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

Trading Technologies Begins Build of Trading Ecosystem

Subscribe to our newsletter

Trading Technologies (TT) has been developing expertise for 25 years and says the next 25 will be about adding value for customers based on its intent to build an ecosystem encompassing trading applications, infrastructure and data. TT won’t pull back from its traditional business in trading screens, but it is pushing on to extend its low-latency network into new markets, add applications to the TT platform, and innovate with emerging technologies.

The company moved from an installed customer base to offer a hybrid cloud software-as-a-service model five years ago, rebuilt the TT platform three years ago and now maintains not only the screen business, but also trading software, infrastructure solutions, and cloud data management. It says it is responding to customer needs for more cost efficiency across the trading spectrum, which can, in many cases, be achieved by consolidating vendor platforms and/or moving from in-house builds for trade flows to vendor solutions that can be more effective.

The recent integration of the TT platform with the Coinbase GDAX platform offering access to spot cryptocurrency markets, and the presence of both options and futures on the TT platform, speak to the need to consolidate multiple platforms.

In terms of vendor product development, TT chief marketing officer Brian Mehta, says the company is returning to its roots in innovation and looking at how to bring emerging technologies, such as artificial intelligence (AI) and machine learning, onto the platform. An early addition here is the result of TT’s acquisition of Neurensic, made late last year and taking the company into trade surveillance for the first time. The solution, now called TT Score, is already being used by customers on a standalone basis and should be integrated with the TT platform by the end of Q2. Its innovation is in bypassing human made parameter models for trade surveillance and introducing machine learning models that have been trained with positively labelled regulatory case data by a team of data scientists and domain experts to recognise the mathematical vectors of manipulative trading activity.

The surveillance application provides value add for customers and is an element in TT’s creation of a trading ecosystem. Exchange connectivity is also important, with TT recently adding the Osaka Securities Exchange (OSE) through the JPX colocation space, and proximity connectivity to Tokyo Commodity Exchange (TOCOM). Tokyo Financial Exchange (TFX) will be offered soon through the AT TOKYO CC2 premium rack colocation space. The Osaka connection is the first of 17 additional markets – next up is likely to be an exchange in Korea – that will be added to the TT network over the next 12 months.

The company’s commitment to date, specifically post-trade data, is a Software-as-a-Service (SAAS) solution using cloud technology for data storage. Customers use data stored in the cloud for regulatory compliance and most recently used the data to meet the data retention and access requirements of Markets in Financial Instruments Directive II (MiFID II). TT intends the extend the application of the data, initially to back-testing and later to other functionality providing access to data that can inform trading strategies.

TT has towards 20 of the top futures commission merchants (FCMs) as customers and expects its growing trading ecosystem to find favour with not only existing customers, but also prospects looking for cost efficiency coupled to increased functionality on a single platform.

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

“Take it When You Can” is the New Reality in U.S. Credit Markets

By Kevin Rutter, CEO of AIQ Markets. While the recent geopolitical shock has temporarily slowed issuance in U.S. corporate bonds, a notable market shift was already underway. Companies have been increasingly opportunistically, accelerating debt issuance when windows open, rather than waiting for ideal conditions – and this is raising new challenges for market participants in...

EVENT

TradingTech Summit New York

Our TradingTech Summit in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

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...