet its insurance infrastructure remains weak and fragmented. Stablecoins, now exceeding $250B (mid-2025) with ~50% YoY growth, have become the de facto settlement layer across exchanges and payments, surpassing Visa and Mastercard in on-chain settlement volume. Tether ranks among the world’s top holders of U.S. Treasuries (around 7th globally by early 2025), while fintechs such as Stripe and Robinhood are standardizing on-chain dollar rails for payouts and wallets. This marks a durable shift toward programmable finance and with it, growing demand for programmable risk coverage. In this research piece, we will take an in-depth look at the Catalysis Coverage protocol, how it works, and its promise in rearchitecting onchain insurance.

Existing models rely on gated underwriting, idle and thin capital pools, and governance-driven claims, leaving systemic risks like smart contract exploits, oracle failures, stablecoin depegs, or liquidity spirals largely unprotected. Catalysis Coverage introduces a new design: restaked collateral, already abundant and slashable, is routed into curator-run CoverPools where premiums are competitively priced and claims (of any size) are settled deterministically through slashing. Thereby turning insurance from a static, governance-heavy process into a programmable market. Delegators look to earn yield for underwriting real protocol risk, curators monetize actuarial expertise, and protocols secure transparent, enforceable protection at lower cost than existing insurance solutions. The result is a scalable and permissionless coverage layer: auditable, composable, and capable of supporting not only DeFi protocols but the broader financial stack they anchor.

Since 2020, crypto platforms have lost an estimated $6–8B to exploits, according to a Chainalysis’ report. Over the same period, Nexus Mutual, by far the largest on-chain insurance protocol, has paid out just ~$18M in valid claims. That equates to a coverage ratio of roughly 0.2–0.3%, meaning over >99% of realized losses went uninsured. The gap underscores how marginal the on-chain insurance footprint remains relative to the scale of systemic risk.

DeFi has grown, beyond crypto, into a cornerstone of the financial economy, with billions locked across lending, stablecoins, and trading platforms. However, its insurance rails remain primitive and stuck: underwriting is gated, capital sits idle, pricing is static, and claims depend on slow governance procedures. The result is thin coverage, delayed payouts, and little confidence in protection, leaving systemic risks like liquidation spirals, exploits, stablecoin or derivative depegs, and oracle failures largely unaddressed.

Catalysis Coverage introduces an alternative. It channels restaked collateral into pools run by curators, where premiums are set competitively and faults trigger slashing to deliver fast, claimable protection. Instead of the current slow, shallow, and gated procedures, coverage becomes a highly-composable and programmable market: modular, auditable, and aligned with the needs of both protocols and underwriters.

The shared-security layer supplies deep collateral, Catalysis Core orchestrates premium flows and slashing execution, and independent curators design policies, set claim conditions, and split risk into junior and senior tranches. Delegators turn their capital more efficient by earning extra yield by underwriting real protocol risk, while protocols gain predictable, enforceable protection. The result is a friendly coverage layer—robust enough to insure a wide range of protocols in crypto.

Catalysis Coverage achieves optimized insurance through a structured worflow: buyers (policy holders) request cover, curators assess and price risk, delegators signal capacity, and premiums are escrowed with optional buffer deposits. Tranching aligns risk and returns, and, at maturity, premiums flow to delegators or are refunded if no claim is activated. If a claim is flagged and valid, the system executes slashing, swaps collateral into payout tokens, and pays the policyholder—seamlessly, in a single transaction.

• Request: A buyer-protocol requests cover from one or more CoverPools for protection, specifying how much coverage they want, for how long, and under what terms.

• Risk Assessment: The CoverPool Curator evaluates the request, models the risk, and sets the premium rate, coverage limits, and clear claim conditions.

• Capacity Signalling: After Curators request delegations from Catalysis Core, willing delegators back the policy by committing stake in advance, but funds do not move yet.

