Rethinking cross‑border payments: Market Town’s Bitcoin approach from Edinburgh
Written by Henry Murray-Smith, Market Town
“Imagine a contract where every January first, forever, I will give you one dollar. You can sell and transfer this contract. You want to sell this contract to Charlie. How much does he pay?”
This question is really asking “why is a dollar today worth more than a dollar tomorrow?” and is as fundamental to finance as a writer of the English language starting on the left hand side of the page. Charlie buys the contract for about eight dollars.
In 2021, five years into an informal financial education, I stood in the kitchenette of a data centre waiting for tea to brew, closing a wealth management textbook from the CISI (the Chartered Institute for Securities and Investment). Concluding my first reading I was more certain finance was, at its most favourable angle, a hot mess. And for all the detail and breadth of my education, I still had no idea what money was.
Some years later, the best definition I can muster is that money is part of human nature. It’s a phenomenon that appears with any collection of people, expressed through technology. My favourite example is cigarettes in prison, because they’re so perfectly divisible and scarce. They also have a practical purpose: you *can* save them to trade another day, or smoke one in a moment of reflection. But step outside prison and cigarettes are no longer tender. A shopkeeper will no sooner trade cigarettes for groceries than they would accept a nugget of gold.
When investigating money, the inevitable subject of Bitcoin appeared. My cynicism only began to erode reading Fidelity’s ‘Bitcoin First Revisited’ which explains why Bitcoin, not the thousands of other ‘web3 projects’ satisfies the properties of money to a greater degree than fiat currencies and gold. I still despised its energy consumption, because I hadn’t connected the dots that, if electricity is almost all of your running costs, finding stranded and renewable energy would be incentivised.
I also hadn’t considered the energy cost of the current system: millions of offices, bank branches, and autoteller machines serviced by vehicles – that system full of failure points, gatekeepers and opaque fees. So what backs Bitcoin? Even if fiat currency isn’t backed by gold (anymore) it’s backed by a government’s ability to raise taxes and sell bonds. Well, it takes a lot of energy to mine one Bitcoin, almost a hundred thousand US dollars of electricity. It can’t be created without significant cost. Saying it’s backed by energy doesn’t exactly stir the soul, but it is, and the market values that captured energy, or that Bitcoin, very highly.
So why wasn’t there a browser for the Bitcoin network, I wondered? Why didn’t some clever developer build a portal like so many thousands of startups during the early days of the internet, which had Mosaic and Netscape? The sad truth is that many of the innovation dollars went to adjacent crypto projects pretending to be superior to Bitcoin, optimised for different things, and now they’re all fading. Only Bitcoin persists, everything else dies and, yet, few use it as currency.
Today, half a billion people own Bitcoin, most indirectly, and it’s one per cent of global money supply. Numbers like these inspire us to build the future of payments, banking and financial services.
After eighteen months of product development, our mobile app is being designed in California by Alexander Lambert, who led the design, often from day one, of Friendster.com, car sharing platform Getaround.com, and Airkit.com (acquired by Salesforce).
To explore our roadmap beyond global payments, say hello@market.town
Learn more about Edinburgh fintech Market Town and its Bitcoin‑powered cross‑border payments platform.
Aveni extends market leading wealth and compliance platform into consumer agentic AI for financial services
£12m investment accelerates launch of Agent Assure, closing the AI agent safety gap
Aveni, the UK’s leading AI fintech specialist in wealth management, financial advice and banking, today announced a £12 million funding round led by PXN Ventures, the UK’s fastest-growing venture and investments firm outside London and the South East, and supported by existing investors Puma Growth Partners, Lloyds Banking Group, Nationwide and Scottish Enterprise. The investment will accelerate development of Aveni’s Unified Assurance Platform (UAP) and the launch of its new Agent Assure and Agent Approve solutions, purpose-built to assess the conduct risk of AI agents that interact with consumers in financial services.
Aveni is the established market leader in AI adoption across UK wealth and banking, with over seven years of live deployments and product development. Its products Aveni Assist, an AI productivity solution for advisers and operations teams, and Aveni Detect, its AI compliance monitoring tool, are deployed across the UK’s leading banks, wealth managers and financial advisers. Underpinning both is FinLLM, Aveni’s proprietary suite of specialist small language models built for and utilising UK financial services data.
