Is Technical Debt Really The Problem?

Is Technical Debt Really the Problem?

Technical debt has become one of the most familiar challenges facing established technology businesses. But what if technical debt itself is not actually the problem firms should be measuring?

In this episode of FinTech Focus TV, Toby Babb is joined by Steve Grob, Founder at Vision57, for a wide-ranging conversation about the evolution of capital markets technology, the growing complexity facing established platforms and what firms need to consider as they prepare for the future of trading.

The discussion begins with an unusual comparison between ageing in the human body and ageing technology platforms. From there, Toby and Steve explore technical debt, legacy technology, major transformation programmes, strategic decision-making, AI, platform technologies and the changing structure of global financial markets.

With trading environments becoming increasingly complex and technology more deeply embedded in how financial services businesses operate, the conversation raises an important question for leaders across FinTech and capital markets: are firms focusing on the right technology problems?

What ageing can teach us about technical debt

The inspiration for the conversation comes from an article Steve wrote titled “Has your firm had its Gompertz moment?”

Steve explains that he regularly looks outside financial technology for different lenses through which to understand the industry, drawing on areas including life sciences, mathematics and physics. In this case, his thinking began with the ageing process and whether the rate of deterioration remains constant as someone gets older or accelerates.

His research led him to Benjamin Gompertz, a British actuary who, in 1825, examined mortality and developed what became known as Gompertz Law. Steve explains that the principle suggests the chances of dying double every seven to nine years.

However, it was the reasoning behind accelerating ageing that Steve found particularly relevant to capital markets technology. He explains that as the body ages, its ability to repair itself deteriorates. This prompted him to consider whether the same concept could be applied to technical debt and legacy technology.

Rather than asking whether technical debt is getting worse, Steve suggests that technology leaders should consider whether their organisation's ability to repair its systems and keep its platform fresh is improving or deteriorating.

The comparison becomes particularly interesting when Steve maps biological repair mechanisms onto technology practices. In technology, capabilities such as refactoring, documentation and retaining experienced senior engineers all contribute to a platform's ability to repair itself.

It changes the focus from simply measuring the accumulation of technical debt to examining whether a business still has the capabilities required to manage it.

Why capital markets technology becomes harder to repair

Every technology platform is fighting against increasing complexity.

Steve explains that a quick fix can be relatively straightforward when a company and its engineering team are small. When hundreds of engineers are maintaining a large platform, however, those decisions can compound.

People who originally built parts of the technology leave. New engineers arrive without the same historical understanding. Documentation may be incomplete. At the same time, the environment surrounding the platform continues changing.

Capital markets firms might need to introduce another asset class, respond to new regulation or adapt their technology to new ways of trading. The result is that the ability to “reverse age” an established technology platform becomes progressively more difficult.

For technology leaders, Steve argues that this means looking beyond whether individual systems are functioning today. Firms also need to understand what happens when something goes wrong. He points to the importance of considering the “blast radius” of a failure: does one issue affect a small isolated part of the platform, or can it disrupt the entire system?

These questions become increasingly important as capital markets technology grows more interconnected and the demands placed on trading infrastructure continue to increase.

The future of trading will create even more complexity

If capital markets technology is already complex, Steve believes the pressures facing it are only going to increase.

During the episode, he points towards the emergence of always-on trading, prediction markets, perpetual futures and intraday options. At the same time, characteristics associated with different asset classes are beginning to overlap.

Crypto markets add another dimension because much of their infrastructure was developed without the legacy assumptions embedded in technology created decades ago. Steve highlights instantaneous settlement as one example of how those expectations can differ.

The commercial and technological pressures are also changing. Steve expects firms will increasingly need to process larger numbers of smaller orders, execute them faster and potentially make less money from each individual transaction. At the same time, the consequences of technology failures, including regulatory penalties, remain significant.

For firms operating across financial markets, this creates an environment where maintaining resilient, adaptable trading technology becomes increasingly important.

It also means the decisions organisations make around technology investment, engineering talent and long-term platform strategy today could have a significant impact on their ability to compete tomorrow.