• Quote Publication: CoverPools publish quotes with rates, capacity, and expiry dates for the buyer to choose from.

• Binding: The buyer-protocol accepts a quote. The system validates all commitments and issues a Policy token, locking the agreement in place. This happens atomically: either all conditions are met, or nothing goes through.

• Premium & Escrow: When a policy binds, the buyer pays the premium upfront plus a refundable buffer deposit (RBD); platform and pool fees are taken immediately, and the remainder sits in escrow within Catalysis Core until maturity.

• Tranching: Coverage is split into junior (first-loss, higher return) and senior (protected, lower return but larger capacity) layers, by curators. Delegators choose which tranche to back, based on risk appetites.

• Maturity: If no claim occurs, the buffer deposit is refunded to the buyer and premiums are paid out to delegatos relative to their stake commitment.

• Claims: If the covered event occurs, the claim conditions are checked automatically. If valid, the buffer deposit is tapped first toward the payout as buyer skin-in the-game (deterring frivolous claims and abuse of coverage); then delegator stake is slashed according to tranche composition (junior first, senior later), converted into the payout token, and sent directly to the buyer, in a single transaction.

Catalysis Coverage introduces a coordination layer where four sets of actors—Shared Security Protocols (SSPs), Delegators, CoverPool Curators, and Coverage Clients—interact around the conversion of restaked collateral into structured insurance vehicle. The governing element is economics: premiums, yields, fees, and the credible guarantee of slashing. Coverage works only if these incentives balance into a sustainable, capital-efficient equilibrium.

SSPs such as EigenLayer, Symbiotic, and SatLayer act as capital reservoirs and slashing executors. Catalysis relies on these marketplaces to source collateral, attract delegators, and enforce objective claim payouts via deterministic slashing. The selection decision should hinge on carefully-considered SSP parameters, such as:

• Withdrawal latency → defines how quickly delegators can reclaim their stake once a policy term ends. Long withdrawal epochs introduce liquidity risk for delegators, shorter ones make coverage more attractive by lowering capital lock-in costs, while mismatched withdrawal epochs across SSPs add operational complexity and potential confusion.

• Collateral type → different collateral asset types carry different volatility and liquidity profiles. Volatile assets increase the tail-risk of undercollateralization, whereas stable collateral supports more predictable coverage economics. Protocols may favor or reject coverage depending on the mix.

• Slashing determinism → the credibility of Catalysis rests on the guarantee that valid claims are enforced without delay or governance disputes. SSPs with clear, automatic, and verifiable slashing logic ensure that premiums correspond to real protection, not discretionary promises.

For an extensive read of SSPs’ risk-profiling metrics, refer to:

Tokensight Research Hub

May 9

Restaking Protocols Infra Risk Framework V2

Expanding upon our initial risk framework for assessing the infrastructure risks of restaking protocols.

By engaging with Catalysis Coverage and directing idle restaked assets into CoverPools, SSPs unlock additional yield channels to themselves and their users: estimated to translate into 5–7% APY in senior tranches or 10–12%+ in junior tranches. The trade-off is duration risk: capital is to be locked through both policy term and SSP exit epochs. SSPs therefore earn not just fees, but also systemic utility and capital efficiency as the entities whose liquidity mechanics directly shape the economics of coverage.

By tapping into this system, curators further monetize their skills through fees and premium volume, but healthy returns depend entirely on performance. Their economics are shaped by both upside and downside dynamics:

• Low loss ratios → consistent underwriting discipline in defining the risks, the correct terms, and setting proper pricing builds trust with delegators, attracting more delegations and expanding pool capacity.

• Reputation effects → a strong record compounds into higher premium inflows, as protocols prefer curators with proven prudence and transparent claim handling.

• Mispricing risk → underpriced coverage exposes delegators to uncompensated slashing and triggers capital flight; overpriced coverage drives protocols away, collapsing demand.

