An Introduction to 3Jane
A New Unsecured lending Primitive
Executive Summary
This paper analyzes 3Jane—a new DeFi unsecured lending protocol recently funded by Paradigm—and compares it with established platforms like TrueFi, Maple, Goldfinch, and Clearpool.
Traditional DeFi lending has relied on overcollateralized loans, limiting access to borrowers without substantial crypto collateral. Existing unsecured lending protocols have mostly targeted institutional borrowers, using human-led credit assessments and legal recourse.
3Jane takes a different approach by offering real-time unsecured credit lines to a wider borrower base—including DeFi users, small businesses, and on-chain entities like DAOs and AI agents. It uses its algorithmic 3CA model, combining on-chain activity and off-chain financial data to recalibrate credit limits and risk premiums every 30 days. The system features a dual-tranche lending pool, dynamic default risk management, and privacy-preserving data integrations.
This paper highlights both risks—such as borrower heterogeneity, reliance on collections agencies, and dynamic algorithmic recalibration—and opportunities, including potential credit expansion to productive but asset-light borrowers.
Key areas to watch as 3Jane matures:
Effectiveness of default management and risk pricing
Adoption by retail and small business borrowers
Impact of dynamic recalibration on borrower behavior and market stability
Whether algorithmic underwriting can outperform human-led assessments
If 3Jane successfully identifies profitable unsecured lending candidates, it could lay the groundwork for a new credit sector in DeFi—broadening beyond asset-based collateral to include cash-flow and data-driven lending signals, and expanding DeFi’s relevance to real-world economic activity.
What is 3Jane and How Does It Work
Overview
3Jane is a new credit-based money market protocol enabling real-time, unsecured credit lines for DeFi users, small businesses, and on-chain entities like DAOs and AI agents. Unlike traditional DeFi lending, which requires overcollateralized loans, 3Jane aims to unlock capital-efficient, unsecured lending through a data-driven underwriting approach that blends on-chain and off-chain information.
Key Features of 3Jane
Real-Time Unsecured Credit Lines
3Jane enables borrowers to access real-time USDC credit lines without posting collateral. Credit limits are determined based on a holistic financial profile that goes beyond existing asset holdings.
Hybrid Underwriting Model
The protocol’s underwriting algorithm, 3CA (3Jane Credit Risk Algorithm), combines:
On-chain data: DeFi activity, protocol interactions, transaction history, and crypto assets across multiple EVM networks.
Off-chain data: Bank account cash flow data (via Plaid), centralized exchange balances, and traditional credit scores (via Credit Karma and VantageScore).
This hybrid model is novel in DeFi, leveraging zero-knowledge proofs (zkTLS) to preserve privacy while ensuring data authenticity.
Dynamic Credit Limits & Risk Premiums
Borrower credit lines, interest rates, and repayment terms are dynamically recalculated every 30 days based on updated financial data. Borrowers’ future cash flows, DeFi positions, and credit histories shape these risk-adjusted parameters.
Dual-Tranche Lending Pool
Lenders in 3Jane can participate through:
USD3: Senior tranche (85% of the pool), priority access to interest repayments.
sUSD3: Subordinate tranche (15%), higher yield but absorbs first-loss risk.
This structure mirrors traditional structured credit markets, offering different risk-return profiles to lenders.
Credit Slashing & Collections
To manage defaults, 3Jane reduces credit scores for missed payments, shares late fees with performing borrowers, and auctions bad debt to licensed U.S. collections agencies.
Borrower Flow
Borrowers connect their crypto wallet and bank account using secure OAuth integrations (e.g., Plaid). 3Jane’s zkFetch technology gathers real-time bank balances, historical cash flow data, and credit bureau scores without revealing sensitive raw data on-chain. The 3CA algorithm analyzes this data—along with DeFi transaction history—to calculate personalized credit lines and interest rates. Borrowers can draw USDC instantly, with interest accruing only on drawn amounts and repayments recalculated monthly based on updated data.
Lender Flow
Lenders deposit USDC into the 3Jane pool to mint USD3 or stake for sUSD3. Idle liquidity earns Aave yield until borrowers draw funds. When deployed, lenders earn borrower-specific risk premiums. USD3 holders have priority in repayments and redemptions, while sUSD3 stakers capture higher yields in exchange for assuming first-loss risk.
The Current On-Chain Credit Environment and How 3Jane Compares
State of On-Chain Credit in DeFi
The on-chain credit landscape can be broadly divided into two categories:
Overcollateralized lending protocols, such as Aave and Kamino, which rely on borrowers posting crypto collateral worth significantly more than the borrowed amount to secure the loan. This model prioritizes lender security but inherently limits capital efficiency and access to credit for asset-light or emerging borrowers.
Uncollateralized lending protocols, which seek to extend credit without requiring posted collateral. These include TrueFi, Maple Finance, Goldfinch, and Clearpool, each adopting a slightly different approach to borrower vetting and credit extension.
The unsecured lending segment of DeFi remains relatively small compared to overcollateralized markets. While it addresses a clear need for flexible working capital and fills certain gaps (e.g., funding for trading firms, off-chain real-world asset lending), its reach has been constrained by several common features:
Borrower Base: Primarily limited to institutions with established reputations and strong balance sheets.
Underwriting Models: Heavy reliance on off-chain due diligence, KYC/AML processes, and delegated or manual risk assessment by designated underwriters or community actors.
