Private Lending

A cryptographic protocol that distributes a computation across multiple parties where no single party can see the others' private inputs. The parties jointly compute a function over their inputs while keeping those inputs private.

• Facilitates private order matching and negotiation between lenders and borrowers without a trusted intermediary.
• Can be used for private credit scoring, where multiple data providers contribute to a score without exposing their raw data.
• Ensures that sensitive financial data, like income or asset details, is never revealed in plaintext to any participant.

Cryptographic primitives that allow a user to commit to a chosen value (or statement) while keeping it hidden, with the ability to reveal it later. The commitment is binding (cannot be changed) and hiding (does not reveal the value).

• Used as a fundamental building block in private transaction systems.
• A borrower can commit to a collateral amount or loan request terms before revealing them to a specific counterparty.
• Provides a mechanism for atomicity in OTC deals, ensuring both parties are bound to the agreed terms before execution.

Secure, isolated areas within a main processor (CPU) that guarantee code and data loaded inside are protected with respect to confidentiality and integrity. Examples include Intel SGX and AMD SEV.

• Acts as a secure enclave for processing sensitive loan agreement data off-chain.
• Enables private order books and matching engines where terms are decrypted, matched, and executed only within the secure hardware.
• Provides a high-performance alternative to pure cryptographic methods, though it introduces hardware trust assumptions.

Loans with a set maturity date and repayment schedule, contrasting with open-ended, variable-rate lending pools. The entire principal is typically repaid at maturity (bullet payment).

• Structure: Defined interest rate, duration, and repayment schedule are encoded in the smart contract.
• Advantage: Predictable cash flows for both parties; useful for project financing or specific capital needs.
• Example: A project borrows a lump sum for 12 months to fund development, with interest accruing and principal due at term end.

Platforms that match individual lenders and borrowers to negotiate custom terms directly, rather than pooling funds in a shared liquidity pool.

• Process: Parties agree on collateral type, loan amount, interest rate, and duration via a smart contract order.
• Flexibility: Supports exotic collateral assets, unique LTV ratios, and complex covenants not possible in pooled systems.
• Example Use: A lender accepts a basket of NFTs as collateral for a loan, with terms tailored to the specific collection's volatility.

Blockchain-based infrastructure used by institutions for large, over-the-counter (OTC) lending deals, bringing traditional finance workflows on-chain.

• Features: Integration with legal frameworks, KYC/AML compliance, and support for cross-chain collateral.
• Automation: Smart contracts handle interest payments, margin calls, and partial releases, reducing operational overhead.
• Benefit: Combines the efficiency and transparency of DeFi with the structure and risk management of institutional finance.

Using flash loans—uncollateralized loans that must be borrowed and repaid in a single transaction—within private lending strategies for arbitrage or collateral swapping.

• Mechanism: A borrower uses a flash loan to instantly provide collateral for a private loan, or to repay a loan to avoid liquidation, all within one block.
• Complex Use Case: Collateral swap – taking a flash loan to repay a loan position, withdraw the original collateral, sell it, and use the proceeds to repay the flash loan, effectively swapping the collateral asset.
• Requirement: High technical expertise to craft the atomic transaction and manage execution risk.

The primary security mechanism is over-collateralization, where borrowers lock assets exceeding the loan value. This creates liquidation risk if the collateral's value falls below a predefined liquidation threshold, triggering an automated sale. Key factors include:

• Volatility: High volatility assets require higher collateral ratios.
• Oracle Reliability: Price feeds must be accurate and manipulation-resistant to prevent unfair liquidations.
• Liquidation Efficiency: Slippage and network congestion can impact the final sale price, affecting both borrower and lender recovery.

While smart contracts automate terms, counterparty risk is not eliminated. It transforms into smart contract risk and oracle risk. Default risk is managed algorithmically but depends on:

• Collateral Sufficiency: Ensuring the initial and maintenance ratios are sound.
• Grace Periods: The time allowed to top up collateral before liquidation.
• Recovery Mechanisms: Processes for handling undercollateralized positions after a "black swan" market event.