Economically, curators face asymmetric incentives: the upside is persistent fee revenue from premium volume, while the downside includes fee clawbacks, bonding penalties, and reputational damage that can permanently impair their ability to attract delegations. This dynamic ensures that actuarial competence is continuously tested in an open market. Over time, Catalysis evolves into a coverage market for actuarial reputation, where only curators who consistently align delegator returns with sustainable premium levels thrive.

While Catalysis provides the middleware, curators supply the actuarial judgment and market differentiation that make coverage viable. Each CoverPool is stewarded by a single curator, responsible for the economic design of policies across three dimensions:

• Premium calibration → setting rates that balance attractive APY for delegators with affordable protection for clients, ensuring pools remain competitive while solvent.

• Tranche design → structuring junior (first-loss, higher yield) and senior (protected, lower yield) layers to attract different risk appetites and manage capital efficiency.

• Claim specifications → defining clear and objective terms that minimize disputes, enable instant settlement, and build trust. Well-designed specs not only protect delegators from ambiguous slashing but also attract demand from clients who value transparent, automated coverage over discretionary governance votes.

For Catalysis, attracting strong curators is central: they expand the breadth of coverage offerings, bring actuarial credibility, and generate premium volume that sustains the entire system. The more curators with differentiated expertise join, the more diverse the insurance market becomes, which increases adoption, deepens delegator yield opportunities, and entrenches Catalysis as the neutral coordination layer for on-chain insurance.

Delegators convert passive stake into programmable underwriting capital. They choose pools and tranches aligned with their risk tolerance:

• Junior tranches absorb first-loss exposure and target double-digit APY, but are most exposed to slashing.

• Senior tranches sit above junior buffers, earning lower but steadier yields (low- to mid-single digits).

Because premiums are escrowed at bind, yields are predictable if no claim is triggered. The fundamental inequality guiding delegation is:

If this inequality holds, delegators participate; if not, they rotate capital out. This equation possibly stands as the most important to get right within Catalysis’ ecosystem.

Delegators have the crucial role of liquidity providers for Catalysis’ system, that enforce pricing discipline through capital rotation. If risk is overpriced, clients exit; if it’s underpriced, delegators exit after suffering slashing losses. Their movement between pools creates a self-correcting filter: only CoverPools with sustainable economics retain capital. LRT protocols (Ether.fi, Renzo, Swell), acting as delegators, amplify this dynamic by routing restaked capital into diversified pools, pushing delegators toward risk-adjusted equilibrium across the system. The more pools with favourable economics, the more stake capacity Catalysis is able to source.

Protocols buy coverage to protect against explicit loss scenarios—such as depegs, bad debt, or liquidity shortfalls—by paying upfront premiums priced more competitively than legacy insurance models. Instead of locking capital in idle reserves, they pay only for the risk they request and might face. Pricing competition between curators pushes premiums lower, while transparency of claim specs and deterministic slashing by SSPs ensures that when coverage is needed, payouts are both credible and automatic.

The economic proposition is twofold:

• Capital efficiency → premiums replace large idle buffers, allowing balance-sheet capital to reallocate to productive activities across lending, liquidity provision, or growth.

• Credible protection → claim payouts are guaranteed on-chain through slashing, avoiding governance delays, subjective votes, or underfunded pools from existing, sub-optimal solutions.

From the demand side, premiums form the revenue stream sustaining the whole system. Market competition ensures differentiation:

• Well-audited and transparent protocols enjoy lower premiums, as curators perceive lower default or claim probability.

• Opaque or fragile protocols pay more, reflecting higher underwriting risk.

The disincentive is straightforward: if Catalysis premiums exceed the cost of simply holding excess reserves, protocols will walk away. Equilibrium demand therefore hinges on Catalysis consistently offering better economics and execution than alternatives. Self-insurance locks capital in idle buffers; legacy insurance exposes protocols to governance delays and disputed claims. Catalysis instead delivers deterministic enforcement, transparent pricing, and capital efficiency, making it the rational choice for Coverage clients as long as its premiums remain anchored to economic reality.

