Can AI Finally Modernise Capital Markets? | Breakfast with Babb

Artificial intelligence is changing how financial institutions develop trading technology, modernise legacy systems and approach software engineering. For an industry where replacing established infrastructure has traditionally been expensive, complex and time-consuming, AI presents an opportunity to accelerate technological change.

But can AI genuinely overcome the barriers that have slowed capital markets modernisation for decades?

In a special Breakfast with Babb episode of FinTech Focus TV, filmed at Andrew's Diner in New York, Toby Babb speaks with Jon Butler, CEO and Co-founder of Velox, about AI-driven software development, modern trading platforms, international expansion and the future of capital markets technology.

Their conversation reveals an important distinction: AI can make software development considerably faster, but successful financial technology still depends on experienced engineers, sound architecture and informed commercial decisions.

Why Is Capital Markets Technology Modernisation So Difficult?

Legacy technology remains a significant challenge for banks, brokers and trading firms. Established trading platforms are often deeply integrated into business operations, making them difficult to replace without introducing substantial costs and operational risks.

Jon explains that Velox was founded to help capital markets development teams build front- and middle-office software faster, whether modernising existing systems or developing alternatives to established vendor products.

Its development platform provides reusable technology components designed to reduce the effort involved in building sophisticated financial applications.

This matters because trading technology is not straightforward to develop. Futures execution platforms, for example, must handle substantial market data volumes while supporting responsive interfaces and low-latency trading workflows.

Jon discusses how Velox's work on a futures execution platform revealed opportunities for new technology in a market historically dominated by established providers.

The resulting business, Future Edge, demonstrates how modern development approaches can create new commercial opportunities alongside internal technology transformation.

For firms operating in trading and exchange infrastructure, the challenge is finding ways to introduce modern capabilities without sacrificing the performance and reliability that financial markets demand.

How Is AI Transforming Software Engineering in Financial Services?

AI is changing the development process by making sophisticated technology more accessible to engineers and reducing the time required for certain implementation tasks.

Jon explains that AI allows developers to interact with Velox's platform using natural language rather than learning every detail of its configuration language and APIs.

This does not mean AI independently creates the underlying high-performance technology. Instead, it helps developers use and connect components that have already been engineered for demanding financial markets applications.

The distinction is important for financial institutions assessing AI-powered software development.

Jon advocates what he calls governed or constrained AI engineering, where AI operates within a carefully designed technical environment.

As he explains:

"One approach that seems to work is you need to limit what AI has to think about. 'cause then it's easier to control."

Rather than allowing AI to make unrestricted technical decisions, firms can use established frameworks, clear boundaries and human oversight to improve development productivity.

This approach is particularly relevant in capital markets, where software must satisfy demanding requirements around performance, resilience and operational control.

The opportunity for organisations investing in Data and AI expertise is therefore not simply to introduce new tools. It is to develop the technical capabilities and working practices required to use those tools effectively.

Will AI Replace Software Engineers in Capital Markets?

One of the episode's strongest discussions concerns how AI could change the structure of software engineering teams.

Jon suggests that AI-assisted development may allow smaller teams to deliver work that previously required considerably more developers.

He illustrates this with a hypothetical example: a project that once required one senior engineer and ten developers might be achievable with one senior engineer and two developers using AI.

This is Jon's illustration of potential productivity gains, rather than a verified industry-wide staffing benchmark.

Crucially, he does not suggest that experienced engineers become unnecessary.

AI can generate code, but senior engineers still need to make architectural decisions, manage development processes, evaluate technical trade-offs and supervise AI-generated work.

Jon argues that the long-term success of a software product depends on much more than the quality or quantity of its code.

Architecture, design, technical debt and maintainability all influence whether a platform remains effective over time.

Jon expands on this argument in his article, “Capital Markets Developers Don’t Play Dice”, published on pages 90–91 of The Financial Technologist – Influence List 2026. He explains why capital markets software development presents particular challenges for AI, including complex business requirements, low tolerance for failure and the importance of maintaining sophisticated codebases. His central argument is that generating code faster does not necessarily reduce the overall cost of software development. Experienced engineers remain essential to ensuring that AI-assisted development produces reliable, maintainable technology.

