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

Managing Data Technology Remains a Challenges at Enterprise Level, DMRAV Delegates Told

Subscribe to our newsletter

Proving return on investment (ROI) while attempting to take an incremental approach to enterprise data management projects remains a significant challenge for managers seeking sign-off for EDM projects, delegates at A-Team’s Data Management for Risk, Analytics & Valuations conference in London heard.

According to panellists on the event’s discussion on ‘Technology Challenges of Building an Enterprise Data Management Infrastructure’ session, EDM projects remain a challenge irrespective of the current economic climate. Colin Gibson, head of data architecture for Royal Bank of Scotland’s Global Banking and Markets division told the audience that in good times, internal clients were in a hurry to realise the fruits of data management projects, while in bad times they were reticent to spend.

Notwithstanding the financial climate, panellists agreed that consistency and content coverage were key attributes of any project to unify internal data. While good data governance helps, they said, education is also a major factor to ensure internal clients understood the benefits they would receive, and most importantly when they could expect to receive them.

Christopher Thompson, vice president, reference data, in the Securities Services Department of Mizuho International, said the days of ‘blue-sky’ EDM projects were likely over. Victoria Stahley, associate director and senior project manager at Royal Bank of Canada, said users should get used to the idea that projects may not simply take a year, and could take longer to bear fruit.

The panellists, including Thomson Reuters global head of enterprise data management, Sally Hinds, expressed some appetite for outsourcing some of the data management process, possibly to a data utility. At the same time, they conceded that certain elements of a firm’s data relied on heavy customisation, and would be difficult to outsource to a third party.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Building a Semantic Layer for Your Enterprise Data Estate

Date: 8 September 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes The democratisation of data has encouraged engineers to think about how to make their data estates more accessible and useable for non-technical business end-users. Translating intention into data action requires careful configuration that enables consumers to mine insight, analytics...

BLOG

Governance to be Scrutinised at Inaugural AI in Data Management Summit NYC

Ensuring artificial intelligence deployments are securely governed without stymieing their potential is a delicate balancing act. It requires carefully drawn policies, frameworks and processes. As deployment of the technology expands and its capabilities and complexity multiply, the governance structure must adapt and evolve. How to get this right is among the most important topics swirling...

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...