Delegators delegate capital only if curators demonstrate credible risk-return economics. They monitor loss ratios, claim histories, and fee structures. The ability to exit and redelegate is the ultimate equilibrium mechanism: if a curator misprices risk or fails to deliver sustainable returns, capital drains away regardless of reputation.

Curators take raw collateral and shape it into structured insurance products. Leveraging their expertise, they define policy scope, premium levels, tranche mechanics, and exclusions, abstracting such hurdles away from delegators. Their revenue depends on delegator trust and retention, making their performance inseparable from delegator profitability.

To illustrate how Catalysis Coverage functions in practice, we examine three archetypal DeFi settings: lending, yield-bearing stablecoins, and vaults. Each example highlights how coverage absorbs specific risks, enhances capital efficiency, and aligns incentives across protocols, delegators, and clients under different stress scenarios.

The lending visualization shows a stacked blue bar of collateral and Catalysis Coverage, and in green, the borrower’s loan amount and outstanding debt at three stages: T1 at loan inception, T2 midway into repayment, and T3 closer to maturity. The figure illustrates the sequence in which protection operates: collateral being the first-loss buffer liquidated in default, while Coverage activates only if liquidation proceeds fall short of the outstanding balance. This ensures that even in undercollateralized or volatile scenarios, lenders’ effective protection remains above the required threshold ($130M).

In lending, defaults unfold in two stages: the borrower’s collateral is liquidated to repay debt; if insufficient, a shortfall occurs leaving bad debt to be dealt with by the protocol. Catalysis Coverage does not substitute this process, as it is only activated if liquidation proceeds fall short of the outstanding balance, filling the residual gap to ensure lenders are repaid in full. Collateral remains the primary buffer, while coverage serves as a conditional shortfall backstop. Looking ahead, coverage could also be extended to smooth liquidation risk itself (e.g. auction underperformance or cascade dynamics), but its current scope is solely focused on shortfall absorption.

The visualization depicts this dynamic across three repayment timeframes. At T1, the borrower owes $100M with $90M of collateral posted, and purchases $50M of coverage to remain above the liquidation threshold ($140M > $130M). In case a default occurs, collateral liquidates for $90M and coverage pays the $10M shortfall. At T2 (after a $10M repayment), outstanding debt falls to $90M while collateral remains $90M. In this case, default would be fully covered by collateral, and coverage is not triggered. At T3, after another $10M repayment, debt is $80M but collateral’s NAV drops to $75M, due to liquidity stress or price volatility. The previously “overcollateralized” position now sits below the $130M threshold (75 + 50 = 125). Collateral is sold, a $5M shortfall surfaces, and Coverage absorbs that amount.

This sequencing highlights the efficiency gains of combining collateral and Coverage. Borrowers can post leaner collateral ratios (e.g. 90% instead of 140%) while still meeting lenders’ risk thresholds through conditional coverage. Claims can also be structured to vary across the loan term, aligning payout probabilities with amortization and market risk. When defaults occur, slashing fills the shortfall, converting delegator stake into payouts for lenders. Over time, this equilibrium reduces idle collateral requirements, preserves safety, and yields delegators a return commensurate with shortfall risk; thereby creating a lending system that is both more capital-efficient and more resilient.

The stablecoin visualization compares, in blue colours, asset-side protection (NAV plus reserves, topped with Coverage) against the constant liability of redeemable supply at $1, in green. The three scenarios T1 (Normal), T2 (Stress), and T3 (Near-Depeg) show how coverage operates as a safety buffer when asset backing falls toward or below liabilities.

