PR, Communications and getting your Fintech Story Right
29 October, 2025
Redefining Market Data and Trust in Trading Technology with BMLL
In this episode of FinTech Focus TV, recorded at the Future of Capital Markets Tech Summit: Buy AND Build Event 2025 in London, Toby sits down with Paul Humphrey, CEO, and Elliot Banks, Chief Product Officer of BMLL, to explore how market data is evolving, why trust has become the cornerstone of innovation, and how FinTech firms can make smarter choices in the ongoing buy versus build debate.
This discussion offers an inside look at how BMLL is reshaping the trading technology landscape by enabling financial institutions to access, understand, and act on high-quality, full-depth historical market data. It’s a conversation that captures both the technical complexity and the strategic transformation driving the sector, and one that speaks directly to the evolution of FinTech talent, engineering, and data expertise.
The Changing Landscape of Market Data in FinTech
The conversation opens with a recognition that data quality is now the defining factor in trading success. As Paul Humphrey explains, BMLL specialises in full-depth, Level 3 historical market data, providing engineered datasets that are ready to use from day one. This isn’t simply about collecting information; it’s about making data usable, standardised, and reliable for trading firms that depend on it to drive decision-making and performance.
At its core, BMLL’s mission is to remove the heavy lifting associated with historical data engineering. By managing the “pain and the edge cases,” as Paul puts it, BMLL enables its customers to hit the ground running, freeing up their technical talent to focus on innovation rather than data preparation.
This has become particularly crucial as trading and financial technology have grown more data-dependent than ever. In modern markets, no one can trade effectively without being an engineer in some capacity, which means the quality of data underpinning those algorithms and systems is critical. Feeding poor-quality data into a high-performance trading model, Paul notes, inevitably undermines performance. The margin for error is gone; the quality threshold has never been higher.
From “Build or Buy” to “Build on Trust”
The Future of Capital Markets Tech Summit: Buy AND Build Event 2025 theme is a timely one for this discussion. Historically, financial institutions faced a binary choice when it came to their data infrastructure, buy raw market data and build internal systems to manage it, or build everything from scratch in-house. For many, there simply wasn’t a viable option to buy a complete, high-quality solution. As a result, only the most sophisticated firms, armed with deep resources and teams of quantitative engineers, could achieve the necessary standards.
BMLL has changed that equation. By engineering data at scale, normalising it, and packaging it into ready-to-use platforms, the company has democratised access to institutional-grade data infrastructure. Firms no longer need to choose between build or buy. Instead, they can build on top of trusted partners like BMLL, leveraging their expertise while focusing on their own areas of innovation.
This shift from control to collaboration marks a major cultural evolution within financial technology. For decades, many firms were reluctant to trust third parties with something as sensitive and business-critical as their market data. Now, as Paul notes, that mindset is changing. Once the right level of trust is established, backed by proven quality, transparency, and delivery, firms are increasingly willing to partner rather than build alone.
Quality Data as the Foundation of AI and Machine Learning
Bringing his product perspective into the discussion, Elliot Banks emphasises that quality market data is now essential for AI and machine learning applications. The more sophisticated trading systems become, the more they depend on structured, curated data lakes that are clean, well-managed, and continually updated.
Elliot explains that firms are now recognising the value of having dedicated specialists who ensure data quality from the start. This not only ensures that data-driven models perform more effectively but also frees up internal engineering teams to focus on what they do best: designing and optimising algorithms, running back tests, and developing analytics.
For trading firms competing in a fast-evolving digital landscape, this focus on data quality has become a differentiator. It’s not enough to have data, you need the right data, engineered to meet the standards of high-performance computing and advanced analytics. As AI continues to transform trading, firms that fail to prioritise data curation risk falling behind in both speed and accuracy.
The Evolution of Trust and Partnership in FinTech
Trust, as both Paul and Elliot point out, has become the defining theme of FinTech partnerships. When BMLL was first introduced to the market, many firms struggled to understand what they offered. The industry was largely divided: a small group of highly technical firms understood the problem and wanted to solve it themselves, while the majority didn’t yet recognise the opportunity.
Over time, that perception changed. By starting at the most complex level, full-depth Level 3 data, BMLL built a foundation that allowed it to expand into Level 2 and Level 1 products. This progression opened up a far broader customer base, proving that what was once considered niche infrastructure is now fundamental to the entire trading ecosystem.
This success has also been reflected in how clients engage with BMLL. The company’s Client Product Advisory Board was created at the request of some of its largest customers, including major global banks and sovereign wealth funds. These institutions wanted direct visibility into BMLL’s product roadmap, ensuring that future developments aligned with their evolving needs and compliance standards.
This transparency has strengthened confidence across the sector. Firms no longer see working with smaller, innovative FinTech providers as a risk, but rather as a strategic advantage. As Paul remarks, the old saying “no one gets fired for hiring IBM” is giving way to a new reality: those who fail to adopt the right FinTech partnerships risk being left behind.
Reducing Total Cost of Ownership through Smart Market Data Solutions
One of the most tangible benefits of partnering with firms like BMLL is the reduction in total cost of ownership (TCO) for market data. Historically, financial institutions managed massive internal teams dedicated to curating and maintaining data infrastructure. Even if they purchased data feeds, they still had to invest heavily in normalisation, storage, and maintenance to achieve the quality required for trading models.
