In fintech, the technology roadmap is meant to serve as the bridge between ambition and execution. It’s where strategy becomes real. Where it is translated into systems, products, and capabilities that drive revenue, manage risk, and create your firm’s competitive advantage.

And yet, in many organisations, the roadmap quietly becomes something else entirely: a political football, a dumping ground for ideas, or worse, a mechanism that consumes vast resources while delivering very little commercial value. This kills morale.

I’ve seen this pattern repeat across firms of different sizes and maturities. The problem isn’t a lack of intelligence or effort. As it turns out, running a technology roadmap that actually delivers business value is far harder than most teams and leaders expect.

Let’s explore why.

The core challenges

1. The roadmap becomes more negotiation and less strategy

In theory, a roadmap should reflect clear business priorities: growth in scale and revenues, efficiency and risk reduction.

In practice, it often reflects internal compromise.

Senior stakeholders push their agendas. Product teams advocate for features. Engineering leaders argue for platform work. Before long, the roadmap is less about “what matters most” and more about “what survived the negotiation.”

The result? A diluted set of priorities that lack focus and fail to move the needle.

2. Delivery reality is disconnected from planning

Many fintech roadmaps are built in clean, logical layers with quarterly milestones, neatly sequenced dependencies and well-defined outcomes.

But delivery doesn’t behave that way.

Hidden complexity, legacy constraints, and unclear ownership of the roadmap creates friction. Teams discover too late that “simple” initiatives are anything but. Timelines slip, scope expands, and confidence erodes.

Without constant recalibration, the roadmap quickly becomes science fiction.

3. Non-commercial work creeps in

This is one of the most damaging and least discussed issues.

Work that has no clear commercial value finds its way onto the roadmap:

• Features with no measurable customer impact (how would you define this within an OKR?)

• Internal tools built “just in case”

• Platform investments with vague or distant/untested ROI

Sometimes this work is well-intentioned. Often, it isn’t properly challenged and can reflect a culture of fear to not speak up and push back.

Over time, it crowds out the initiatives that actually drive revenue or reduce cost.

4. “Dark work” happens under the surface

Every organisation has it.

Work that isn’t formally prioritised, but happens anyway:

• Side projects driven by influential stakeholders (sometimes that person is the darling of the CEO, so people feel they can’t call it out)

• Engineering efforts justified as “technical necessity” but never validated

• Quiet reallocations of time to avoid difficult conversations

This “dark work” is rarely visible in governance forums, but it consumes real capacity.

And more importantly, it signals something deeper: a breakdown in trust and alignment and allows toxic culture to breed when people don’t speak up out of fear.

5. Culture undermines execution

You can often diagnose a failing roadmap by looking at the culture around it:

• Teams reluctant to challenge weak ideas

• Leaders rewarding activity rather than outcomes

• A lack of transparency about trade-offs and constraints

In these environments, the roadmap becomes performative and is just a waste of time. It looks structured, but it doesn’t guide real decision-making.

What it takes to make a roadmap work

Fixing this isn’t about better templates or more detailed plans.

It requires discipline in a few critical areas:

Ruthless focus on commercial value

Every initiative should be able to answer a simple question: how does this create or protect value?
If it can’t, it shouldn’t be there.

Continuous reality-checking

Roadmaps are not static documents. They need constant pressure-testing against delivery reality… what’s actually happening on the ground.

Radical transparency

Work should be visible. Trade-offs should be explicit. If something is being done, it should be acknowledged and justified.

Willingness to say no

This is where most organisations struggle.

Saying no to senior stakeholders, legacy ideas, or “nice-to-haves” is uncomfortable, but essential.

Where Agile Mind typically helps

This is exactly the space where Agile Mind adds value: bringing an independent, delivery-focused lens to technology roadmaps that have become noisy, overloaded, or misaligned.

Concretely, that often means:

1. Reviewing the roadmap through a commercial lens

Stripping back the plan to identify:

• What genuinely drives revenue or strategic advantage

• What is speculative or low-value

• What should be stopped altogether

2. Keeping the roadmap honest and on track

Working with teams to:

• Align delivery reality with stated plans

• Identify and flag risks early

• Reprioritise based on evidence, not optimism

3. Identifying and removing non-viable work

Challenging initiatives that:

• Lack clear outcomes

• Have a weak business case

• Exist primarily due to inertia or politics

4. Sniffing out “dark work”

This is often where the biggest gains are hidden.