On the asset side, NAV and reserves fluctuate with market conditions. At T1, NAV plus reserves comfortably exceed liabilities, so coverage remains unused. At T2, sharp market stress cuts NAV by 20%, and reserves help absorb part of the shock and coverage stands ready to activate if liabilities are threatened. At T3, as NAV continues falling, additional coverage is purchased: slashable delegated collateral is requested to restore balance and preserve the peg. This dynamic allows stablecoin issuers to run leaner reserves and earn peace of mind, relying on coverage for tail scenarios, while delegators earn premiums for underwriting systemic stability.

The overall economic balance is therefore strengthened. Issuers gain capital efficiency by reducing non-yielding reserve buffers, now supporting growth and yield generation. Holders gain confidence that the peg is protected even under stress. Delegators also see an increase in capital efficiency, however, may face correlated tail risk: slashing occuring in periods of systemic stress, when stablecoin liquidity wobbles. Premiums must therefore compensate adequately for rare but severe events. Across scenarios, the visualization shows how coverage smooths volatility in asset backing, ensuring withdrawals remain whole and transforming restaked collateral into a programmable peg backstop.

The vaults visualization places available liquidity (undeployed capital plus coverage) alongside outstanding withdrawal requests across three scenarios: T1 (Calm) under normal flows, T2 (Spike) during a sudden redemption surge and emergency coverage top-up, and T3 (Settle) when requests normalize but additional coverage is still drawn to restore balance. The bars illustrate how coverage supplements liquidity whenever user redemptions exceed what the vault can supply natively.

Vaults naturally suffer from liquidity mismatch: capital is often deployed into staked or longer-term strategies, yet users expect near-instant withdrawals. At T1, liquidity comfortably exceeds requests, so coverage remains unused. At T2, a market shock drives redemptions sharply higher while undeployed buffers are thin; here, coverage is activated, slashing delegator collateral and converting it into stable payouts to meet withdrawals. This mechanism prevents long queues, gated exits, or fire-sale liquidations of underlying positions. At T3, withdrawal pressure subsides, but coverage is again requested to refill liquidity to safe operating levels—ensuring vault confidence even after stress.

For vault operators, coverage substitutes for costly idle reserves: instead of holding excess liquidity that drags down yield, they pay predictable premiums to backstop spikes. For users, coverage guarantees timely redemptions and protects against the systemic risk of locked exits. For delegators, premiums generate steady yield, though exposure clusters in moments of correlated stress when multiple vaults may request payouts at once. Over time, equilibrium forms where vaults weigh the cost of premiums against the opportunity cost of holding idle liquidity, while delegators demand sufficient compensation for underwriting these redemption shocks.

At the core of Catalysis Coverage is the delegator’s calculus: does the premium yield earned from underwriting exceed the expected slashing loss from claims? This decision is captured by:

Delegators will only allocate to CoverPools when expected yield clears this hurdle, ensuring that premiums earned consistently outweigh the tail risk of slashing. To make this concrete: if the probability of a claim during a coverage term is 3% and the expected slashing loss is $5k, then the premium must be at least $150 for delegators to break even. Anything above that threshold produces net positive yield; anything below it makes participation irrational.

The case studies on lending, stablecoins, and vaults illustrate how this balance plays out in practice:

• Lending showed how coverage fills the shortfall gap between collateral liquidation and outstanding debt. The premium must price in the probability and severity of borrower default and of collateral health drawdown. Delegators gain only if yield exceeds the expected loss from such shortfalls, and protocols and borrowers buy coverage when the premium is cheaper than overcollateralizing or holding larger reserves.

• Yield-Bearing Stablecoins illustrated peg defense. NAV erosion under stress is offset by reserves and coverage top-ups. Premiums here must capture both the frequency and depth of stress scenarios. Delegators accept low but non-zero claim probabilities as long as premium flows cover the tail-risk of depegs, while issuers save versus hoarding idle reserves.

• Vaults highlighted liquidity mismatches, where withdrawal spikes exceed liquid assets and coverage bridges the gap. Premiums must track the likelihood of these sudden stresses. Delegators are safe only if the premium more than offsets expected payouts, while vaults benefit by reducing idle buffers without sacrificing user confidence.

