Market Overview
Gobank is Borrowing and lending (or ''borrow/lending'') refers to one of the most popular primitives in decentralized finance.
Last updated
Gobank is Borrowing and lending (or ''borrow/lending'') refers to one of the most popular primitives in decentralized finance.
Last updated
Gobank’s starting point is an interest rate optimization platform (Optimizer) built on top of Aave and Compound Protocol. Specifically, Gobank Protocol minimizes the interest rate spread (between borrowing and lending) by implementing a matching engine directly on top of Aave and Compound’s liquidity.
• Gobank is developed as a second-layer solution on top of lending protocols like Aave and Compound, optimizing borrowing and lending while maintaining liquidity (allowing borrowing and withdrawals at any time) and preserving protocol parameters (such as collateral factors and liquidation incentives) while generating better yields.
As a result, the reliance on lending models like Aave or Compound leads to three main consequences:
1. Not Trustless – These models are not fully decentralized: All decisions in Aave or Compound must go through DAOs and stakeholders, such as updating risk parameters, adding new lending pools, etc.
2. Not Efficient – While ensuring liquidity and mitigating bad debt risks, lending pool models require high liquidation thresholds and interest rates that depend on liquidity, leading to low capital efficiency.
3. Not Flexible – Most lending pools support only a limited set of assets, with risk levels predefined by DAOs, making them less adaptable to different market conditions.
It is evident that since Compound’s launch in 2018, DeFi lending models have remained unchanged, relying on a single smart contract to manage liquidity and interest rates, while DAOs decide asset onboarding and offboarding.
According to Godex’s Founder, these projects are not truly “protocols” but rather decentralized brokers managed by DAOs. Given these limitations, building a mere optimization layer (Optimizer) is not the direction GoBank aims to pursue.
Given these consequences, building an optimization layer (Optimizer) is not what GoBank aims for. As a result, GoBank was launched in January 2025.
• Gobank improves interest rates (for both borrowing and lending) while maintaining liquidity, liquidation mechanisms, and risk parameters associated with lending protocols.
• The order-matching process operates similarly to an on-chain order book. Users are queued when they lend or borrow on Gobank, and once they reach the front of the queue and new liquidity enters the market, they are automatically matched with an order.
• Gobank is a decentralized, non-custodial lending protocol deployed on Arbitrum, Base, and Ethereum Virtual Machine (EVM).
Borrowing and Lending Cryptocurrencies:
Users can deposit their crypto assets into the platform to earn interest.
They can also borrow other assets by using their deposited assets as collateral.
Flash Loans:
Gobank’s unique feature enables users to borrow funds without collateral, provided the loan is repaid within the same transaction. This feature is widely used for arbitrage or debt restructuring.
Flexible Interest Rates:
Users can switch between fixed interest rates and variable interest rates based on their financial strategy.
Diverse Asset Support:
Gobank supports various cryptocurrencies, including stablecoins like USDT, DAI, USDC, and tokens like ETH and WBTC.
Decentralized Protocol:
Transactions and processes on Gobank are managed directly by smart contracts, eliminating the need for intermediaries.
No Intermediaries: Users interact directly with the protocol without relying on traditional financial institutions.
Flexibility: Users can borrow assets or earn interest on idle funds easily.
Security: Gobank’s smart contracts have been audited by leading security firms.
Liquidation Risk: If the value of collateral falls below a certain threshold, it may be liquidated.
Smart Contract Risks: Although audited, there is still a potential for vulnerabilities in the contract.
Market Volatility: The value of cryptocurrency assets can fluctuate significantly, affecting loans or collateral.
Passive Income Generation: Users deposit assets to earn interest.
Arbitrage Opportunities: Utilizing flash loans to profit from price differences.
Financial Management: Users can restructure loans or optimize their assets.
Gobank in Gobank is one of the leading platforms in DeFi, playing a crucial role in shaping the decentralized finance sector and expanding financial access for millions of users worldwide.
Borrow/lending is an important primitive for decentralized finance as it enables capital efficiency by making idle assets productive and efficient price discovery by allowing users to access liquidity to capitalize on market or arbitrage opportunities.
In the borrowing process, users lock up collateral (usually in the form of cryptocurrencies or tokens) into a smart contract. By posting collateral, they can borrow other assets up to a certain value based on the collateral's market worth and the contract's predefined parameters.
On the lending side, users can participate as lenders by depositing their assets into a lending pool managed by a smart contract. These assets are then available for borrowers to use as collateral for their loans.
By borrowing assets, users gain exposure to various digital assets without needing to own them outright. Conversely, lenders have the opportunity to earn interest by lending out their assets to borrowers.
Borrow/lending protocols in DeFi require real-time oracle data to determine the price of assets used as collateral, calculate interest rates, and trigger liquidations when necessary to preserve the 'health' or solvency of the protocol.