By engaging across teams - not just leadership layers - it becomes possible to uncover:

• Unofficial workstreams

• Misaligned incentives

• Capacity being quietly diverted elsewhere

Once visible, these can be addressed directly.

5. Calling out cultural issues that block delivery

Not diplomatically for the sake of it, but constructively and clearly.

Without your firm addressing the underlying behaviours, no roadmap will hold.

Final thought

A technology roadmap should be a sharp instrument. It should cut through noise, focus effort, and drive measurable outcomes.

If it’s doing the opposite - absorbing energy without delivering value - it’s not just inefficient. It’s actively harmful.

The good news is that this is fixable. But it requires honesty, discipline, and often an external perspective to challenge what’s really going on beneath the surface.

If that resonates, it’s probably time to take a harder look at the roadmap you’re running.

In mid-February 2026, Mony Group, the owner of MoneySuperMarket, the price comparison website, lost £144m in value. The stock price fell by 18% after ChatGPT ate their lunch after launching their own insurance price comparison tool. Naturally, investors took flight when they realised MoneySuperMarket’s business model was easy picking for AI-powered competitors. Christian Dery, of Capital Fund Management, gave this ominous warning: “Firms with generic business models, low barriers to entry and high risk of automation will not survive.” (Source: Telegraph.)

This makes you think that in an age of APIs, your technology platform might be calling out to a number of external APIs in the name of data sharing and easy access, but this example shows how vulnerable a business model these price comparison sites are when a bunch of API calls can be so easily replicated by an AI tool at a fraction of the cost.

I’ve been advising firms recently on AI usage and it is perfectly rational that people in leadership are worried about the operational and security risks of AI agents; yet this example of MoneySuperMarket is in a whole different category. The innovator’s dilemma here is to look at your business model and realise that what was effective just a year ago can be made obsolete in an afternoon.

Take a serious look at your business model if you want to still have a business. This isn’t a technology problem…

Whilst the obvious aspects of technology due-diligence need to be taken into account (e.g. system architecture and software design cyber security, infrastructure and deployment, usability of their GUI, etc.) there are some crucial factors to consider, given the dynamic nature of the tech industry, combined with the volatility of early-stage tech ventures.Evaluating a tech firm is more that data alone.

Three top tips from our extensive CTO tech background in software and technology include:

1. The strength, experience, and, critically, cohesion of the founding team are vital during discovery. We look for a team who can articulate a clear vision, showing relevant industry experience, and how they have been able to pivot to get this far. We look for indicators of risk that include high turnover, lack of technical leadership, or founders who don’t a solid track record: we saw this recently with a scale-up firm that didn’t have a strong CTO and they suffered a serious cyber attack due to not having a strong technical background, leading a team that was too junior.

2. Is the software proprietary or easily replicated? Has the startup filed patents or developed defensible intellectual property? We help clients assess whether the tech is scalable and whether it can sustain a competitive advantage, especially when AI is shaking up business models that are repeatable and easily replicated by large-language models.

3. How are they demonstrating product-market fit? What is the actual demand for the product, and does the ARR show there is a runway for growth at scale? The firm must have data to prove they are on top of a pressing problem and developed a solution people are willing to pay for, and that has features developed and on the product roadmap that are more attractive than competitor offerings. We look for user traction, engagement metrics, and feedback from early adopters to validate what the leadership team talk about.

We are cognisant that your primary objective is generating a healthy return for investors, and that means putting your capital into a venture that has risks. With our help, we believe you will be able to manage those risks, both at the onset and on an ongoing basis.

If you’d like to bring in a technology due-diligence partner who can blend scepticism, insight, and vision, then we can help you evaluate the team, technology, market, so you can make more informed and confident decisions.

If there isn’t a single person who owns all the priorities you may be wondering why nothing gets done in time…

Delivering for your customers sets an expectation that you will get products to them when you say you will, and without error. Nothing slows down those deliveries like context switching does. When engineers have to shift their focus to put out fires or deal with ad-hoc requests from ‘the head of…’ it kills productivity. Something I’ve done for over a decade is to only have a couple of designated people to handle production problems on a rota basis. It prevents everyone from piling in to deal with an issue and the roadmap grinding to a halt.

