Risk Framework

Concordia’s risk framework applies to the capacity to borrow assets and use them as collateral. It is a system to secure loans with collaterals in such a way as to balance capital efficiency and risk proper collateralization.

Principles of Concordia's risk engine

Concordia’s risk engine is:

  1. Holistic

  2. Data driven

  3. Dyanmic

1. Holistic

Concordia’s risk model appraises the risk of a portfolio as a whole. Liabilities and collaterals are not appraised separately, but rather in the context of their specific composition.

A portfolio is a set of collaterals and liabilities. The ultimate question of the risk engine is whether (and to what confidence) the set of collaterals can secure against the liabilities. If the risk is too great, then the portfolio owner will either need to reduce their debt, pledge additional collateral, or suffer forced close-out.

Key difference

In on-chain finance (as elsewhere in crypto-oriented trading platforms), the conventional approach to risk assessment is to assign haircuts to collaterals independently of each other, and then appraise whether the scaled-down value of the pot of collateral is sufficient to back the sum of outstanding debt. In Concordia, the quantity of risk is attributed to the entire portfolio, not the individual collaterals.

To take an example from digital assets, Bitcoin is a high risk collateral for borrowing USDC, since the value of Bitcoin is extremely volatile relative to the value of USDC. But Bitcoin is relatively less risky when used as collateral to borrow ETH. The reason Bitcoin is less risky in the context of ETH is that the value of these two assets are highly correlated: if Bitcoin depreciates, it is a safe bet that so will ETH.

The specific positions are measured against their historical performance in order to quantify the amount of risk inherent in that portfolio’s basket of collaterals’ likelihood to secure that portfolio’s debts. Consequently, changes in the portfolio’s set of positions will change the haircut it receives. Every portfolio composition has a deterministic relationship to its specific quantity of risk.

This approach to risk can create portfolios that are more capital efficient than on competitor’s platforms. For example, suppose a DeFi lending protocol assigns a 20% haircut to USDC (a dollar-pegged digital asset). If a user were to pledge $1 of USDC, they could only borrow up to $0.80 of USDT (another dollar-pegged digital asset). Concordia’s risk model, on the other hand, would inspect the concrete risk of backing USDT debt with USDC collateral, and since these assets have very similar identical historical performance, the would could be significantly less than 20%, presenting a Concordia portfolio with much more borrow power.

2. Data-driven

On-chain finance happens in real-time and in a transparent, easily accessible public ledger. Market data is flowing out in the open.

Concordia’s risk model reacts to the real-time changes in market conditions. It tunes its parameters automatically & algorithmically. As volatility (or other indicators) shift over time, Concordia's risk engine re-calculates risk based upon the changing markets.

3. Dynamic

In order to avoid toxic liquidation spiral, a dynamic approach to rebalancing (liquidation) is required.

Concordia use both Dynamic Closing Factor and Dynamic Incentives to increase incentives for liquidators by increasing the amount of collateral available for liquidation in line with the riskiness of the distressed portfolios' Health Ratio, thereby further de-risking the protocol linearly with the risk it carries.

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