Why long-term technology investment can be difficult

If maintaining and repairing technology is so important, why does technical debt become such a persistent problem?

Steve argues that some of the answer comes down to relatively basic principles.

Refactoring is one example. In simple terms, Steve describes it as going through existing code and removing the unnecessary complexity that has accumulated, comparing the process to clearing out a garden shed.

The difficulty is that refactoring requires resources. It needs time, budget, people and energy, while the immediate outcome might not appear to make the platform do anything new.

Technology leaders can therefore face a choice between investing in the long-term health of the platform and delivering a new feature that a client wants now.

Toby and Steve discuss how organisational pressures can naturally encourage short-term decision-making. The benefits of a major investment in technology resilience might not be visible during the tenure of the person making that decision.

Steve also highlights another dynamic. As the tipping point approaches and the risks surrounding an ageing platform become more obvious, organisations may finally decide to act. By that point, however, the challenge can be significantly harder to address.

The firms that manage this effectively, Steve suggests, are those willing to take a longer-term view and absorb complexity on behalf of their customers rather than prioritising only immediate returns.

Why major technology transformation programmes fail

The conversation then turns towards another persistent challenge in financial services technology: major programmes that stall or fail.

Toby raises the significant cost of unsuccessful technology programmes and asks why businesses continue to struggle with large-scale transformation.

Steve believes one of the problems comes from the way technology budgets and projects are initiated.

Someone wants a problem addressed but initially encounters resistance. Eventually, approval arrives, and by that stage there can be significant pent-up demand to demonstrate progress.

Instead of taking time to understand the problem fully, teams can rush into prototypes, coding and visible activity.

When the resulting technology is eventually shown to users, the response can effectively become: this is what we originally asked for, but now that we understand the problem better, it is not what we actually need.

The organisation has delivered something, but it has solved the wrong problem.

In other cases, technology can simply automate an existing inefficient process rather than questioning whether that process should exist in its current form at all.

This is where strategy, technology leadership and an understanding of the wider business become critical. Successful financial technology transformation is not simply about producing more technology. It is about identifying the right problem before deciding how technology should solve it.

Better technology leadership starts with better questions

One of the recurring themes throughout the FinTech Focus TV conversation is the importance of asking better questions.

Toby draws a comparison with leadership more broadly, discussing the idea that exceptional leaders are not necessarily those who always provide the best answers. Instead, they can be the people capable of asking the best questions.

For capital markets technology leaders, this means challenging assumptions before committing significant resources to transformation.

Steve suggests that firms should begin at board level by asking what their industry is likely to look like in five years.

From there comes another question: how is the business going to make money in that future environment?

Only then should leaders examine whether their current organisation and technology infrastructure are capable of executing against that vision.

That process might reveal a need for new asset classes, algorithms, geographical capabilities or other areas of investment. But critically, those decisions emerge from a longer-term vision rather than a series of disconnected short-term requirements.

Steve summarises his approach with perhaps the simplest question of all: why?

Why does the business want to make a particular technology investment? Why does it believe there is a commercial opportunity? Why does it have the right to make money from that market?

The questions can become existential, but failing to ask them can leave organisations investing heavily in technology without a clear understanding of what they are ultimately trying to achieve.

AI in capital markets still requires human expertise

The importance of questioning assumptions leads naturally into a discussion about artificial intelligence.

Toby and Steve are both active users of AI, but the conversation highlights the importance of subject-matter expertise when using these tools.

Steve explains that getting the most from AI requires understanding the topic well enough to recognise when the model has produced something incorrect. Rather than simply accepting an initial answer, he advocates challenging AI models and asking them to identify reasons why their own conclusions might not be true.

For Steve, AI is therefore not necessarily about taking shortcuts.

In fact, he says using AI can make a task take longer because it creates opportunities to continue questioning, rephrasing and exploring different paths. The benefit is not simply speed; it is the potential to achieve a better result.