Risk Management: Legal recourse via loan agreements and, in some cases, staking of protocol governance tokens as first-loss protection.
Static Credit Terms: Risk terms and loan structures are typically set at the outset and remain unchanged for the duration of the loan.
Key Differences: How 3Jane Fits Into the Landscape
3Jane is a new entrant in the on-chain unsecured lending space that incorporates some novel design choices compared to existing protocols. These differences can be summarized as follows:
Broader Borrower Base: Unlike traditional unsecured lending protocols, which focus on large institutional borrowers, 3Jane extends credit access to a wider range of borrowers—including individuals, small businesses, and on-chain-native entities such as DAOs and AI agents. This inclusivity aims to unlock economic potential for a broader set of actors within DeFi.
Algorithmic Underwriting: 3Jane replaces manual, human-driven credit decisions with its 3CA algorithm, which blends on-chain activity and off-chain financial data—like bank cash flows and credit scores—to dynamically adjust borrower risk profiles and credit limits every 30 days. This data-driven approach could enable more responsive credit decisions and broader financial access.
Dynamic Risk Management: Instead of relying on static insurance structures (such as staked governance tokens), 3Jane uses real-time credit score adjustments and auctions defaulted loans to licensed collections agencies. This integrated approach combines on-chain penalties with off-chain recovery efforts, addressing the challenge of managing unsecured debt in a decentralized ecosystem.
Flexible Credit Structure: 3Jane’s pooled credit market features two tranches for lenders: senior USD3 for lower risk and priority repayment, and subordinate sUSD3 for higher yield and first-loss risk. This structure provides varied risk-return profiles for lenders and dynamically adjusts based on updated borrower data and market conditions.
Risks and Opportunities: Juxtaposing 3Jane’s Model Against Existing Protocols
3Jane marks a departure from earlier unsecured DeFi lending models in how it identifies borrowers, sets rates, and manages risk—differing notably from TrueFi, Maple, Goldfinch, and Clearpool.
Borrower Inclusivity and Credit Risk
Existing protocols limit credit to large institutions and whitelisted borrowers, ensuring well-capitalized participants but excluding retail and small businesses. 3Jane broadens eligibility to include DeFi users, small businesses, and on-chain entities like DAOs and AI agents. While this inclusivity could unlock asset-light economic activity, it also exposes 3Jane to less predictable credit performance and higher default risk.
Underwriting Approach: Delegated vs. Automated
TrueFi, Maple, and Goldfinch rely on manual due diligence by credit committees and pool delegates, leveraging human judgment. In contrast, 3Jane fully automates underwriting through its 3CA algorithm, recalibrating credit limits and risk premiums monthly using on-chain and off-chain data. This algorithmic approach improves scalability but carries modeling risks and borrower dissatisfaction if recalibration misaligns with market conditions.
Default and Recovery Mechanisms
Protocols like TrueFi and Maple depend on legal agreements and staked governance tokens for loss recovery, with pool delegates assuming first-loss risk. 3Jane uses a dynamic, three-tiered system: credit score penalties for delinquents, late interest redistribution to performing borrowers, and auctioning defaulted loans to collections agencies. This shift to data-driven enforcement moves away from static insurance but depends on accurate scoring and effective collections.
Opportunities and Implications
3Jane’s data-driven underwriting and broader borrower pool could expand DeFi’s reach beyond institutions, creating credit flows based on real-time cash flows and data rather than static collateral. However, these opportunities come with risks: borrower heterogeneity, reliance on external data, and real-world collections processes introduce uncertainties absent in more institutional-focused models. 3Jane’s success will hinge on the 3CA algorithm’s accuracy, the performance of collections partners, and the repayment behavior of its diverse borrower base.
Final Thoughts
As 3Jane enters the on-chain lending space, it will be crucial to monitor how its hybrid credit underwriting approach and dynamic borrower segmentation perform in practice. Of particular interest will be the protocol’s ability to accurately price credit risk across a broader and more diverse borrower base than has typically been served in DeFi.
Key areas for observation as the protocol matures include:
Default and Recovery Dynamics: How effectively 3Jane’s three-part default management system—dynamic credit scoring, pooled upside redistribution, and off-chain collections—can mitigate unsecured loan risk at scale.
Credit Risk Pricing: Whether the 3CA algorithm’s blending of on-chain and off-chain data can achieve more efficient credit spread compression while maintaining system solvency.
Borrower Demand and Behavior: The degree to which individuals, small businesses, and on-chain entities embrace unsecured borrowing within a DeFi-native system, and whether repayment discipline mirrors traditional unsecured markets or introduces new dynamics.
Data and Privacy Practices: How well the zero-knowledge-based integrations protect borrower privacy without compromising the accuracy of credit assessments.
If 3Jane’s algorithms successfully identify profitable unsecured borrowers, it could create a new DeFi credit sector based on cash flows and data, not just posted collateral. Such a sector would move beyond the traditional collateralized lending paradigm—broadening the definition of crypto credit to include future income and data-based lending signals, and potentially unlocking a new wave of capital efficiency and economic growth within the blockchain ecosystem.
Ultimately, 3Jane’s experiments in real-time, algorithmic credit creation will serve as a test case for whether unsecured, data-driven credit can responsibly and sustainably grow in decentralized financial systems—informing not only 3Jane’s trajectory, but the future of DeFi.
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