About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Technology Catches Up To Regulators’ Monitoring Demands

Subscribe to our newsletter

Conducting a simple real-time statistical analysis of financial market activity does not necessarily require “sophisticated AI or machine learning,” says Guy Warren, CEO of ITRS, an application performance management and big data analytics provider.

The purpose of conducting such an analysis is to determine when a circuit breaker kicks in to catch and stop algorithmic trading activity that has exceeded volatility limits, whether that halt of trading was warranted, or what caused it. ITRS real-time monitoring and analytics tools let it act directly on a client’s behalf, triggering a “kill switch” or “pause,” so people can manually investigate relevant trading and market data, Warren explains.

Regulators are trying to get greater control and specificity around the use of such sudden stops of market activity, adds Warren.

“Regulators are right to push for firms to have the ability to catch fluctuations and pause activity,” he says. “They increased the number of liquidity venues subject to a requirement to catch fluctuations — in response to a very large OTC presence which they thought might be manipulated.”

The regulatory push is driving more interest in implementing circuit breakers, but regulators’ wishes appear to now be better timed. Technological capabilities now make it possible to monitor ticks for 1 million instruments coming from different asset classes and regions, in a manner that was impossible four years ago. As a result, the position of some regulators that firms ought to be able to monitor all the instruments they are dealing with is now feasible when it wasn’t before, Warren explains.

Better technology makes it possible for computers to check market news that is triggering extreme price changes and evaluation if those fluctuations are genuine, he observes. “Telling if what’s happening is right can be done cost-effectively,” says Warren. “That’s not only on liquidity venues, because they have a matching engine or it’s not too hard to build one in, but on trading venues, it is possible. Most regulation will come in on trading venues, because that’s the safest place to try to catch [an unjust fluctuation]. The trading venues are trying to stop participants from putting bad trades or rogue data into the marketplace.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

BLOG

How Firms Are Adapting to a Multi-Channel, AI-Driven Future – Global Relay Survey

Global Relay has published its 2025/26 Data Insights: Communications Capture Trends report, now in its third annual edition and rapidly becoming a reference point for how regulated financial institutions manage their communications obligations. Drawing on data from more than 12,000 regulated financial institutions using Global Relay’s connectors, the survey tracks which channels firms are archiving,...

EVENT

Buy AND Build: The Future of Capital Markets Technology

Buy AND Build: The Future of Capital Markets Technology London examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...