A single person, let’s call them the roadmap owner (a CEO or a product manager), responsible for priorities on your tech roadmap is not a choke point. They are a necessity to get your teams focused on what is most commercially important and gives them the ability to say no to ‘just a little request’ that people try to slide in under the counter.

Other requests can be added to the backlog but they can only be requested for the roadmap owner to review and need a business case to justify being looked at (revenue projection or cost savings otherwise it’s a waste of time).

The roadmap owner will also ensure there isn’t an overwhelming number of items in flight. People need to feel that what they are working on is important and achievable. I tend to advocate for a top 5 or 6 items. Anything outside of that isn’t of interest to teams in the middle of getting the items assigned to them done by an agreed date.

Doing less gets more done!

“Strategy is a commodity. Execution is an art.”

Peter Drucker

Why is execution an art? Simply due to so many things that can go wrong, especially with technology deliveries. Delays in hardware arriving for a new data centre (not everyone uses cloud in low-latency trading!), requirements were not properly understood and your customer tells you the product you have so far is wrong.

People not communicating effectively across teams add complexity and miss key data, such as whether a data store was being replicated to a disaster recovery site (whoops, we assumed it was). Leaders can become accustomed to delegating everything and as such don’t know what is happening on the ground and people are not inclined to put up their hands that they are in trouble until it is too late and the client deadline is now going to slip.

A lot of stars have to align to get all the inputs, ingestion of requirements and data, through to outputs that bring value to customers.

The best product and tech people are paranoid. It’s not that they don’t trust people; they just know the art of getting things done means having a close relationship with the delivery teams and not having layers of communication.

People who are familiar with exchange-traded equities will find some interesting differences with bilateral trading of equities, which is gathering momentum for a number of reasons:

1. Lower fees/commissions;

2. Access to non-banking providers who are offering their own portfolio of shares to clients;

3. Ability to execute orders away from exchanges and traditional brokers that won’t impact markets and reduce signalling risk

You are sending through an order request to an SI (systematic internaliser), not an order to a central party such as an exchange. This is because in OTC trading, the liquidity provider isn’t obliged to accept your order and can reject your order request (note that for our purposes liquidity provider and systematic internaliser are interchangeable terms). You can have multiple liquidity providers competing for your order if you are dealing with a multi-party trading venue.

This is a new way of trading equities and is allowing people to use APIs that are not dissimilar to FX (streaming prices over a FIX API, or ITCH, with a separate orders session on FIX), given one is dealing with effectively a spot product with usually a single leg, e.g. buying Rolls Royce shares is behaviourally no different from buying EUR/USD from an FX liquidity provider.

As reported by The Trade News, in Q1 2025, systematic internalisers (SIs) made up approximately 14% of European equity execution activity, so this is an area of growth.

One of the major technology challenges for platforms offering bilateral liquidity is that each day there are thousands of symbols to consume, as well as new listings or old ones being removed, which has implications for reference data and caching latest prices for clients to be able to request and get a real-time streaming response. I led a team that got the first multi-SI bilateral equities platform launched at Reactive Markets, so if this is something that you want advice on how to get going, or just to understand that market, then feel free to reach out.

When clients engage me on AI , they are increasingly looking at agentic AI use-cases. I try to make clear that they need to be very bounded in those use-cases. When I was building fully-automated trading systems, we spent a lot of time building circuit-breakers and firewalls as part of the delivery. Why? Simply because we didn’t trust the system not to be stupid, dangerous and market moving (nor did our regulators and compliance colleagues). So it goes with other use-cases that involve systems operating autonomously. As the famous 1979 IBM idiom goes:

“A computer can never be held accountable.

Therefore a computer must never make a management decision.”

By all means, use AI agents to automate tasks, or scan vast amounts of data for patterns and insights, trading strategies, cyber threats, KYC and onboarding automation, as these lend themselves to AI agents. BUT, so long as you are guarding your IP, business priorities and strategy, AI need not be involved.

Don’t forget, your edge is knowing technology but also in having the human big picture and nuance to make informed decisions about what your business needs to be doing next.