For Financial Technology employers, this could change how engineering capability is assessed.

Coding proficiency remains important, but the ability to manage complex systems, understand financial markets and make sound engineering decisions may become even more valuable.

This creates important considerations for software engineering recruitment, particularly when financial institutions need professionals who combine specialist trading technology knowledge with experience using AI development tools.

How AI Is Changing Buy and Build in Capital Markets

The conversation also examines how AI is changing the economics of buy and build in financial technology.

Jon's argument is that firms should purchase established solutions where those products meet their requirements, while building the components they cannot obtain elsewhere.

As he explains:

"recognising that we buy it if we can, but we can't buy everything, so we build the bits that we can't."

Buying established technology allows financial institutions to benefit from products developed for multiple customers, rather than repeatedly investing in the same capabilities.

However, banks and trading firms also have specialist requirements that standardised solutions may not accommodate.

AI changes this balance by reducing some of the barriers associated with bespoke development.

Jon highlights exchange connectivity as an example. Well-documented APIs can make certain development and integration tasks particularly suitable for AI assistance.

He also explains how existing legacy code can provide valuable information when modernising applications, potentially reducing the need to recreate extensive requirements documentation.

For financial institutions, this creates opportunities to reconsider technology projects that previously appeared too costly or difficult.

However, AI does not remove the need for careful investment decisions. Organisations must still consider software architecture, maintenance requirements and whether developing a bespoke solution provides genuine commercial value.

The result is not the disappearance of established vendors, but potentially greater flexibility in how financial institutions combine existing products with their own technology.

Why Is Saudi Arabia Creating Opportunities for Financial Technology?

Beyond AI, Jon discusses Velox's international expansion and growing involvement in Saudi Arabia.

He confirms that Velox has signed an agreement and is working with a major Saudi Arabian bank following a process developed over approximately two to three years.

Jon connects this opportunity to Saudi Arabia's financial sector development and the increasing demand for modern trading infrastructure.

He also highlights growing interest in retail trading, particularly among younger investors who expect sophisticated mobile applications and modern digital experiences.

As trading activity and customer expectations evolve, banks and brokers face increasing pressure to improve their technology.

The conversation also touches on Retail Edge, an initiative exploring opportunities to apply a similar development approach within retail wealth technology.

These developments illustrate how demand for modern financial services technology extends beyond established capital markets centres.

For employers, international expansion also introduces challenges around leadership, specialist engineering expertise and building teams capable of supporting complex financial institutions across different markets.

What Does the Future Hold for AI in Capital Markets?

Jon believes AI could help overcome the inertia that has historically slowed technology investment and modernisation across capital markets.

He sees significant opportunities for financial institutions to accelerate development, replace ageing systems and introduce new products.

However, he also makes an important observation: AI accelerates the implementation of bad ideas as well as good ones.

Making software easier to build does not automatically make every product commercially valuable.

Financial institutions still need to identify meaningful customer problems, understand their technology requirements and make informed decisions about where to invest.

This reinforces the importance of experienced technology leadership and effective change and transformation expertise when organisations undertake complex modernisation programmes.

The companies that benefit most from AI may not be those generating the greatest amount of code, but those combining faster development with strong engineering, clear product strategy and genuine market demand.

The Future of Capital Markets Technology Depends on AI and Human Expertise

AI is creating opportunities to accelerate capital markets modernisation, improve software engineering productivity and rethink how financial institutions develop trading technology.

Yet Jon Butler's central argument is that technology alone is not enough.

The future of capital markets software development will still depend on experienced engineers, effective architecture, human oversight and the ability to distinguish worthwhile innovation from unnecessary complexity.

For banks, brokers and FinTech companies, this creates both a technology challenge and a talent challenge: developing the capabilities needed to modernise financial infrastructure while making effective use of AI.