Agentic AI adoption in financial services is accelerating, but deployment at scale is being held back by a critical gap in assurance. With just 2% of firms reporting adequate AI guardrails, the absence of robust, regulated oversight for AI agents that interact directly with consumers is the number one challenge for the industry. Regulators are clear that the mode of engagement, human or machine, is secondary to consumer outcomes, which must be assessed consistently across all interactions.
Agent Assure directly addresses this gap. A natural extension of the Aveni Detect proposition, it enables firms to monitor and manage the conduct risk of AI agents alongside human interactions, in a single unified view. Together with Aveni Assist, Aveni Detect and the new Agent Approve solution, this Assure forms the Unified Assurance Platform: the financial service industry’s first comprehensive framework for assuring both human and agent interactions with consumers at scale.
Aveni is a participant in the FCA’s Supercharged Sandbox programme and has established the Agent Assurance Expert Council to support development of responsible AI governance frameworks. The company is working directly with regulators and industry bodies to shape the emerging standards for AI in financial services.
Joseph Twigg, CEO of Aveni, said: “The continued confidence shown by our existing investors is a powerful endorsement of the direction we’re taking. We have spent seven years building the models, the experience and the regulatory relationships that make us uniquely qualified to solve the hardest problem in AI adoption right now: how do you assure the conduct of an AI agent interacting with a real consumer? Agent Assure is our answer — and this investment accelerates our ability to deliver our full platform at scale.”
Alastair Moore at PXN Ventures, said: “Aveni is fast becoming financial advisers’ go-to tool for helping them leverage AI in a safe and appropriate way. The team now has seven years of live deployments and proprietary models built within the UK financial services sector. Their infrastructure is answering one of the biggest questions in AI adoption: how to manage real client interactions and build trust, so advisers can focus on what they do best. We’re proud to support Aveni through multiple PXN funds, including the Praetura Growth VCT, as they continue their growth journey and demonstrate the world-class fintech capabilities of the North of the UK.”
Ben Leslie, Investment Director, Puma Growth Partners, commented: “The impact Aveni is making in deploying AI into UK financial services is already significant, and we continue to see a substantial growth opportunity ahead. With agentic AI adoption accelerating and regulators rightly focused on consistent consumer outcomes, robust assurance for AI agents is rapidly becoming a core requirement for the sector. As a standout example of Scotland’s growing strength as a technology hub, Aveni is well placed to lead this next phase. We are delighted to invest again from our Scotland office to support Joseph, Jamie, Professor Lexi Birch and the wider team as they scale the Unified Assurance Platform and launch Agent Assure.”
Kirsty Rutter, Fintech Investment Director at Lloyds Banking Group, said: “Agentic AI represents a significant opportunity for financial services to enhance customer experience through more personalised interactions. Aveni is helping firms adopt this technology in a safe and responsible way. We’re pleased to continue supporting Aveni’s ongoing development through investment and partnership.”
The continued backing of existing investors reflects confidence in Aveni’s roadmap and market position. PXN Ventures led the round alongside Puma Growth Partners, Lloyds Banking Group, Nationwide and Scottish Enterprise.
Navigating Consumer Duty: The Hidden Cost of Friction
By Shiyu Chen, behavioural scientist and founder at BehaviourAI Lab
Consumer Duty has reshaped the way financial services firms need to think about customer journey. The FCA’s shift from tick-box compliance to outcome-based evidence doesn’t come with sirens or warning, but it does change the ground we’re standing on.
What used to be a design preference is now part of a firm’s regulator responsibility. And this shift invites a different kind of conversation: not about what we’ve declared to customers, but about what they actually encounter.
It’s time to step back, understanding how user journey shapes outcomes, and to diagnose, redesign, and measure those behavioural dynamics through a behavioural science approach.
Sludge: The Silent Enemy in Consumer Duty
Behavioural scientists often talk about nudges – subtle design choices that help people make better decisions. But there is a darker twin: sludge. Where a nudge supports good outcomes, sludge creates friction that slows, confuses, or traps consumers, often preventing them from acting in their own best interests. Sometimes it’s deliberate. More often, it’s accidental by product of growth driven design.