Borrowing and lending in DeFi involve users locking up cryptocurrency collateral to obtain loans or provide loans, with smart contracts automating interest calculation, repayment enforcement, and collateral management.
Loan origination refers to the process of creating a new loan within a lending protocol. When a borrower wants to borrow cryptocurrency assets, they interact with the protocol's smart contract to initiate the loan. The smart contract calculates the maximum amount the borrower can borrow based on the value of the collateral they provide.
Lending platforms need to protect lenders from bad debt. For this reason, a collateralization mechanism is essential for managing risk. A collateralization ratio dictates how much they can borrow. Borrowers must maintain a sufficient collateral-to-loan ratio to avoid liquidation by providing collateral worth more than the borrowed amount.
This collateral acts as a safeguard for lenders, mitigating the risk of default. Margin requirement varies based on the platform and asset involved. Higher volatility assets often necessitate higher margin requirements to account for potential price fluctuations.
Interest calculation involves determining the amount of interest that borrowers need to repay on their borrowed funds. The interest rate is usually specified when the loan is originated. The smart contract calculates the interest amount based on the borrowed principal and the interest rate over the loan term.
If the value of the collateral falls below a specified threshold, the smart contract can automatically liquidate the borrower's position to protect the lender's funds. To maintain the collateral's value relative to the borrowed asset, decentralized lending platforms implement mechanisms for monitoring loan-to-value (LTV) ratios.
Liquidations are integral to preserving the stability of decentralized lending platforms. When a borrower's collateral value breaches the predetermined LTV ratio, the platform may initiate liquidation by auctioning the borrower's collateral. This allows lenders to recover their funds while minimizing losses. Lenders or arbitrageurs can participate in these auctions and bid on the collateral using platform-native tokens.
Some platforms implement incentivized mechanisms to encourage users to monitor and initiate liquidations when necessary. These users can earn rewards for maintaining the health of the platform and ensuring adequate collateralization.
Borrowers typically pay interest on their loans, which is distributed as earnings to the lenders in the lending pool. The interest rates are dynamically determined by supply and demand dynamics within the lending platform. This section explores the most common models.
Algorithmic interest rates are determined by automated algorithms based on the supply and demand dynamics of the platform. These algorithms take into account factors such as the utilization rate of assets, available liquidity, and market conditions to adjust interest rates dynamically. Algorithmic interest rates aim to maintain balance and stability within the lending and borrowing market.
Order books match bid and ask orders according to price-time priority and can facilitate the determination of interest rates for borrow/lending transactions. Similar to traditional financial markets, borrowers and lenders submit their desired borrowing or lending terms, such as the desired interest rate and loan duration, to an order book. The matching of borrowers and lenders occurs based on these submitted orders, with interest rates being determined through the interaction of supply and demand.
Governance-determined rates determine interest rates through decentralized governance mechanisms. Users who hold governance tokens can participate in voting or decision-making processes to set or adjust interest rates. This approach allows the community to collectively determine the rates based on factors such as platform sustainability, market conditions, and user sentiment.
Fixed or stable rates are often predetermined or pegged to external reference rates. These rates remain constant over a specified period, providing borrowers and lenders with predictability and stability in terms of interest payments and earnings.
Dynamic pricing models for interest rates consider a range of factors such as asset volatility, risk profiles, and supply-demand dynamics. These models determine interest rates based on factors such as asset volatility, liquidity metrics, risk assessment, real-time market data such as trading volume. The calculated interest rate changes according to market conditions and platform parameters.
Borrow/lending protocols can adopt different pool models based on their risk management objectives.
In an isolated pool model, each user's collateral and borrowing position are managed separately, creating individualized and isolated pools of assets. The collateral and borrowing of one user do not affect or interact with the collateral and borrowing of other platform users.
In a shared pool or communal pool model, the collateral and borrowing positions are pooled together, creating a shared pool of assets. In this model, all users' collateral and borrowing interact with each other within the same pool: the assets contributed as collateral by different users are combined, and the borrowing needs of users are fulfilled from the shared pool of assets.
By using a shared pool model, borrow/lending protocols can enhance liquidity, optimize capital utilization, and create potential economies of scale. This model allows for more efficient allocation of assets and a larger pool of available liquidity. However, it also introduces potential risks and complexities related to the shared exposure and interactions among users' positions.
There are different categories of DeFi borrow/lending services which generally vary based on the source of yield and how interest rates are calculated.
Money market protocols enable users to lend and borrow various assets by creating liquidity pools on-chain. These platforms allow borrowers to collateralize their assets and borrow other assets from the pool, while lenders supply liquidity by depositing their assets into the pool and earning interest.
