To become trusted platforms for the use of data, data exchanges will need to incorporate anti-falsification measures such as strong authentication protocols and blockchain-based tracing and verification tools. Trust, much like financial markets, is the bedrock for making the platform function optimally. One aspect of this is by reinforcing and creating a strong foundation for trust, data sellers and buyers are more likely to participate. A byproduct of this is greater liquidity and less volatile trading. This in turn will inspire additional participants to join the platform, which will create even more liquidity and smoother trading, and so on and so forth.
In a world without stock exchanges, every investment in a company would require drawing up a complex contract from scratch. How much of the business is the investor buying? What dividends does she have a right to receive? How will his opinions about the way the company is run be communicated to managers, and weighed against the opinions of other owners?
Stock exchanges simplify all of that. On a stock exchange, standardized stock certificates replace bespoke contracts. They lay out all the rights and responsibilities that a contract would have, but make investing and trading easier.
Similar tools could and should be used in data exchanges. The buyer in a transaction facilitated by a data exchange would receive the right to access and use certain data, under certain conditions. The details could be enumerated in a tradable “data certificate” rather than a complex contract, reducing transaction costs and enhancing liquidity. Higher liquidity makes it easier for prices to be discovered, and at the same time stabilizes the business of the exchange. As data trading evolved and became more commonplace, standardized products and trading formats might emerge, as they have in financial markets. That could make things even easier for users and further promote the exchange of data.
The valuation question
One reason financial exchanges are useful is they help people understand what things are worth. Stock prices are public, so buying shares on an exchange takes away the fear that someone else might be getting vastly better deal.
Could data exchanges do something similar for information? Data is notoriously hard to value, but exchanges would lend a degree of transparency to the market and help track supply and demand. There would be limits, though. Assessing the underlying value of data – as opposed to its current market price – would require the development of valuation models that do not currently exist. Without them, potential data traders might still stay away.
Such models do exist for financial assets, which are typically assessed in terms of the present value of their expected future cash flows. A legion of analysts exists to do the math and advise investors. Data could in theory be valued the same way, but the practice is still in its infancy. Data valuation also cannot be narrowly understood in the context of narrow buy-and-sell models. Rather, it needs to also include data’s progenitive nature and the implication that it has on the contextual value of data and various datasets that each provide a unique view, and therefore, a unique value.
Regulating data exchanges
Financial exchanges need trust to function, and trust requires effective regulation. Securities regulations seek to ensure transparency and prevent market manipulation and other abuses. In places like Japan, financial regulations have been expanded to cover new kinds of assets such as cryptocurrencies.
There is no equivalent of the US Securities and Exchange Commission (SEC) for data trading, nor are there specific laws governing the practice. As long as data are bought and sold privately, there may be no need for disclosure rules or penalties for insider trading. But an equitable and successful public market would require such regulations, as well as a system of enforcement. As in finance, exchanges open to the general public might need tighter rules and stricter enforcement than those restricted to professionals.
A major difference between financial and data exchanges is the role of privacy protection, which is a critical factor in data transactions. Any regulatory regime governing data-exchange operators would need to address the privacy concerns of both market participants and the public.
It’s one thing to set up a data exchange; it’s another thing to get people to use it. Markets are attractive when there is plenty of liquidity – that is, lots of buyers and sellers are actively trading (as we mentioned before). But how do you appeal to potential traders when nothing exists yet? Particularly when it comes to data sellers (lots of businesses are eager to buy data), providing clear, convincing incentives will be key. That includes financial rewards but also trusted governance, the kind that can only be created through the efforts of a wide range of public and private-sector stakeholders.
The world’s rising tide of data can be used for good. But first we need to share it.
Dimitri Zabelin, Policy Analyst, Data Policy, World Economic Forum LLC
Tomonori Yuyama, Fellow, Centre for the Fourth Industrial Revolution Japan, World Economic Forum
Tomoaki Nakanishi, Project Fellow, Data for Common Purpose Initiative, World Economic Forum
This article was originally published in the World Economic Forum. You can view it here.
Source: The Print