Under Consumer Duty, however, sludge is no longer a UX flaw. It is a regulatory risk. In other words, user journey is no longer a design preference; it is a regulatory obligation.
From Theory to Practice: Where Sludge Hides
Across the four Consumer Duty outcomes, sludge shows up in predictable and measurable ways. Here are some of the most common patterns observed when conducting behavioural diagnostics:
In Consumer Understanding, sludge emerges when complex layouts bury key risks “below the fold”, leading users to skim past critical information. This becomes visible when users spend only a few seconds on a lengthy Terms and Conditions page before clicking “Accept”.
In Consumer Support, sludge takes the form of exit friction, where cancelling a product requires far more effort than signing up. For example, a two step onboarding journey contrasted with a ten step cancellation process.
In Price & Value, sludge appears through fee shrouding, where total costs are only revealed at the final payment stage, often triggering sharp drop offs when users encounter unexpected charges.
In Products & Services, sludge shows up as dark nudges, such as urgency cues (“Only 2 left!”) that push consumers toward unsuitable choices, reflected in high cooling off cancellations shortly after purchase.
These patterns aren’t simply UX quirks. They are behavioural signals that parts of the journey may be misaligned with Consumer Duty expectations.
Evidence in Practice: Decoding the Metrics
Understanding where harm may emerge in a user journey often begins with simple behavioural signals. Metrics such as reading time vs. scroll depth reveal whether customers meaningfully engage with key information. Similarly, basket abandonment at payment indicates moments where unexpected fees or late‑stage cost disclosures prompt users to drop off.
Other indicators point to friction that distorts decision‑making. The parity ratio can reveal disproportionate effort that may hinder Consumer Support. And the reversal rate often signals that urgency cues or other dark patterns may have pushed users toward unsuitable products.
These metrics don’t provide the full diagnostic picture, but they offer early behavioural clues about where journeys may be creating unintended barriers or risks.
The Behavioural Toolkit: Hook-Fix-Proof
The BehaviourAI Lab offers a structured approach to help financial services firms identify and mitigate sludge before it becomes a regulatory issue. The Hook-Fix-Proof framework integrates behavioural diagnostic, behavioural design, and behavioural validation to improve user journeys.
Hook focuses on identifying the behavioural dynamics that create sludge – the friction points, hidden barriers and decision pathways that shape how users actually behave. This stage surfaces the subtle patterns that traditional UX reviews often miss.
Fix applies choice architecture principles to redesign those pathways, removing unnecessary friction and reducing sludge so that decisions become clearer, smoother, and more aligned with users’ goals. The emphasis is on enabling better choices, not nudging toward predetermined ones.
Proof brings empirical validation, using behavioural measurements to demonstrate whether the redesigned journey truly improves outcomes. This stage provides the outcome based evidence that Consumer Duty now expects – showing measurable behavioural change, not just good intentions.
Is your product journey hiding a Sludge Red Flag?
At BehaviourAI Lab, we help financial services firms diagnose, redesign, and validate their journeys using behavioural science and metrics that evidence Consumer Duty outcomes.
Don’t wait for the regulator to spot the friction. Book a Sludge Diagnostic and get ahead of the risk.
The AI Sovereignty Trap: Why UK Financial Services Are Sleepwalking Into It
By Nagu Gopalakrishnan, Co-founder, Vidai
Governance cannot live at the application layer for regulated platforms. I learnt that running regulatory engineering for the Ads Creative Infrastructure programmes at Amazon, taking us through EU Digital Markets Act and Digital Services Act compliance, MiFID II‑grade regulation for large platforms, with penalties of up to 10% of global turnover. You either build a horizontal control plane that every product team inherits, or you spend the next five years putting out fires one integration at a time.
I am watching UK financial services make the second choice with AI right now. The regulators have already told them not to. And the economics of agentic AI will punish them for it before the regulators do.
The Problem Is Jurisdictional, Not Operational
Most conversations about AI vendor strategy in financial services frame the issue as cost or flexibility. Pick the right model. Negotiate the right rate. Avoid getting trapped on a single roadmap. These are real concerns, but they miss the deeper one.
