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

A-Team Insight Blogs

The Proof is in the Pudding

Subscribe to our newsletter

Lunch – London, so curry, of course – with a disillusioned reference data friend the other day leads us to take stock a bit of where this reference data marketplace has arrived, and from whence it came.

Reference Data Review will be four years old this year. Looking back over the archive – as we do as we put together each issue – we find a unique and valuable treasure trove. But not just of data or information, not just the facts of the evolution of this marketplace. Rather, what will continue to make Reference Data Review unique is our cataloguing of the attitudes of the players within the marketplace as they have twisted and changed over time.

Four years isn’t a very long time. But in reference data it’s been an age. When we started out with Reference Data Review, it was a little-known backwater, really, of the much more sexy and lucrative market data industry, an area we knew well from years of experience within it. Today, it’s a recognized, perhaps mature, subsegment of the financial data marketplace. One that’s possibly overcrowded with too many me-too events, and a raft of bottom-feeders struggling to get in on the act.

But the plus side is how the market’s attitude has evolved from those early days of Reference Data Review. Then, it was all about definitions, approaches, corporate governance, buy-in and ROI. It was about Powerpoint presentations, vapourware and acquisitions of major centralized databases that ultimately faded and died.

Of course, it still is about all those things. But on top of that, our industry now routinely throws up real implementations. This issue, for example, lists a range of projects, ranging from the mighty – ING – to the not so. And this is only the deals we managed to squeeze into this month’s 16+ pages.

So why was our reference data friend so reticent?

Perhaps because of the slow pace of change, in the face of a myriad compelling reasons why financial institutions should tear out their ageing IT infrastructures and replace them with architectures that make data a help rather than a hindrance? That’s part of it.

What’s transpiring from all the white papers, trade conference presentations, operations group powerpoints and, indeed, contributed Reference Data Review articles, is that many of the projects being undertaken by real people in the marketplace aren’t always the over-arching, architecture-busting sea-change implementations that many in our space had envisioned. Rather, they’re highly selective deals, aimed at addressing a very specific business issue. Much like most business projects should be, really. Is it time, then, to pack our bags and go home? Of course not. We just need to get used to operating in what is turning out to be the equilibrium state of the industry, where reference data projects are conducted to deal with practical problems. Nothing wrong in that.

Subscribe to our newsletter

Related content

WEBINAR

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

Date: 15 October 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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...

BLOG

Data Opportunities Abound in Migration to the Cloud: Webinar Preview

The shift from on-premises data management to the cloud is a huge undertaking that requires an enormous amount of planning. The benefits, though, are potentially even greater; after all, why else would an organisation go through the process of lifting and shifting the most vital ingredient in their operational arsenal? The move to cloud-based services...

EVENT

Data Management Summit London

Now in its 17th year, Data Management Summit (DMS) London returns In April 2027, to explore how to use data and AI to drive measurable business outcomes reliably, repeatedly and at scale.

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...