Together, these cases converge on a single insight: equilibrium exists only when premiums accurately reflect both the frequency and severity of loss events. If premiums understate risk, delegators suffer uncompensated slashing; if they overshoot, protocols abandon coverage. The balance holds when (i) premium income scales with genuine protocol demand for solvency protection, and (ii) expected slashing losses remain contained through curator quality, diversification, and tranche structuring. When these two conditions align, delegators achieve net APY above alternatives, protocols secure cheaper protection than idle reserves, and curators sustain fee income without mispricing risk.

Along with the innovation unlocked, a few new risks emerge that must be addressed with thoughtful mitigation paths. These risks range from principal–agent misalignments between curators and delegators, to correlated exposure across pools, to oracle vulnerabilities. Managing them is essential for ensuring that the economics remain sustainable for every party.

• Principal–Agent Problem (curators vs. delegators): Curators set premiums and claim specs on behalf of delegators, while delegators ultimately bear the slashing risk. Misaligned incentives can push curators towards reckless underwriting in pursuit of yields.
  → Mitigations can include curator bonding (posting slashable collateral as skin-in-the-game), clawbacks or variable fee structures tied to pool loss ratios, and transparent on-chain audit trails and logs of quotes, exclusions, and claims.

• Delegator Economics: The system only works if premiums outweigh expected slashing losses from claims paid out. Delegators need both sustainable yield and confidence that their capital won’t be eroded by systemic mispricing.
  → Transparent modelling of claim probabilities, curator quality, vault isolation, and diversified delegation strategies are critical.

• Inter-SSP correlation: When operators or capital overlap across multiple SSPs, correlated failures can trigger systemic slashing, such as collateral devaluation or liquidation stemming from DeFi.
  → Exposing overlaps through metadata, setting concentration caps, rigorous risk evaluations, and monitoring cross-protocol price and collateral correlation are necessary safeguards.

• Vault overlap exposure: More than one vault may insure the same protocol or depend on the same oracle, creating hidden redundancy.
  → Dependency graphs, canonical pools, and automated alerts can reduce this double-counting risk.

• Systemic Correlation: Coverage pools may face simultaneous claims across distinct domains. If a stablecoin depegs, lending defaults spike, and vault redemptions surge at the same time, correlated stress can overwhelm coverage capacity and drain delegator collateral.
  → Mitigations might include cross-pool correlation modelling, capital buffers sized for tail-risk clustering, and dynamic tranche repricing that accounts for multi-domain stress exposure.

As covered in the beginning of this piece, legacy DeFi insurance protocols like Nexus Mutual, Sherlock, and Aave’s Safety Module laid the initial groundwork but remain constrained: gated access, slow governance-based payouts, heavy underwriter whitelisting, and limited capital efficiency and availability.

Succinctly, Catalysis Coverage embeds insurance principles directly into the restaking stack by using multi-SSP collateral, slashing enforceability upon claim activation, atomic one-transaction claims, and non-custodial stake, Catalysis Coverage ensures faster execution, curation, transparent risk attribution, and competitive pricing and buying powers; thereby evolving insurance from static, inefficient solutions into a dynamic, seamless market.

Below we presented a comprehensive breakdown of the working components of legacy insurance protocols, against Catalysis Coverage:

Catalysis Coverage shows that on-chain insurance can move beyond governance delays and vague guarantees to a disciplined equilibrium: premiums aligned with real risks, delegators earning sustainable yield, and protocols securing their solvency (and reputation) without idle funds. The examples of lending, stablecoins, and vaults reveal the same principle: coverage works only when yield, cost, and risk converge in balance. By thinking insurance anew and embedding this logic into the restaking stack, Catalysis turns insurance from a fragile add-on into a durable financial primitive, one that can scale resilience across DeFi.

Check Catalysis website and Twitter.

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