Extraterritorial data laws are a fact of the cloud era. The US CLOUD Act is the most discussed example: it allows US authorities to compel any US‑headquartered provider to disclose customer data they hold anywhere in the world. Other jurisdictions have similar mechanisms. The relevant question for a UK‑regulated firm is not ‘which country?’ but ‘how many jurisdictions does my AI stack expose me to, and have I done it consciously?’.
Data residency clauses help less than they appear to. A contract with your UK‑region cloud provider has no force over the frontier model providers your applications then call into; those are separate contractual relationships, often with different jurisdictional anchors. The EU‑US Data Privacy Framework offers some cover for one specific corridor, but it has been struck down twice already and faces a credible third challenge.
For a UK firm serving Scottish or EU customers, every model API call sends data outside the protections that residency contracts negotiated — and across an agentic workflow, those calls compound into exposure most firms cannot quantify.
This is precisely the concentration risk the UK’s Critical Third Parties Regime (CTPR) was designed to confront. CTPR is, at its heart, about systemic dependencies on a small number of providers serving the financial system. A single AI provider handling AML triage, customer correspondence drafting, claims assessment or internal policy retrieval is the textbook example.
Agentic AI Makes It Worse and More Expensive
The shift to agentic AI changes this calculus by an order of magnitude. When a human asks a model a question, the data exposure is one prompt. When an agent runs a fifty‑step reasoning loop touching customer records, transaction history and internal policy documents, every step is a potential exposure path, and every step is a billable token.
Forrester predicts machine‑initiated traffic to financial institutions will surge by 40% by the end of 2026, while human visits drop by 20%. That is not a usage statistic. It is simultaneously a sovereignty exposure curve and a cost curve. Most current AI governance tooling was built for neither. Whether you are a tier‑1 bank, an insurer, an asset manager or a fintech selling into regulated buyers, the maths is the same.
The cost side of that curve is worth dwelling on. A workflow that costs pennies in pilot can cost five‑figure sums per day in production once the agents start chaining. Most finance teams in regulated firms were not staffed to forecast that, and most current AI tooling does not give them the visibility to try.
The dominant approach today is to bolt observability and policy enforcement into application‑side libraries written in Python or Node, designed for episodic human chat traffic. Under sustained machine‑to‑machine throughput, these layers do not fail loudly; they fail expensively. We benchmarked our Rust‑based control plane against a leading Python gateway on identical workloads, and we held up nearly double the throughput‑per‑core on hardware four generations older. The full methodology and source code are public at vidai.uk/blog/rust-python-vidai. The headline number matters less than what it implies: the architecture you choose for your governance layer determines whether multi‑model AI is economically viable at agentic scale, or whether it cannibalises your margins the moment traffic ramps.
The Control Plane Answer
A horizontal control plane, sitting between your applications and the models, should deliver governance across three axes — sovereignty, cost and compliance — and one engineering concession that makes adoption possible.
Sovereignty by design: Vidai runs entirely inside your VPC, deployed in minutes. No SaaS path, no phone‑home, no licence ping, no usage telemetry. We do not see your prompts, your responses or your timing. Your data, your control, your infrastructure. Egress is enforced inside the control plane: you decide what crosses to model providers and what does not, including from your own applications. That removes a class of third‑party dependency a SaaS gateway would add, and that CTPR would expect you to register
Cost governance: Real‑time, per‑team, per‑agent, per‑request, per‑workflow, per‑model spend is the floor. The ceiling is full historical lineage of how pricing changed over time. When a provider shifts rates mid‑year, your finance team can see what the same workload would have cost under the old pricing, what it costs now and what it would cost if re‑routed. Cost‑based routing then closes the loop, sending each workload to whichever provider is cheapest for that latency profile at that moment, not whichever vendor has the lowest headline rate.
Compliance governance: A single security and compliance review covers every model behind the control plane, with full request and response retention for regulatory inspection. Adding a new provider becomes a configuration change, not a six‑month procurement cycle. The ‘sign‑off tax’ that pushes regulated firms towards single‑vendor lock‑in disappears.