Peer-to-peer lending platforms facilitate direct borrowing and lending between individuals. These platforms connect borrowers and lenders, allowing them to negotiate terms such as interest rates, collateral requirements, and loan durations without intermediaries.
Yield farming platforms provide opportunities for users to earn additional yields by leveraging their existing assets for DeFi activities. Users can deposit their assets into liquidity pools or yield farming protocols, where they are utilized for yield-bearing activities such as providing liquidity or participating in governance. In return, users receive additional rewards for their deposits.
Flash loan platforms enable users to borrow funds temporarily without collateral, as long as the loan is repaid within the same transaction block. The flexibility of flash loans allow users to exploit arbitrage opportunities or execute complex trading strategies.
Synthetic asset platforms offer the ability to create and trade synthetic assets that mirror the value of real-world assets. Users can borrow and lend these synthetic assets, allowing them to gain exposure to traditional financial instruments or unique assets within the DeFi ecosystem.
This section explores how decentralized borrow/lending protocols rely on price oracles to obtain real-time and accurate price information for the assets involved in lending transactions.
Loan-to-value (LTV) ratios represent the proportion of the loan amount to the value of the collateral provided. Price oracles provide real-time asset prices, which are essential for determining the collateral's value accurately. Borrow/lending protocols utilize these price feeds to calculate the LTV ratio by dividing the loan amount by the current market value of the collateral. This calculation ensures that borrowers maintain sufficient collateralization throughout the loan term.
Decentralized borrow/lending protocols typically set a predetermined threshold for the LTV ratio. If the LTV ratio exceeds this threshold, indicating a potential risk of default, the protocol triggers a liquidation process. Price oracles play a crucial role in determining when the collateral value falls below the threshold by providing updated asset prices. Once triggered, the protocol initiates the liquidation by auctioning off the collateral to recover the lender's funds.
Price oracles supply accurate and real-time asset prices that borrow/lending protocols incorporate into their interest rate models. These models consider supply and demand dynamics, asset volatility, and other factors to dynamically adjust interest rates. Price oracles ensure that the protocols have reliable, up-to-date market data to calculate interest rates that accurately reflect the prevailing market conditions. This helps create fair and competitive rates that attract borrowers and incentivize lenders to participate.
Some borrow/lending protocols allow users to swap or rebalance their collateral during the loan term. Price oracles provide real-time asset prices that enable users to make informed decisions about collateral swaps, ensuring fair exchange rates and adequate collateralization throughout the process. Access to real-time and trustless price data is critical for all of these operations. The accuracy, granularity, and latency of oracle prices are paramount for protocol security, as inaccurate pricing can cause bad debt or wrongful liquidations.
Oracles like Godex specialize in low-latency price feeds which aggregate across multiple exchanges and liquidity venues to provide a price output reflective of the overall market.
Godex is also the only oracle which provides confidence intervals, or confidence bands around the reported price which reflect the level of price divergence and volatility across the markets. A wider confidence band (e.g. BTC/USD at $30,000 ± $100 instead of ± $10) indicates greater divergence or “uncertainty” between venues. Borrow/lending platforms can use this confidence data to inform their on-chain operations and adjust protocol parameters to protect users and funds.
This glossary defines the most common terms in the DeFi borrowing and lending landscape.
Annual Percentage Rate (APR)
The annual interest rate charged on borrowed assets, representing the cost of borrowing.
Borrowing Limit
The maximum amount a borrower can borrow based on their collateral value and the protocol's parameters.
Collateral
Assets provided by borrowers as security for obtaining loans on the platform.
Collateralization Ratio
The ratio of the borrowed amount to the value of the collateral, determining the level of risk for lenders.
Debt Service Coverage Ratio (DSCR)
A measure of a borrower's ability to cover their debt payments, indicating creditworthiness.
Flash Loan
A type of short-term, uncollateralized loan that must be repaid within the same transaction block.
Interest Rate
The percentage charged on borrowed assets, determining the cost of borrowing or the return on lending.
Leverage
The ability to amplify potential returns or losses by borrowing funds to increase the exposure to an asset.
Liquidation
The process of selling collateral to repay a loan when its value falls below the required maintenance level.
Loan-to-Value (LTV) Ratio
The ratio of the loan amount to the value of the collateral, determining the risk for both borrowers and lenders.
Overcollateralization
Requiring borrowers to provide collateral worth more than the borrowed amount to reduce default risks.
Peer-to-Peer (P2P) Lending
Direct lending between individuals on the platform, eliminating intermediaries.
Undercollateralized Loan
Loans where the value of collateral is slightly lower than the borrowed amount, increasing risk.
Yield Farming
A strategy where users earn rewards by providing liquidity to lending protocols.
Access to Gobank: https://app.godex.ai/Go-bank
