Currently, the DeFi fixed income sector is mired in a deadlock of 'linkage failure': high-quality assets (such as tETH, on-chain government bonds) find it difficult to accurately match high-demand scenarios (such as institutional cross-border collateral, retail short-term arbitrage), leading to asset idleness; scenarios cannot dynamically adjust rules based on user demand (such as institutions needing compliance processes, retail investors needing low-threshold operations), resulting in a fragmented experience; users cannot find a matching combination of 'asset characteristics - scenario functions - their own needs', and can only passively accept a 'one-size-fits-all' fixed income solution. Most protocols only focus on 'asset supply' or 'scenario building', but overlook the linkage value of the three. TreehouseFi innovatively constructs the 'Fixed Income Triangular Value Resonance Network (TVRN)', enabling assets, scenarios, and users to form a 'mutually empowering, value multiplying' resonance effect through 'dynamic asset scenario adaptation, reverse asset activation of scenarios, dual-end driven user demand', aligning with the industry trends of institutionalization and RWA scenario diversification while reconstructing the traditional logic of 'unidirectional supply' in DeFi fixed income.
I. Dynamic asset scenario adaptation: From 'fixed attributes' to 'scenario-specific characteristic adjustments'
TreehouseFi's TVRN network's first breakthrough lies in breaking the limitations of 'asset attribute solidification'—through 'smart contract characteristic modules', allowing the same asset to automatically adjust core attributes (collateral ratio, liquidity, yield structure) when entering different scenarios, ensuring precise matching of assets and scenario needs, avoiding the problem of 'assets being useful in scenario A but useless in scenario B'.
Its technical core is the 'dynamic adjustment contract for asset characteristics', taking tETH and on-chain government bonds RWA as examples:
1. tETH's cross-scenario characteristic adaptation:
◦ When entering the Aave lending scenario, the contract automatically raises the collateral ratio of tETH from the base 92% to 95% (as Aave requires highly liquid collateral), while closing the 'long-term locked income' function and opening the 'borrow and repay anytime' feature;
◦ When entering the Pendle derivatives scenario, the collateral ratio is adjusted back to 88% (the derivatives scenario needs to control risk exposure), automatically splitting the 'base staking income' and 'interest rate volatility income'—the former belongs to the user, and the latter is used for derivatives margin. Users can obtain an additional 0.3% scenario subsidy by bearing a small interest rate risk;
◦ When entering the RWA collateral scenario, the collateral ratio is fixed at 90% (the collateral scenario needs to balance safety and efficiency), while activating the 'cross-chain collateral confirmation' function, automatically synchronizing the on-chain holding records of tETH to traditional custody systems (e.g., Fireblocks), meeting institutional compliance requirements.
2. Scenario adaptation of on-chain government bonds RWA:
When a 1-year on-chain government bond enters the 'retail investment scenario', the contract automatically splits into 'fractal assets of $100 each', supporting 'T+1 redemption'; when entering the 'institutional allocation scenario', it automatically merges into 'standardized assets of $100,000 each', closing the fragmentation function, while opening 'quarterly interest payment automatic transfer' (interest directly transferred to the institution's designated custody account); when entering the 'cross-border settlement scenario', the 'credit endorsement' feature is activated, and the cash flow records of the underlying assets of RWA are automatically synchronized to the SWIFT system, which can serve as collateral for cross-border trade.
This dynamic adaptation increases asset utilization by 40%: a certain arbitrage institution circulates 10,000 tETH among Aave (lending), Pendle (derivatives), and RWA collateral scenarios, with the characteristics automatically adjusted, raising the comprehensive annualized yield of tETH from a single staking of 5.0% to 5.8%, without incurring additional operational costs.
II. Scenario reverse asset activation: From 'passive reception' to 'active mining of asset value'
The second capability of the TVRN network is to prevent scenarios from passively receiving assets, but instead actively mining the potential value of assets through a 'demand trigger mechanism' (such as splitting liquidity units, activating ecological rights), forming a positive cycle of 'scenario demand → asset value release → scenario attractiveness enhancement'.
