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

A-Team Insight Blogs

ITRS Adds Analytic Framework for Data Integrity to Geneos Suite

Subscribe to our newsletter

ITRS Group is piloting an analytic framework for data integrity that is designed to give investment banks, brokers and exchanges a real-time view across pricing data sourced from multiple market data feeds.

A production version of the Geneos Market Data Monitor (MDM) will be released on 20 February, offering users predefined relative price algorithms – as well as an environment to develop their own algos – that compare the content and latency of feeds from vendors, ensure data integrity and contribution consistency, and flag up events such as data gaps and spikes.

The Geneos MDM module is built on existing ITRS Geneos monitoring technology, including a configurable dashboard for real-time alerts. It includes a library of feed adapters for market data from firms including NYSE, Trading Technologies, GL Trade, Thomson Reuters and Bloomberg, and an open application programming interface based on the open source LUA scripting language that supports rapid algo development and performance.

Ian Salmon, head of business development at ITRS, says regulatory scrutiny is driving the need for robust processes around pricing, particularly derived pricing. These processes need to be auditable, demonstrable and automated, yet allow human intervention and action when necessary. He explains: “Whether an institution is consuming or publishing market data, the integrity, accuracy and consistency of prices in real time is paramount. By using MDM’s tick-by-tick analytics, our users are able to compare the behaviour of a price feed, perhaps a Spot FX currency pair, against custom analytic calculations. When an anomaly is flagged, the Geneos dashboard proactively alerts the appropriate team, allowing it to track, audit and resolve the issue before it has an impact on the market.”

As well as an environment for algo development, the MDM framework includes a toolkit to build custom interfaces to proprietary pricing feeds. The solution can be deployed in-house or provided as a managed solution by ITRS. Salmon concludes: “We are running three pilots of MDM as well as proofs of concept with potential users. Most interest is coming from investment banks and the brokerage community, with specific interest being in checking contributed data from interdealer brokers that create and distribute prices.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Generative and Agentic AI in Financial Markets: What the Data Really Shows

Artificial intelligence is reshaping financial markets – but the reality on the ground is more nuanced, more uneven, and more instructive than the headlines suggest. A new A-Team Insight research programme, drawing on responses from senior AI decision-makers at buy-side and sell-side institutions across the USA, UK and Canada, reveals a market in transition: from...

BLOG

xyt Layers Natural-Language AI onto Trading Data Platform as Race for AI-Ready Analytics Intensifies

xyt, the independent trading data intelligence platform formerly known as big xyt, has introduced a set of AI-powered capabilities designed to let clients query its datasets in natural language, integrate its data into their own AI environments, and generate executable analytical outputs from a prompt. The announcement positions the firm in an increasingly crowded field...

EVENT

Eagle Alpha Alternative Data Conference, London, hosted by A-Team Group

Your Gateway to the Alternative Data Ecosystem. Now in its 8th year, the Eagle Alpha Alternative Data Conference, managed by A-Team Group, is the premier content and networking forum for investment firms and hedge funds using alternative data.

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...