With the importance of intangible assets being recoganised in the recent years, it is a very trendy thing to re-classify them as assets and use them as collateral for debt financing. Data, which is considered as the new oil field in the AI and digital economy, gets a lot of attention in the past several years. The key process in the current environment is to connect it to some kind of property rights and allow data to be traded. The idea that market is efficient and we can use the efficient market to uncover the true value of this new “asset” is the key. So, if data is really valuable in the economy, a fair value will be attached to it and the entity having this data can use this “fair market value” to seek financing in the financial market or through financial intermediaries.
Two issues immediately emerge as in all “less regulated” markets and financial “assets”:
- Information asymmetry is huge. We need to acknowledge that most of the validation process can be camouflaged and the quality of data may be worse than the ABS and MBS in the pre-GFC era. Even worse, this asset is not separable and its value (may) nonlinearly, or even exponentially, relates to its size. For ABS and MBS, more assets is advertised as less risky. In case of data, more data can be more information and thus more valuable. Mechanically pin it down to a valuation can be risky in this kind of cases.
- Liquidity is thin. You generally need a very liquid market with a lot of participants to uncover its value, e.g. polymarket style.
This will be an interesting topic, from a policy perspective, to explore the implication of mechanically expand the list of collateralisable assets on the financial intermediaries and whole economy. Will there be an boom-bust cycle in the Kiyotaki-Moore style?