For institutional scenarios, reverse activation focuses on 'compliance value mining':
TreehouseFi collaborates with Goldman Sachs to establish an 'institution-level RWA allocation scenario'. When the scenario detects that an institutional user has a 'low-risk allocation demand of $100 million with a 6-month term', it will proactively trigger two asset activation actions:
1. Splitting the 'time liquidity unit' of tUSDC—splitting the $100 million tUSDC held by the institution into '4 units of 15 days + 2 units of 90 days', with 15-day units used to capture short-term interest rate peaks (e.g., a certain week the USDC interest rate on Arbitrum reached 6.2%), and 90-day units locking in long-term stable returns (e.g., 3.5% short-term bond RWA);
2. Activating the 'credit stratification' feature of on-chain government bonds RWA—splitting the credit rating of the underlying bonds (e.g., AA+) into 'senior (90% principal, annualized 3.2%)' and 'subordinated (10% principal, annualized 4.8%)', allowing institutions to choose allocations based on risk preferences. A certain institution chose 80% senior + 20% subordinated, achieving a comprehensive annualized yield of 3.4%, while meeting its 'risk tolerance ≤ 1%' requirement.
For retail scenarios, reverse activation focuses on 'low-threshold value release':
The 'retail small arbitrage scenario' detects that a user's average holding is only $500, actively activating the 'small aggregation arbitrage' function of tAssets—aggregating $500 tUSDC from 100 users into $50,000 to participate in large lending arbitrage on Arbitrum (interest rate difference 0.5%, individual users cannot participate), with arbitrage profits distributed proportionally after deducting a 0.05% service fee, resulting in an average additional monthly income of $1.2 per user, three times higher than individual operation. At the same time, the scenario automatically closes 'complex parameter settings', retaining only the 'one-click participation/exit' button, reducing new user onboarding time to 2 minutes.
III. User demand driven from both ends: From 'unidirectional supply' to 'demand defining assets and scenarios'
The ultimate value of the TVRN network lies in making user demand the core driving force behind asset adaptation and scenario adjustments—through 'dual-end synchronization of demand profiles', user demand guides asset adjustment characteristics while driving scenario optimization rules, forming a closed loop of 'user demand → asset adaptation → scenario adjustment → meeting demand'.
Its implementation path relies on the 'user demand hub' and 'dual-end synchronization contract':
1. Precise collection of demand profiles:
◦ Institutional users connect their own asset management systems via API, uploading demand parameters such as 'risk tolerance (e.g., ≤0.8%), liquidity requirements (e.g., T+3 redemption), compliance standards (e.g., MiCA registration)';
◦ Retail users generate 'risk preferences (conservative/aggressive), idle fund duration (7 days/30 days), operating habits (one-click operation/custom strategy)' tags through 'demand questionnaires + on-chain behavior analysis', and the profile data is verified on-chain by Chainlink Oracle to ensure authenticity and reliability.
2. Demand-driven dual-end adjustment:
◦ Driving asset adjustments: When the demand of a European pension fund (risk ≤ 0.8%, T+3 redemption) is synchronized to the asset side, tUSDC automatically closes the 'high-risk cross-chain arbitrage' feature, retaining only the 'current income + short-term bond RWA' combination, while locking the redemption cycle to T+3 to avoid liquidity risk;
◦ Driving scenario adjustments: When the needs of a retail user (aggressive, 7 days idle, one-click operation) are synchronized to the scenario side, the 'cross-chain arbitrage scenario' automatically filters arbitrage strategies with '7-day period, risk ≤ 2%', hiding complex parameter settings (such as cross-chain gas fee optimization, interest rate difference monitoring), allowing the user to complete the entire process from asset transfer to profit receipt with a click of 'one-click participation'.
