Currently, the DeFi fixed income sector faces two key pain points that restrict ecological risk resistance and user stickiness: first, the lack of asset scenario resilience; most projects' tAssets and RWA can only passively endure shocks during scenario fluctuations (such as sudden market interest rate changes, regional policy adjustments, and short-term risks of underlying assets), lacking proactive resilience mechanisms— for instance, when interest rates suddenly rise in regional lending scenarios, tUSDC cannot quickly adjust its liquidity buffer strategy, leading to user redemption congestion; when short-term cash flow fluctuations occur in RWA underlying assets, there are no dynamic compensation tools, directly harming user returns and weakening asset risk resistance in scenarios; second, users' co-creation efficacy is low, with lengthy co-creation processes in similar projects (averaging 1-2 months from topic initiation to implementation) and a lack of quantitative assessment of user contributions, leading to 'high input low return'— quality rule suggestions submitted by users cannot be implemented quickly due to cumbersome processes or lack clear feedback after implementation, gradually dampening co-creation enthusiasm and making it difficult to form a continuous participation loop.
TreehouseFi breaks away from the traditional framework of 'adaptation + co-creation', strengthening ecological risk resistance through 'asset scenario resilience construction' and activating user participation value through 'user co-creation efficacy enhancement', creating a new DeFi fixed income ecosystem that combines 'risk resistance resilience' and 'participation vitality' through the coordination of two core systems.
1. Building asset scenario resilience: Ensuring assets remain 'stable' amidst scenario fluctuations
TreehouseFi abandons the traditional model of 'passively enduring risk' and designs three core mechanisms around 'resilience' from three dimensions: risk prediction, dynamic buffering, and continuous optimization, enhancing the asset's risk resistance in scenarios and ensuring user experience and asset value stability in fluctuating environments.
1. Dynamic adjustment pool for resilience parameters
The project builds a 'resilience parameter pool' for core scenarios (regional lending, cross-border RWA allocation, green asset investment), linking core asset parameters (liquidity buffer ratios, income compensation coefficients, elasticity ranges of collateral rates) with scenario risk indicators (interest rate volatility, policy sensitivity coefficients, risk levels of underlying assets) for real-time dynamic adjustment:
• In regional lending scenarios, the resilience parameters of tUSDC are linked to the 'regional interest rate volatility': when the daily interest rate fluctuation exceeds 1.5%, the resilience parameter pool automatically adjusts the liquidity buffer ratio of tUSDC (from 15% to 25%), while activating the 'income compensation coefficient'—for users holding positions for over 30 days, an additional 0.2% annualized return subsidy is provided to hedge against interest rate fluctuations;
• In cross-border RWA scenarios, the resilience parameters of RWA are linked to the 'target area policy risk index': if the policy risk index rises to the warning threshold, the flexibility range of RWA collateral rates is automatically expanded (adjusted from 1.2-1.5 times to 1.1-1.6 times), allowing users to flexibly adjust their collateral ratios according to risk preferences;
• The adjustment logic of resilience parameters and the data sources of risk indicators (such as interest rate data from compliant financial platforms, policy risk indices from third-party risk control institutions) are all publicly disclosed, with parameter adjustment records being chained in real time, allowing users to trace through an on-chain dashboard.
2. Dynamic buffer tools for scenario risks
In response to sudden risks in scenarios (such as liquidity gaps in tAssets and short-term default risks of underlying RWA assets), the project designs a 'Dynamic Buffer Toolkit' that includes three types of tools: liquidity supplementation, income compensation, and risk diversification, which can be quickly activated when risks occur:
• Liquidity buffer tools: When tAssets experience a peak in short-term redemptions, automatically call upon the 'cross-scenario liquidity pool' (collecting idle tAssets from various scenarios) to supplement the quota, while temporarily opening the 'RWA collateral quick exchange' function— users can quickly exchange RWA collateral for tAssets to alleviate redemption pressure;
• Income buffer tools: When short-term income fluctuations occur in the underlying RWA assets, activate the 'income smoothing fund' (accumulated from 10% of various scenario asset service fees) to supplement user income differentials, ensuring that monthly income fluctuations do not exceed 0.3%;
• Risk diversification tools: For cross-border RWA, support users in diversifying collateral across multiple regional RWA asset pools, so that when a specific regional RWA faces risks, only a portion of the collateral is affected, reducing the impact of single risks on users;
• The initiation conditions, funding sources, and usage rules of the buffer tools are all solidified through smart contracts, requiring no manual intervention, ensuring a 'second-level response' when risks occur.
3. Continuous testing and optimization of resilience
The project will establish an 'Asset Scenario Resilience Testing Module', regularly simulating scenario risks (such as extreme interest rate fluctuations, sudden policy changes, and large-scale redemptions), optimizing resilience mechanisms based on testing results:
• Conduct 'Resilience Stress Tests' once a month, simulating different risk scenarios (such as a 3% single-day interest rate increase or redemption amounts reaching 5 times the usual), monitoring the speed of asset parameter adjustments, the effectiveness of buffer tools, and user income stability;
• Generate 'Resilience Optimization Reports' based on testing results to make targeted adjustments to mechanisms— for instance, if testing reveals insufficient liquidity buffers for tUSDC in a certain area, the coverage of cross-scenario liquidity pools can be expanded;
• Invite users to participate in 'resilience testing feedback', collecting user experience suggestions on risk response processes (such as whether redemptions are smooth, whether income compensation is timely), incorporating user feedback into optimization basis, ensuring that resilience mechanisms meet both technical logic and user needs.
