CFTC – The U.S. Commodity Futures Trading Commission Chairman Christopher Giancarlo aforementioned in an exceedingly speech on 7th Nov. that the technological advances, as well as Distributed Ledger Technology [DLT], might facilitate regulators better supervise trading markets.
Giancarlo delivered his speech titled “Quantitative Regulation: Effective Market Regulation in an exceedingly “Digital Era” at the FinTech Week conference at Georgetown University school of law. The chairman self-addressed rising digital technologies, along with DLT, big data, automatic data analysis, and AI, and therefore their impact on trading markets and the monetary landscape.
In terms of applying these technologies to trading markets, Giancarlo said that “we begin to envision a world where the bulk of normal tasks are managed by machines” since, combined with DLT, automation facilitates price reduction and improves trade matching, processing, clearing and settlement.
Giancarlo instructed that higher-order computing technologies can probably become “ubiquitous” to trade goods and monetary derivatives markets. He stated that the CFTC along with other regulators got to keep up with the advances of AI so as to succeed.
Giancarlo additional acknowledged that the commission should be proactive in restrictive information assortment, automatic analysis, and data-driven policy application, and eventually become a “quantitative regulator.”
Speaking on the challenges represented by data automation and machines and their impact on labor markets, Giancarlo declared that “being a quantitative regulator doesn’t mean replacing human judgment and market intelligence; it simply means reinforcing it:”
“It means liberating agency employees from repetitive and low worth tasks to specialize in high worth activities that need their knowledgeable judgment and domain information. It means marshalling quality knowledge that’s expeditiously and, perhaps, algorithmically analyzed upon which human judgement may be deployed, unfurled and enlarged.”
The chairman instructed that DLT would facilitate regulators analyze information, real-world outcomes, and success in satisfying restrictive objectives, “rather than deem static rules and laws that were placed in situ while not knowing the results or consequences they’d drive within the market.”
Explaining further, he added:
“We also can envision the day where rulebooks are digitized, compliance is progressively automated or designed into business operations through smart contracts, and restrictive news is glad through real time DLT networks.”