A drop‑in path, not a re‑platforming project: Most gateways force engineering teams into an OpenAI‑compatible shape, which means every team using Anthropic, Bedrock or Google native SDKs has to refactor before they can join the control plane or add an additional application‑side library. Vidai sits transparently in front of whatever SDK is already in production. Joining the control plane is a base URL change, not a sprint. That single design choice is often the difference between a multi‑model strategy that ships this quarter and one that lives in a slide deck for two years.
This is what we are building at Vidai, from Scotland, with a team whose backgrounds span hyperscale EU regulatory navigation and national critical infrastructure resilience. The combination is deliberate. The next decade of financial AI will be defined less by which model wins and more by who governs the substrate the models run through.
The Choice for UK Financial Leaders
The UK has a window here that will not stay open for long. CTPR is live. DORA is live. The Bank of England, FCA and PRA are all signalling that AI concentration risk is moving up the supervisory agenda. The firms that build their multi‑model strategy now, on a sovereign control plane they actually own, will be ahead of the requirement when it lands. The firms that wait will be retrofitting under regulatory pressure, on someone else’s timeline.
The goal is not to pick the winning AI model. It is to build the infrastructure that lets you use any winning model without losing control of your data, your budget or your sovereignty.
That is a decision that gets made at the architecture layer, not the application layer. And it gets made now, or it gets made for you.
Localising for North America: Lessons for Scottish Fintechs
By Atlantic Fintech
Expanding into North America is a natural next step for many ambitious Scottish fintechs. The market is large, sophisticated, and innovation-friendly – but it is not a single, unified landscape. Success depends less on scaling what already works at home, and more on adapting thoughtfully across product, language, and market expectations.
At Atlantic Fintech, we’ve worked closely with fintechs on both sides of the Atlantic. A consistent theme emerges: localisation is not a final step – it’s strategy from day one.
North America Is Not One Market
One of the most common misconceptions is treating North America as a single, homogeneous opportunity. In reality, it is a patchwork of regulatory environments, consumer behaviors, and financial systems.
- Canada and the U.S. operate under different regulatory frameworks, with further variation at the provincial and state levels.
- Payments infrastructure differs significantly (for example, Interac in Canada versus ACH and card-heavy systems in the U.S.).
- Procurement cycles, especially in financial institutions, tend to be longer and more relationship-driven than in the UK.
For Scottish fintechs, this means market entry should start with a clear geographic focus rather than a continent-wide approach.
Product Localisation: Beyond Compliance
Adapting your product for North America goes well beyond regulatory compliance. It requires aligning with local user expectations and financial habits.
- Integrate with region-specific payment rails and financial data systems.
- Reflect local financial terminology and user flows (e.g., “checking account” vs. “current account”).
- Ensure your product aligns with local security expectations and trust signals, which can vary by market.
An example: a fintech offering open banking-enabled services in the UK may need to rethink its data access strategy in North America, where open banking frameworks are still evolving and often rely on different providers and standards.
Language and Communication Nuances
Even in English-speaking markets, language localisation matters more than many expect. Subtle differences in tone, terminology, and messaging can affect credibility and conversion.
- North American audiences tend to prefer more direct, benefits-driven messaging.
- Marketing content often leans less on understatement and more on clarity and value proposition.
- Bilingual requirements – particularly in Canada – add another layer. French is not optional in Québec and can strengthen brand trust nationally.
For Scottish fintechs, this is less about translation and more about transcreation: ensuring your message resonates culturally, not just linguistically.
Finding Product-Market Fit
Product-market fit in North America often requires iteration, even for well-established companies.
- Customer expectations around onboarding, UX, and support can differ significantly.
- Enterprise buyers may expect local presence, partnerships, or pilots before committing.
- Pricing models may need adjustment to align with local purchasing norms and budgets.
Partnerships can be a powerful accelerator. Collaborating with local fintech ecosystems, financial institutions, or innovation hubs can provide faster access to networks and insights.
A Note on Atlantic Canada
While Toronto and New York often dominate conversations about North American fintech, Atlantic Canada offers a compelling – and often overlooked – entry point. Atlantic Canada can serve as an effective “soft landing” zone for international fintechs. It allows companies to test, adapt, and refine their North American strategy in a more agile and supportive setting before scaling into larger markets.