2. Enhancing user co-creation efficacy: Enabling users to co-create 'high input high return'
TreehouseFi addresses the pain points of 'long co-creation processes and low efficacy' by designing an 'efficacy-oriented' co-creation system, enhancing the efficiency of co-creation from 'initiation to implementation' through three main methods: quantifying contributions, simplifying processes, and linking incentives, allowing user contributions and returns to be directly connected.
1. Quantitative assessment of co-creation contributions
The project develops a 'Co-Creation Contribution Quantification Model' to quantify users' co-creation behaviors (topic initiation, plan design, testing feedback, implementation promotion), avoiding 'vague contributions':
• Different co-creation behaviors correspond to different 'efficacy points': initiating topics that meet ecological needs earns 50 points, designing implementable plans (including specific parameters and execution steps) earns 100 points, participating in plan testing and providing effective feedback earns 30 points, and collecting user feedback after the plan is implemented earns 80 points;
• Efficacy points are linked to the quality of co-creation results: if the participation rate of the scenario increases by more than 10% after the plan is implemented or user satisfaction reaches 90%, participating users' efficacy points are additionally increased by 50%; if the plan does not achieve the expected results, only 60% of the base points are earned;
• Efficacy points are recorded in real time in user accounts, with details (such as which score comes from which co-creation behavior, quality assessment basis) available for review, ensuring quantitative transparency.
2. Rapid implementation channels for co-creation
The project builds a 'rapid co-creation implementation process', simplifying the steps from topic to implementation, shortening the average implementation cycle from 1-2 months to within 15 working days:
• Topic screening phase: Use a 'community preliminary screening + core user review' dual-process; after passing the preliminary screening (support rate exceeding 50%), complete the review within 2 working days to avoid lengthy discussions;
• Plan design phase: Provide 'standardized plan templates' (including parameter frameworks and key contract logic points), users only need to supplement key information, and the tech team simultaneously provides compliance and feasibility suggestions, shortening design cycles;
• Implementation testing phase: Establish a 'small-scale rapid testing' channel, inviting 20% of target scenario users to participate in testing, with a testing period not exceeding 3 working days, and directly implement after fixing issues;
• Set clear time limits for each segment; if co-creation projects are not advanced within the time limit, automatically trigger 'progress disclosure' to explain the reasons to the community, ensuring efficient processes.
3. Closed loop of co-creation efficacy incentives
The project establishes an incentive closed loop of 'efficacy points - rights - feedback', allowing users' co-creation efficacy to be directly transformed into actual value, forming a positive cycle of 'high efficacy → high returns → more active participation':
• The accumulation of efficacy points unlocks rights at threshold levels: 500 points unlocks 'priority review rights for co-creation topics', 1000 points unlocks 'revenue sharing rights after the plan is implemented' (able to receive 1% of the monthly service fee from the implemented scenario for 3 months), and 2000 points unlocks 'recommendation rights for asset resilience parameters';
• Real-time rights fulfillment: Unlocked rights can be directly activated in user accounts, such as 'revenue sharing rights' being automatically distributed to user wallets monthly, without the need for manual application;
• Regularly publish 'Co-creation Efficacy Reports' to publicly disclose user efficacy point rankings, rights fulfillment status, and co-creation outcomes, allowing users to clearly see the conversion path from 'efficacy → value', enhancing participation motivation.
3. Ecological collaboration and future directions
TreehouseFi forms a dual advantage of ecological risk resistance and participation vitality through the bidirectional linkage of 'asset scenario resilience construction' and 'user co-creation efficacy enhancement': resilience mechanisms improve the stability of assets in scenarios, attracting users for long-term allocation; users propose resilience optimization suggestions through efficient co-creation, feeding back into the asset resilience mechanisms to better align with scenario risk characteristics, further enhancing the ecological risk resistance.
In the future, TreehouseFi will focus on three major directions:
1. Expansion of resilience scenarios: Add new risk-characterized scenarios such as supply chain RWA and small micro-loans in county areas, enriching the dimensions of resilience parameters (such as industry chain risk coefficients and regional credit indices), improving targeted resilience solutions for different scenarios;
2. Upgrade of co-creation efficacy tools: Develop a 'Co-Creation Efficacy Assistant' that automatically matches users with suitable co-creation tasks (such as recommending topic directions based on users' historical contributions), providing intelligent suggestions for plan design, further lowering co-creation thresholds;
3. Transparency of ecological resilience: Improve the on-chain resilience data disclosure system, publicly disclose records of asset resilience parameter adjustments, buffer tool usage, and co-creation efficacy point calculations in real time, enhancing user trust and recognition of the ecosystem.
TreehouseFi fills the gap in the DeFi fixed income ecosystem's risk resistance capability with 'asset scenario resilience' and addresses the pain point of virtualized participation value with 'user co-creation efficacy', providing not only a new paradigm of 'risk resistance + high vitality' for the industry but also promoting the transformation of the DeFi fixed income sector from 'scale expansion' to 'quality improvement'.
