The Case for a Market Data Rethink

When firms look to save costs, more often than not, the reaction follows the same pattern: squeeze operational budgets, delay tech upgrades, freeze headcount, or in some cases, redundancies. All the while, one of the biggest and least-scrutinised cost centres continues to grow quietly in the background: market data.

In many investment and wealth management businesses, particularly boutiques and scaling firms, market data can be one of the top three costs alongside people; competing against technology & systems and property costs. Yet, it’s rarely challenged in a meaningful way.

Why Isn’t Market Data Reviewed More?

The simple answer is because, it’s messy.

Contracts can be complex, pricing models are misleading, products have multiple users or jurisdictions, and vendor relationships can spread across teams. This all makes it feel difficult to tackle and as a result, costs rise year-on-year, often by 4–6%, with little justification and even less improvement in service.

In my experience, many providers, especially the larger established ones, (1) bundle products you don’t need, (2) sell access that goes unused, and (3) lock firms into long-term contracts. Once the sales pitch is done, service levels often decline. Smaller firms, in particular, end up paying enterprise-level prices for products and services that simply don’t fit their operating model.

Structure Where None Exists

One of the biggest challenges with market data is that it doesn’t sit within a clearly regulated or standardised framework.

There are industry bodies such as FISD (part of the Software & Information Association Industry), data working groups, and vendor forums that promote best practice, licensing standards, and dialogue between consumers and providers. They play an important role in advocacy and education.

But they don’t provide:

• Enforceable governance

• Cost transparency

• Standard commercial frameworks

• Operational ownership within firms

What does this mean in practice? It basically means market data largely polices itself, with vendors the biggest beneficiaries.

It also results in businesses creating their own structures i.e. defining ownership, creating governance, and enforcing accountability, if they are genuinely serious about cost control, transparency, and long-term resilience.

Without that structure, the same issues repeat themselves year after year.

The Root Issue: No Central Ownership

When structure is missing, ultimately, ownership fragments.

Too often, multiple teams operate independently and engage with the same market data vendor for different use cases.

For example:

• Analytics might be speaking to FactSet about sector or index data for risk tools

• Performance may want time-series data to track analyst coverage

• Operations might need simpler reporting or data distribution

These conversations happen in silos. Vendors (sometimes knowingly) upsell similar datasets multiple times, and there’s no single view of what the firm already pays for, what’s actually used, or where overlap exists.

This lack of central ownership isn’t just inefficient, but it’s expensive and will significantly impact the bottom line. But a centralised market data function is a fantastic way to starting managing the ownership.

Some may argue that it creates a level of bureaucracy and slows the business down, but the reality is that it will enable more informed discussions, better decisions, clearer accountability, and far better value.

Tap Into Your Frontline Experts

Another recurring theme I’ve come across and is frequently overlooked, is that the most valuable insights often come from the people closest to the process and tools.

Analysts, leads, and day-to-day operations staff work with these platforms every day. They know what’s useful, what’s clunky, what’s duplicated, and what’s never touched. Yet, they’re rarely involved in vendor discussions or service reviews, which tend to happen at a purely commercial level. Apart from the commercials not thoroughly taking into account actual usage, it also doesn’t allow the people using the platforms to develop professionally and build up their commercial acumen.

Bringing these users into periodic service reviews, alongside line managers and heads of function, leads to more grounded feedback and better outcomes.

Case Study: Where It Goes Wrong

I remember a project I worked on where the business was selecting a new enterprise system, to support a growing funds and institutional client base.

Subject-matter experts (SMEs) were selected from each function to assess a range of vendors. From which, demos were scheduled and a balanced scorecard was used to mark each of the vendors against a range of criteria. On the surface the process looked robust.

As we went through the selection process, however, it became increasingly clear that there was a strong bias toward one particular system. Some SMEs were actively reminded by senior leaders to attend a specific demo and of its importance.

That solution ironically scored poorly against the agreed criteria, but in the end, the decision was made “strategically” to proceed with that vendor and solution anyway.

The lasting impact was significant:

• The senior decision-maker who championed the solution left the business

• There were hidden market data costs required to make the system usable

• Per-client user costs were materially higher than expected

• The system only met the needs of a small subset of clients

• Additional systems were going to be required to service the remaining client base

• The firm was left with a complex, fragmented solution that didn’t fit with the wider operating model

Decisions have to be made in any organisation, and ultimately someone needs to sign on the dotted line. That’s part of leadership.

But too often, decision-makers remove themselves from the ongoing ownership of those decisions once they’re made. The operational burden, workarounds, and long-term consequences are left for others to manage, with an occasional acknowledgement and pat on the back for keeping things going in difficult moments.

Market data decisions are particularly susceptible to this dynamic, because decisions are made through a commercial lens, with the real costs and constraints only really surfacing months or years later.

How To Start Your Market Data Rethink

Whether you’re a boutique start-up or an established institution, the way you manage market data needs to evolve.

Too often, firms let costs drift until they’re embedded, spiralling, and difficult to unwind. A rethink doesn’t mean ripping everything up. It means starting deliberately, creating transparency, and bringing discipline to a function that has historically been left to grow unchecked.

Sounds like a big ask, but everything is relative and very much depends on where you are today.

So…if you’re a Smaller Firm

The priority is control before you scale.

• Build a basic inventory of vendors, products, users, costs, and renewal dates

• Track usage and coverage from day one

• Create a user request interface early, so all data requests flow through a single channel

• Capture MI, standardise terminology, and build a shared understanding of value across the business

Doing this early gives you leverage and clarity before complexity sets in.

For a Larger or More Established Firm, if I were in your shoes, the priority is transparency and optimisation.

• Conduct a market data health check across top-spend vendors

• Identify overlap across teams and business areas

• Understand who the key competitors are for each dataset or service

• Make it easy for end users to see what the firm already has access to

This doesn’t make market data vendor or commercial managers leads redundant. It actually allows them to focus where they add the most value: product depth, ecosystem fit, and contract negotiation.

Once structure is in place, then firms can build out coverage, reporting, and analytics, and use external insight to support renewals and negotiations with providers such as Expand, Substantive Research, TRG Screen, and 3Di.

From AI perspective, I think Market Data is one of those areas that it can only help so much. It can analyse historical usage data, extract key legal clauses, and support the production of cost and usage data into digestible summaries, but it can’t have the conversations, replace judgement, provide context, or understand commercial nuance.

Fundamentally, you need people to do that who understand the full market data lifestyle and all the intricacies that go with it.

Final Thoughts

The question senior leaders will always ask is simple: how does this effect the bottom line?

And more specifically: how does what can feel like “housekeeping” turn into something tangible on this year’s balance sheet?

The honest answer is that it doesn’t; well at least, not immediately. There is an upfront cost, with the benefits and value coming over time.

But consider this: if you’re paying £100,000 for data that has very limited usage across the business and the cost could increase to £115,000 over the next three years, is it not worth spending a few days investigating that cost, reviewing the products, and potentially saving £5,000–£10,000 or more over the next two to three years and beyond?

Now multiply that across a dozen vendors, and that’s where the case becomes compelling.

Market data maturity is a journey, not a one-off exercise. And the most important step is simply knowing where you are today, because without that clarity, every cost-cutting exercise becomes a short-term measure that has long-term impact and risks targeting the wrong thing.