This distinction is particularly relevant across financial technology and capital markets, where specialist knowledge can be essential to evaluating outputs.

Toby similarly discusses seeing highly experienced professionals second-guess their own knowledge because an AI tool has given them a different answer. The technology has significant capability, but the episode reinforces why human judgement and deep industry expertise remain important.

As AI becomes more integrated into financial services technology, the value of professionals who can combine technical capability with genuine capital markets knowledge could become increasingly significant.

How platform technology could reshape trading

Looking further ahead, Steve believes platform technologies will be central to the future of capital markets.

Today's trading environment is structured around technologies including execution management systems, order management systems and smart order routers. These tools reflect the ways humans currently interact with technology and markets.

Steve imagines a future where that interaction changes substantially.

Rather than a trader manually deciding exactly how to execute an order, they might define an intention. They could request a certain amount of exposure by a particular time, with requirements around information leakage or other execution conditions.

Intelligence and orchestration technology could then determine the best way to achieve that outcome across equities, futures, ETFs, bonds, prediction markets or a combination of different instruments.

Execution could become dynamic, adapting continuously to what is happening in the market while still working towards the trader's desired outcome.

If that happens, even the familiar trading screen could change.

Steve raises the possibility that the traditional blotter, with the green and red indicators that market participants have looked at for decades, may eventually disappear. Instead, screens could increasingly focus on monitoring and exception handling while AI performs more of the underlying activity.

For capital markets technology professionals, this represents a fundamental change in how people, platforms and markets could interact.

Compute futures, prediction markets and multi-asset trading

Towards the end of the episode, Toby asks Steve to look ahead at the trends he expects could dominate conversations over the next 12 to 18 months.

One area Steve is particularly excited about is compute futures.

With enormous amounts of capital being invested in AI, Steve expects businesses will increasingly need ways to manage risk around compute or GPU time and the power required to support it. He predicts this section of the futures market could ultimately become as significant as power and gas, with participants using the market both to hedge risk and speculate.

Prediction markets are another area Steve expects to remain important. Whatever people think about them, he believes they are here to stay.

Beyond trading directly on prediction markets, Steve is particularly interested in their potential value as trading signals. They provide access to what he describes as the “wisdom stroke folly of crowds,” creating another source of information that market participants could incorporate into decision-making.

His final prediction concerns multi-asset knowledge.

Steve compares understanding asset classes with learning languages. A market professional might have one “mother tongue”, which in his case was futures and options. Learning the second language is difficult, but each additional language can become easier.

He expects professionals across the industry will increasingly need to become fluent across multiple asset classes and geographies as the boundaries between markets continue to change.

Building the financial technology skills of the future

For Harrington Starr, these themes connect closely with the changing financial technology talent landscape.

As a FinTech recruitment business working across financial services technology, capital markets, trading technology, software engineering, data, AI and other specialist areas, we see how changes in technology strategy can influence the skills organisations require.

The episode highlights why future technology teams may need more than expertise in an individual system or asset class. As trading platforms become more interconnected, AI becomes embedded into workflows and businesses rethink legacy technology, professionals who understand how different technologies, markets and business requirements fit together could become increasingly valuable.

Steve's argument around the ability to repair technology is also ultimately an argument about people. Refactoring requires engineering resources. Effective documentation requires knowledge. Maintaining complex platforms requires experienced technology professionals who understand both existing infrastructure and where the market is heading.

Technology strategy and talent strategy cannot therefore be viewed entirely in isolation.

Is technical debt really the problem?

The central message from this episode of FinTech Focus TV is not that technical debt does not matter. It is that measuring technical debt alone can miss the bigger question.

Every technology platform ages. Complexity accumulates, requirements change, engineers move on and the financial markets surrounding those systems continue to evolve.

The crucial differentiator may be whether an organisation retains the ability to repair, modernise and adapt.

For financial technology firms, banks, trading businesses and other organisations operating across capital markets, that requires long-term thinking. It means asking why before building, understanding the problem before creating the solution and considering what the business needs to become before deciding what technology it needs today.