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

TORA Introduces AlgoWheel to Help Firms Create Systematic Best Ex Processes

Subscribe to our newsletter

TORA has introduced an AI-powered AlgoWheel designed to help firms create scalable and systematic best execution processes in line with the requirements of Markets in Financial Instruments Directive II (MiFID II).

The TORA AlgoWheel is a quantitative execution strategy optimiser that uses AI technology to automate low-touch order execution or provide real-time market intelligence for orders needing human intervention. It provides a feedback loop that uses historical and real-time order-level execution information to identify the optimal broker algo and inform the trading decision making process.

Historical trade execution information is captured by TORA’s post-trade transaction cost analysis (TCA) solution, while the company’s AI-driven pre-trade TCA tool is used to evaluate each order. The pre-trade TCA platform is built on a convolutional neural network that uses machine learning to increase its estimation precision over time.

Low-touch orders can be automatically executed by TORA’s Strategy Server using the recommended broker algo combination. Alternatively, the recommended broker algo can be displayed directly in the TORA trading blotter for orders where a trader wants to be involved.

When using the automated process, the Strategy Server is configurable to enable traders to customise the execution process using any number of data inputs. For example, traders can set a trading strategy to begin at a time of day, when a stock hits a certain price or pending certain overall market conditions. The server can also be configured to send a certain percentage of orders to different broker algos to help avoid sample bias.

Chris Jenkins, managing director at TORA, says: “To remain competitive in today’s market, traders need to focus their attention where they can add most value. To do that, they need an automated trading solution they trust can achieve best execution for the bulk of their orders.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: From Data to Alpha: AI Strategies for Taming Unstructured Data

Unstructured data and text now accounts for the majority of information flowing through financial markets organisations, spanning research content, corporate disclosures, communications, alternative data, and internal documents. While AI has created new opportunities to extract signals, many firms are discovering that value is constrained not by models, but by the quality of the content, architecture,...

BLOG

Tokenisation’s Real Barrier Is Perception, Not Regulation, Summit Panel Argues

Stablecoins account for roughly $300 billion of tokenised value, intraday repo products are running at billions per day on distributed ledger infrastructure, and at least one retail venue has processed $25 billion in tokenised equity trading. Yet institutional adoption remains sluggish, held back, a panel at A-Team Group’s TradingTech Summit London 2026 argued, less by...

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...