The region also shares many similarities with Scotland: a growing fintech sector made up of over 150 ambitious fintechs, strong ecosystem support from government and industry, and a collaborative, community-driven approach to innovation. Scottish companies looking for a familiar yet globally connected environment can benefit from:
- Close-knit fintech and startup ecosystems that enable faster relationship-building.
- Lower operational costs compared to major financial centres.
- Direct access to both North American and European markets through strong trade ties and cultural alignment.
Building for Scale Through Localisation
The most successful fintechs entering North America are those that treat localisation as a growth lever, not a constraint. They invest early in understanding regional differences, build adaptable products, and engage deeply with local ecosystems.
For Scottish fintechs, there is a strong foundation to build on: a reputation for innovation, strong regulatory understanding, and a global outlook. By pairing these strengths with a deliberate localisation strategy, North America becomes not just accessible – but highly scalable.
About Atlantic Fintech
Atlantic Fintech drives fintech innovation and growth across Atlantic Canada’s four provinces: New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland and Labrador. The organization builds a global fintech community by providing startups and scaling fintech companies with strategic connections, industry expertise, and market entry resources. Atlantic Fintech focuses on fostering collaboration and positioning Atlantic Canada as a recognized fintech hub of international relevance.
Atlantic Fintech offers tailored growth programs, specialized mentorship and go-to-market support. Having developed a strong ecosystem that integrates local talent with global fintech markets, leaders praise the community’s growth opportunities, strategic introductions, and educational events that empower companies to compete worldwide and build sustainable fintech ventures.
Remittance Isn’t Broken. The Outcome Is
By Ayodeji Jegede – Co-Founder, MoneyHive
This article represents my independent perspective as a founder, separate from my employed role. It is published by FinTech Scotland, the recognised industry body for Scottish fintech.
For over a decade, remittance has been framed as a problem of efficiency. Faster payments. Lower fees. Better FX. And to a large extent, the industry has delivered. Global remittance flows exceeded $850 billion, with the UK consistently ranking among the top outbound corridors. Yet despite this scale and maturity, the user experience remains fundamentally incomplete. Because the real problem doesn’t sit in the movement of money. It sits in what happens after.
Remittance is rarely the end goal. It is a means to an outcome: rent needs to be paid, school fees need to be settled, electricity needs to be restored, healthcare needs to be delivered. But once money is sent, the system effectively stops. There is no standardised way to confirm that a bill was actually paid, verify that a service was delivered, or track the outcome beyond “delivered.” This creates a structural disconnect between financial infrastructure and real-world execution. The transaction succeeds. The outcome remains uncertain. That gap is where trust erodes.
Why the Current Model Plateaus
The dominant competitive levers in remittance are now commoditised. Speed is near instant. Fees are compressing. FX margins are increasingly transparent. This creates a ceiling. Incremental improvements in these areas no longer translate into meaningful differentiation. More importantly, they do not solve the user’s core anxiety: “Did what I sent actually get done?” This is not a payments problem. It is a completion problem.
The next phase of fintech in this space will not be defined by better rails. It will be defined by what sits on top of them. Three layers are emerging: outcome assurance (systems that confirm completion of the intended action), embedded verification (direct integrations with service providers like utilities, schools and healthcare), and trust as infrastructure (status and proof becoming core product features). This reframes the core question from “Was the payment successful?” to “Was the responsibility fulfilled?”
What We’re Building at MoneyHive
At MoneyHive, we are building around this shift. Not how to move money, but how to ensure money delivers outcomes. This changes product design at a fundamental level: payments become infrastructure not the product, status tracking becomes real‑time and structured, proof of completion becomes a default expectation, and recurring obligations become programmable. The result is not just a financial service. It is a coordination layer between diaspora users and real‑world services back home.
Outside of my employment, MoneyHive has achieved independent validation. We were accepted into Microsoft for Startups, earning $!00,000 in credits (April 2026), a competitive global program. Our application to the FCA Regulatory Sandbox is under assessment with a case officer assigned. We have built an organic waitlist of more than a quarter of 1000 diaspora users from the UK‑Nigeria corridor. MoneyHive is an active member of the FinTech Scotland community and has been accepted into the Techscaler Catalyst programme, a Scottish Government backed accelerator.
