Would you hire Picasso to paint your living room?

First published by The Financial Technologist, 20 October, 2025

I’m sure we’d all want to say yes, knowing that this wouldn’t be the best use of his time and skills. By the same token, every day, some of the industry’s most experienced quants, hired at great expense, spend 80% of their valuable time scrubbing data before they can start using it. But is that the best use of their skills?

The buy versus build argument has been around for many years. When it comes to market data, firms face a conundrum: do they buy the raw data and spend 80% of their quant teams’ time cleansing the data before they can use it to improve trading performance? If so, is this because firms simply don’t believe they can acquire data of the quality of normalisation they require? Buying data from third-party vendors has, in the past, not met acceptable standards, so perhaps they believed that only they knew how to solve the data puzzle.

That debate is now over. And here is why.

We have solved the data conundrum

For decades, the historical market data industry was the ‘exhaust’ of the wider market data industry. It received little to no investment as traditional providers prioritised revenue from the real-time world. That strategy doesn’t work in a quant-driven environment. Having gaps, spikes, and flaws in your data doesn’t cut it anymore. This is why we have invested heavily in our data engineering capabilities, and now the market is voting with its feet. Firms are increasingly building their strategies on BMLL data and relying on us.

‘Buy to build’ can - and is - taking centre stage

We are increasingly witnessing a shift across market participants towards buy-to-build strategies, cementing the fact that owning or engineering vast amounts of data is no longer what differentiates firms. It’s what they do with the data that matters and gives them a competitive edge.

What stands out for us in 2025 is that sophisticated firms are now trusting our normalisation processes and are increasingly building their global strategies on our historical data.

Here are some of the game-changing collaborations that cement the buy-to-build trend. Our partners use our data to understand market and liquidity dynamics; analyse market quality; optimise trading strategies and improve performance; develop their algos and smart order routers, create custom analytics, unify historical and real-time data for improved execution, and drive market structure thought leadership across the industry.

Optiver builds its strategies on BMLL data and analytics

A strategic investor today, Optiver started as a BMLL customer, relying on BMLL’s historical data to power algo development, execution analysis, shape pricing strategies and generate insights that influence their trading strategies. More recently, Optiver became both an investor and a member of the Client Product Advisory Board (CPAB), which gives them a unique opportunity to understand and shape BMLL products and product roadmap and build their strategies on BMLL data and analytics.

Kepler Cheuvreux built its KCx Spark Smart Order Router on BMLL data and analytics

KCx Spark was designed to intelligently access liquidity across European markets, ensuring best execution, reduced latency, and the ability to adapt to changing market conditions by effectively routing orders. BMLL’s harmonised Level 3 historical European order book data powers KCx Spark, enabling the Quantitative Execution Team to easily create and back-test execution models at scale.

Broadridge builds BMLL historical data and analytics into its EMS and OMS platforms

BMLL’s historical data and analytics are now available within Broadridge’s global sell-side OMS and Xilix EMS for buy-side firms in Japan. Actionable insights and robust analytics are available directly within the workflows of both global sell-side and Japanese buy-side clients - at the point of execution. This empowers Broadridge clients with best-in-class tools to build their strategies and improve trading performance.

Ultumus builds ETF analytics on BMLL data

Ultumus is using BMLL’s high-quality data to assess the impact of its Portfolio Composition File (PCF) service on trading efficiency. A leading European ETF issuer using Ultumus’ PCF, backed by robust BMLL data and analytics, was able to analyse its spread performance, which evidenced a 16% reduction in spread threshold breaches and a 12% performance uplift. The partnership between Ultumus and BMLL will benefit the ETF market overall, leading to increased trading efficiency and robust data quality supporting future ETF launches.

Wamid will build white-labelled cloud analytics tools for Saudi markets on BMLL data

Wamid partnered with BMLL to bring advanced analytics tools to the Saudi capital markets and deliver the region’s first white-labelled cloud analytics tools to quants, analysts and institutional investors. This represents a significant leap forward in market transparency, insight-led decision-making, and the development of a more sophisticated market infrastructure in Saudi Arabia.

Aquis built its Metrics Warehouse and Market at Close analytics on BMLL data

Aquis launched its Metric Warehouse to carry out large-scale analytics and provide bespoke performance metrics to its customers, which showcase market quality and optimise liquidity. Aquis chose BMLL’s ready-to-use, normalised Level 3, 2 and 1 order book data for all European venues to build this analytics service. Aquis also developed its Aquis MaC analysis using BMLL data, demonstrating the benefits of Aquis’ “Market at Close” service, which allows members to post orders at the same price as the primary exchanges during the close.

Pico and Exegy combine their real-time data with BMLL’s historical data to help clients build their execution strategies

The strategic partnerships between Pico and BMLL Exegy and BMLL respectively address the growing need for access to real-time and historical data sets simultaneously to accelerate research, understand liquidity dynamics, and optimise trading outcomes.

The collaborations allow quants and high-performance traders to streamline their workflows as they move through their journey from research to testing and into production.

New market data standards are here to stay

We’ve been working tirelessly to raise the quality of historical market data across the industry, and we are proud to play our part in setting this new standard, alongside our clients and partners - who only ever demand more from their data. And rightly so. If you get normalisation only 95% correct, then you should not bother. What’s more, making poor-quality data usable is very expensive - firms that focus on the Total Cost of Ownership (TCO) are better able to drive their market data fees down.

At BMLL, we obsess over the edge cases, worry about the fine detail, and we do this so that our clients don’t have to. Some consider this the mundane part, but we don’t! We’re delighted to see the industry as a whole benefit from high-quality order book data that is easily accessible and ready to use. This means firms don’t need to hire Picasso to do the menial data curation job; they can hire quants to do what they do best: build successful trading strategies.