Standard lending activity is fully transparent on-chain. Private lending solutions use cryptographic techniques to obscure details:

• Zero-Knowledge Proofs (ZKPs): Prove loan terms are satisfied without revealing amounts or parties.
• Fully Homomorphic Encryption (FHE): Allows computation on encrypted data.
• Mixers & Privacy Pools: Obscure the trail between collateral deposit and loan origination. Trade-offs include increased computational cost and potential regulatory scrutiny.

The immutable logic of lending contracts is a central attack vector. Common vulnerabilities include:

• Reentrancy Attacks: Where malicious contracts repeatedly withdraw funds before state updates.
• Logic Flaws: Errors in interest calculation, liquidation logic, or privilege escalation.
• Upgradeability Risks: If protocols use proxy patterns, compromised admin keys can lead to total loss. Mitigation relies on extensive audits, formal verification, and bug bounty programs.

Privacy features can conflict with Financial Action Task Force (FATF) guidelines and Know Your Customer (KYC) regulations. Lenders and protocol developers may face:

• Travel Rule Compliance: Requirements to share sender/receiver information for transactions.
• Licensing: Operating in certain jurisdictions may require money transmitter or lending licenses.
• Sanctions Screening: The need to screen counterparties against OFAC or other sanctions lists, which is challenging with private transactions.

Security models differ fundamentally based on custody:

• Non-Custodial (DeFi): Users retain control of keys; risk is limited to contract approval. Security depends entirely on public code audits and self-custody practices.
• Custodial (CeFi): A central entity holds assets, introducing counterparty risk and requiring trust in their security practices (e.g., cold storage, insurance). Hybrid models exist, using multi-party computation (MPC) or threshold signatures to distribute trust.

The Collateralization Ratio (CR) is a risk metric representing the value of a borrower's posted collateral relative to the value of the loan. It is calculated as (Collateral Value / Loan Value) * 100%. A higher ratio indicates a safer position for the lender.

• Liquidation Threshold: The minimum CR before a position is automatically liquidated.
• Overcollateralization: A standard requirement where the collateral value exceeds the loan value (e.g., 150% CR).

Liquidation is the automated process of selling a borrower's collateral to repay their loan when their collateralization ratio falls below a predefined threshold. This protects lenders from losses due to market volatility.

• Liquidation Engine: The smart contract logic that triggers and executes the sale.
• Liquidation Penalty: A fee charged to the borrower, often paid to the liquidator as an incentive.
• Liquidators: Network participants who bid on and execute liquidations for a profit.

An Interest Rate Model is an algorithm within a lending protocol that dynamically determines borrowing and lending rates based on the utilization of the pool's capital.

• Utilization Rate: The percentage of total supplied assets that are currently borrowed.
• Variable vs. Fixed Rates: Most DeFi lending uses variable rates that adjust with market conditions, though fixed-rate products also exist.
• Kink Model: A common model where rates increase sharply after a high utilization 'kink' point to incentivize repayments or more deposits.

A Flash Loan is an uncollateralized loan that must be borrowed and repaid within a single blockchain transaction. They are a unique DeFi primitive that enables complex arbitrage, collateral swapping, and self-liquidation strategies.

• Atomic Execution: The entire operation succeeds or fails as one unit; if repayment fails, the transaction reverts.
• Use Cases: Used by arbitrageurs and sophisticated traders to capitalize on price differences across protocols without upfront capital.

A Money Market is a core DeFi protocol that facilitates the lending and borrowing of crypto assets through pooled liquidity. It is the foundational infrastructure upon which private lending is often built.

• Pool-Based Model: Lenders deposit into a shared liquidity pool from which borrowers draw funds.
• Interest-Bearing Tokens: Lenders receive a token (e.g., aTokens, cTokens) representing their share of the pool, which accrues interest.
• Examples: Aave, Compound, and Euler are prominent decentralized money market protocols.

Credit Delegation is a lending mechanism that allows a depositor (delegator) to delegate their borrowing power to a trusted third party (delegatee), enabling undercollateralized or uncollateralized loans.

• Trust-Based: The delegator bears the default risk of the delegatee.
• Smart Contract Vaults: Delegated credit lines are often managed via specific vault contracts with custom terms.
• Use Case: Enables institutional-grade private lending and credit relationships on-chain.