オルタナティブデータをめぐる証券市場の脅威と利欲

The confluence of digital data creation, cloud computing, and machine learning processing is creating Market Data 2.0, which has tremendous implications for capital markets consumers and producers of data. In short, what we think of as market data will include data harvested from the Internet of Things (IoT), satellites, wearables, web interactions, and crowdsourcing, and will yield unique information and sentiment. For some firms, the value of their data might surpass the value of their core business offering.

Capital markets participants are constantly thinking about data. Now, alternative data sets generated by individuals and businesses, and their collective digital interactions are creating new strategies for investors and traders.

In my recent report titled Emerging Trends in Emerging Data: Alternative Data or Market Data 2.0?, I attempt to answer whether emerging data sets are a luxury or a necessity.

Emerging data is in its infancy, with significant opportunities for data providers and consumers. The ecosystem surrounding alternative data is changing by the day, and many players straddle several roles, but the key questions for those in the trading and investing world are: What is out there? What does it do for me? What data makes sense for my strategies in what timeframes? What are the costs of accessing and leveraging the data? What are the compliance and regulatory risks? How does it impact our views on the use of customer data? Do we have the tools to create data products with which we are comfortable using it for our own analysis or our clients?

This is particularly true as we ponder, in real time, the implications of increasing threats posed by improper data disclosure. Furthermore, as the scale of the General Data Privacy Regulation (GDPR), as well as the tremendous cost of noncompliance, becomes better understood, these conversations become more trenchant.

But, new technologies can assist with these challenges: Innovators are building solutions to better process and aggregate data in a secure way around differential privacy. These technologies will grow as the demand for new data types grows.