This dual-end drive increases the user demand satisfaction rate from the industry average of 65% to 92%: a certain retail user's '7-day aggressive' demand is matched through TVRN to the 'tETH cross-chain arbitrage to Mantle (7-day cycle, annualized 6.1%)' asset-scenario combination, with the actual yield deviating only 0.1% from expectations; a certain institution's 'MiCA compliance + $100 million 6-month allocation' demand is matched to the '80% tUSDC (compliance custody) + 20% EU short-term bond RWA' combination, fully meeting its risk control requirements.
IV. Trend Adaptation: Anchoring 'Institutional Scenario Customization + RWA Scenario Diversification'
Currently, the DeFi fixed income sector is presenting two core trends: institutions are no longer satisfied with 'generic scenarios', but require 'customized processes and rules'; RWA is extending from a single 'holding and earning' scenario to diversified scenarios such as 'collateral, settlement, derivatives', with the TVRN network continuously enhancing its triangular resonance capability through targeted iterations.
In terms of institutional scenario customization, TVRN has introduced 'institution-exclusive scenario templates':
Customized scenario templates are developed for three types of institutions: family offices, sovereign funds, and multinational asset management—
• Family office template: Supports 'multi-account permission hierarchy (e.g., analysts can only view, investment managers can operate)' and 'asset portfolio confidentiality (only core members can see holdings)', automatically closing 'on-chain holding disclosure' during asset adaptation;
• Sovereign fund template: Connects to the central bank's regulatory system, requiring real-time synchronization of regulatory data for asset circulation (e.g., cross-chain, staking). Hard requirements such as 'single transaction limit (e.g., $50 million)' and 'risk reserve ratio (no less than 10%)' are embedded in the scenario rules. A Middle Eastern sovereign fund configured a $300 million tAssets + RWA portfolio on the TVRN network through this template, with the operational process fully aligned with its internal risk control system, reducing compliance costs by 70%.
In terms of diversifying RWA scenarios, TVRN expands the 'RWA Scenario Matrix':
New 'RWA derivatives scenarios' and 'RWA cross-border settlement scenarios'—
• RWA derivatives scenario: Based on the coupon rate of on-chain government bonds, 'interest rate swap contracts' are developed, allowing users to convert RWA fixed income into floating income (linked to DOR benchmark) through TVRN, or vice versa. A US asset management firm used this scenario to hedge against interest rate volatility risk, reducing the volatility of the RWA portfolio from 2.1% to 0.9%;
• RWA cross-border settlement scenario: In collaboration with DBS Bank in Singapore, on-chain government bonds are used as 'intermediate collateral assets' for cross-border trade, allowing TVRN to automatically complete the full process of 'RWA ownership confirmation → cross-border collateral registration → asset unlocking after settlement', reducing the settlement time from the traditional 5 days to 8 hours, and the handling fee from 1.5% to 0.3%.
Conclusion: From 'unidirectional supply' to a new paradigm of fixed income 'triangular resonance'
TreehouseFi's TVRN network essentially upgrades DeFi fixed income from a 'unidirectional system driven by assets or scenarios' to a 'resonance system where assets, scenarios, and users empower each other'—assets are no longer 'tools with fixed attributes', but 'value carriers' that can be dynamically adjusted according to scenarios; scenarios are no longer 'passive containers for receiving assets', but 'activation platforms' that can actively mine value; users are no longer 'passive participants accepting solutions', but 'core drivers' defining system rules. This model not only addresses the current pain points of linkage failure but also accurately aligns with the trends of institutional scenario customization and RWA scenario diversification, opening a channel for DeFi fixed income to achieve 'large-scale institutional entry and popular scenario penetration'.
As global fixed income digitalization accelerates, 'triangular resonance' will become the core standard for measuring fixed income infrastructure: it is not just a simple 'asset + scenario' combination, but reconstructs the value creation logic of DeFi fixed income—1 asset in a resonance system can release double the value of a single scenario; 1 scenario in a resonance system can attract three times the number of users compared to traditional models. In this process, TreehouseFi will not only capture the industry growth dividend but also promote the upgrade of DeFi fixed income from 'financial tools' to 'value collaborative ecosystems', providing key support for the maturity and development of the entire industry.