Paul explains that by outsourcing this complexity to a trusted partner, firms can significantly lower their operational overheads while improving performance. Rather than spending time and resources on the mechanics of data engineering, they can redirect their focus to generating value, creating models, strategies, and analytics that directly impact profitability and competitiveness.
This approach aligns closely with trends across the FinTech sector, where firms are increasingly adopting modular, scalable systems that allow them to innovate quickly without bearing the full weight of infrastructure management. In a world where talent shortages continue to impact engineering and quantitative finance, this also makes recruitment and retention far more strategic. Firms can deploy their top talent where it matters most.
A Strategic Shift in FinTech Talent and Engineering Priorities
The BMLL story is not just about technology; it’s also about how FinTech firms structure their teams and deploy their talent. The conversation between Toby, Paul, and Elliot highlights a critical shift, away from building vast internal departments to manage data, and towards leaner, more value-driven engineering teams that focus on innovation and analysis.
This shift mirrors broader changes in the FinTech recruitment landscape. At Harrington Starr, we’ve seen a growing demand for professionals who can combine technical engineering skills with commercial awareness, those who understand both the “how” and the “why” of market data systems.
As automation and AI continue to transform trading technology, firms are seeking people who can integrate data science, quantitative research, and software development into cohesive strategies. Partnerships with data specialists like BMLL make this easier, allowing firms to recruit for creativity, innovation, and problem-solving rather than maintenance-heavy roles.
The end result is a more efficient and scalable approach to FinTech talent, where teams are empowered to focus on higher-level functions and strategic decision-making. It’s a trend that aligns perfectly with the message from this episode: the future of FinTech belongs to firms that build on trust, invest in quality, and use their people where they can make the biggest difference.
The Buy and Build Debate: A New Era for Trading Technology
Throughout the discussion, Toby returns to the event’s central theme, the idea of Buy and Build. For years, this debate has shaped investment decisions in trading technology, with firms forced to weigh the control of building internally against the efficiency of buying external solutions.
What’s clear from BMLL’s success story is that this debate is no longer binary. The future lies in hybrid strategies, buying trusted data foundations and building competitive advantage on top of them. This approach delivers both scalability and specialisation, allowing firms to innovate without compromising reliability.
Paul notes that for many years, historical market data products were treated as the “exhaust” of larger organisations, by-products of trading activity rather than strategic assets. Today, that perception has shifted completely. Data is no longer an afterthought; it’s a core component of competitive strategy.
At the same time, firms are becoming more aware of the real costs of maintaining in-house systems. As Paul explains, reducing total cost of ownership isn’t just about negotiating lower data prices, it’s about rethinking the size of internal infrastructure and the headcount required to sustain it. This is where trusted FinTech providers can deliver real, measurable value.
Building on Trust: The Client Perspective
The Client Product Advisory Board has been instrumental in shaping how BMLL collaborates with its users. Its creation, driven by client demand, reflects the growing maturity of relationships between established financial institutions and emerging FinTech providers.
Clients not only want to use BMLL’s data but also to influence the direction of its development, ensuring that products evolve in line with real-world use cases. For many large financial organisations, this kind of partnership offers the best of both worlds: innovation without unpredictability, and collaboration without risk.
This relationship between trust and transparency underpins the entire conversation. By building credibility through performance and openness, BMLL has overcome one of the biggest barriers facing FinTechs entering institutional markets: the fear of volatility and uncertainty. In doing so, they’ve helped redefine what it means to be a trusted partner in financial technology.
Data Quality, AI, and the Future of FinTech Innovation
As the episode draws to a close, both Paul and Elliot return to the central theme of data quality. For Elliot, the message is clear, data quality is everything. Firms that prioritise clean, well-curated data are setting themselves up for long-term success, particularly as artificial intelligence and automation continue to evolve.
Paul adds that firms that truly want to lower costs and innovate must open their minds to partnership. The next generation of FinTech success stories will come from organisations that recognise the value of collaboration, quality, and efficiency. In a world where AI systems are only as good as the data that powers them, there is no room for compromise.
Ultimately, both guests agree that the timing of this transformation couldn’t be better. The industry is ready for it. Firms are more data-driven, more collaborative, and more focused on value than ever before. And as Toby concludes, the key is ensuring that the best people are doing their best work, not stuck cleaning data, but creating the innovations that will shape the next generation of FinTech.
Conclusion: FinTech Recruitment and the Power of Partnership
This FinTech Focus TV episode from the Future of Capital Markets Tech Summit: Buy AND Build Event captures the heart of a movement transforming financial technology: the shift from isolation to integration, from control to trust.
For FinTech recruitment, the implications are significant. The industry now requires a new blend of talent, data engineers who understand financial markets, quants who can collaborate with AI models, and business leaders who recognise the strategic value of partnerships like BMLL.
At Harrington Starr, we continue to see how firms that embrace this mindset are leading the way, attracting better people, building more resilient systems, and creating the kind of workplaces that define the top 1% of the industry.
As BMLL demonstrates, when quality, trust, and talent converge, the future of FinTech isn’t just built, it’s built better.
