This always depends on the asset type but generally the idea is not to have a Vault backed by a single borrower but we pool individual loans and use shares in the pools as collateral in Maker. Over a large portfolio of assets you can build a general risk model that that can give a valuation of the portfolio with relatively high accuracy.
We believe that this transparency must be available not just to Maker but anyone on chain. Therefore we’ve gone to great lengths to make sure this transparency is available on chain: the asset originators report loan by lone on a risk score and valuation of the asset and the pool models expected losses and revenue of these individual loans into the pool being able to give an accurate NAV to anyone investing in the pool.
The asset originators will share their underwriting and origination process to determine if this is an asset they should add to the pool along with the data that they collect to feed into the credit model.
As we scale this to a larger size, data that should be brought on chain by third party entities to verify that the on chain price model is correct. This data could for example include:
- Personal Credit Score if there is a personal guarantor on the asset
- Real estate pricing: think of an oracle bringing zillow’s zestimate on chain for each NFT in the pool
- Cluster risk: an analysis of cluster risk on the entire pool such as (large counterparties, geographical risk, currency risk etc.)
As this entire structure scales up to larger amounts, these data sources can be integrated and the model overall will become more secure and more importantly not solely dependent on trusting the asset originator entirely.