Starting in the UK to Nigeria corridor, a few patterns are becoming clear. Users are less sensitive to marginal FX gains than assumed. Visibility consistently outperforms price as a trust driver. Repeat usage is driven by certainty, not convenience. In other words, the strongest retention loop is not “This was cheap and fast.” It is “This worked exactly as expected, and I can rely on it again.” That distinction matters because it defines where long‑term value sits.
Why This Matters for the UK and Scotland
The UK is one of the most important remittance hubs globally, both in volume and diversity of corridors. At the same time, ecosystems like Scotland are increasingly positioning themselves at the intersection of fintech innovation, data infrastructure and cross‑sector collaboration. This creates a unique opportunity because solving for outcomes in remittance is not purely a payments challenge. It requires coordination across financial services, utilities and service providers, identity and verification systems, and regulatory frameworks. This is where ecosystems, not just startups, become critical. The companies that succeed will not operate in isolation. They will plug into networks.
The remittance market is large. But more importantly, it is mis defined. It has been optimised around movement, when it should be optimised around completion. That leaves a significant layer of value unaddressed. The opportunity is not to build another way to send money. It is to build systems that ensure something meaningful happens because of it.
Closing Thought
Remittance has always been framed as a financial transaction. In reality, it is a coordination problem between people, money and outcomes. The industry solved the movement of money. It has not yet solved the delivery of intent. The next generation of fintech companies will. And when they do, the question will no longer be “How fast did the money arrive?” It will be “Did it do what it was supposed to do?” That is where trust is built. And where the next wave of value will come from.
Every Life Moment Is a Money Moment
By Dia Banerji, Founder and CEO, Cherpa.ai
Separation. Redundancy. Having a baby. Losing a parent. Caring for an ageing relative. Retiring.
Every one of these moments comes with money questions. And for most people, those questions arrive at exactly the wrong time, when you are stressed, stretched, and trying to hold the rest of life together.
In some ways, I have been trying to make money simpler for people my whole career. I spent over 20 years in financial services, building products, shaping propositions, and working with customers at scale. I saw the best of what our industry can do, and I also saw a pattern that kept repeating.
The people who need help most are often the least likely to get it.
Not because they are not capable. Not because they are not trying. But because the industry still expects people to work out what they need, hunt it down across multiple sources, and then stitch it together for themselves, translating generic education into decisions that make sense for their own lives, often in the very moments they have the least capacity to do so.
The problem is not knowledge, it is design
Financial services impact everyone and it should work for everyone.
Yet the experience most people have is fragmented and exhausting. One app for budgeting. Another for savings. Another for pensions. Another for benefits. Another for insurance. Each tool does something useful in isolation, but real life does not arrive in neat categories.
If you are going through a separation, you might need to rethink your mortgage, update your pension beneficiary, understand what help exists for short term bills, and decide what to tackle first. Those are connected questions, but our tools split them into separate journeys, leaving the person to join the dots. We assume information equals empowerment. Too often it is just cognitive load, and when life is already full, it becomes disengagement rather than better decisions.
The same is true for financial education. The industry has invested heavily in it, and rightly so, but it is usually delivered at a distance from real life, generic, broad, and rarely anchored to the moment someone is actually living through. It tells you what people like you should think about, not what it means for you, right now, in your specific situation.
And if the choice is between a webinar on pension consolidation and the next season of Bridgerton, I know which one I am choosing, and I have worked in pension!
People do not need more content. They need clarity.
The advice gap, and the missing middle
There is another layer to this. Regulated advice is essential for big, complex decisions. But most everyday money questions are not asking for a product recommendation. They are asking for direction, options, and reassurance.
People want to know things like:
- What support can I access right now
- What should I change first
- What am I missing
- What is the “obvious” thing that everyone else seems to know
Often the most valuable intervention is not a recommendation. It is connecting the dots.
Before we built anything, we surveyed people about money confidence. Nine in ten told us they could improve. Many said they feel anxious just thinking about their finances. A meaningful number said they do not seek help from anyone at all. And the words people used stuck with me:
“I don’t need a PhD in financial products. Just tell me what’s relevant to me.”
“My budgeting app shames me for buying a coffee. Too many apps, too little help.”
“Make me feel safe asking stupid questions.”
That last line matters more than it seems. Because the real barrier is often emotional. Shame, fear of getting it wrong, fear of being judged, fear of being sold to, fear of admitting you do not understand.
What should the future feel like
I believe we are entering a new era of financial support. One where the default experience is not search, not generic content, and not a cold handoff into a process designed for specialists.
The future should feel more like this:
One front door. A conversation. Your life context. The options that matter to you.
Not to replace regulated advice, and not to turn every question into a product journey. Instead, to help people navigate the messy, human moments where money is involved, which is most moments.
To do that well, three things have to change.
First, we have to start from life moments, not financial categories. Life is the organising system. The tools should follow.
Second, we have to make information genuinely usable. That means connecting it, prioritising it, and presenting it in plain language, with next steps that feel doable.
Third, we have to treat trust and privacy as design requirements, not legal footnotes. Many people are understandably reluctant to share bank data with a new app.
Building a new front door to financial support
Cherpa exists to meet people right where they are. When life changes, money questions do not arrive neatly labelled. They arrive tangled, emotional, and urgent, and yet we still ask people to navigate a maze of tools, terminology, and generic content.
So we are taking a different approach. We start where real life starts, with the moment, not the product. One conversation that helps someone orient quickly, join the dots across the areas that matter, and move from noise to a clear set of options and next steps. The ambition is to create a trusted front door, a place people can begin, without needing to hand over more data than they are comfortable sharing.
That shift, from fear to agency, is the outcome I care about.
Why this is personal
I lost my dad when I was fourteen. I watched my mum try to navigate a financial system that gave her no useful answers during the hardest moment of her life. That memory has never left me.
It is one thing to know, intellectually, that help exists. It is another to live the reality of not being able to find it, understand it, or know what applies to you.
That is why I keep coming back to this belief.
Every life moment is a money moment. And nobody should have to face them alone.
Dia Banerji is the Founder and CEO of Cherpa.ai, based in Edinburgh.
The real constraint in advice firms is capacity
Insights from Tom Matthieson, Founder & Director, Glimzer
Capacity, not regulation
When people talk about the challenges facing financial advice firms, regulation is usually the first thing mentioned.
But in conversations with advisers, operations teams and firm leaders, a different constraint comes up far more consistently: capacity.
Not a lack of demand. Not a lack of intent to do the right thing for clients. Simply a lack of time and headroom in the day‑to‑day running of the business.
Advisers want to spend time with clients. Firms want to serve more people, improve consistency and grow sustainably. What gets in the way is the volume of administrative work required to keep everything moving. Manual updates. Duplicated data entry. Chasing information across systems. Maintaining spreadsheets alongside core platforms just to get a clear picture of what’s going on.
None of this work improves client outcomes. But it quietly consumes hours every week.
What’s striking is how normal this has become. Many firms accept admin drag as the cost of doing business, even though it directly limits how many clients they can realistically support. As teams grow, the problem often gets worse. More people means more handoffs, more checks and more effort spent reconciling information rather than using it.
Tools built for records, not delivery
A big part of this comes down to the tools firms rely on. Much of the infrastructure used in advice today was designed primarily to store records, not to support how advice is actually delivered in practice. Over time, firms adapt around these systems, building workarounds and manual processes to keep things running. The result is friction that feels unavoidable, but isn’t.
Small fixes that unlock capacity
At Glimzer, we’ve been spending time listening closely to how advice firms actually work day to day. What becomes clear very quickly is that small improvements in how information flows through a business can unlock meaningful capacity. Capturing data once instead of multiple times. Making workflows clearer. Giving teams visibility without having to build reports by hand.
This isn’t about changing the role of the adviser or introducing more complexity. It’s about removing unnecessary work so firms can use the capability they already have more effectively.
Collaboration matters
Being part of the FinTech Scotland community matters to us because these problems aren’t solved in isolation. They sit at the intersection of advice delivery, operations and technology, and they benefit from a shared perspective and honest discussion.
Our aim at Glimzer
We’re building in this space with a simple aim: to reduce friction, give advice firms back time and help them serve more clients without stretching their teams thinner. We’re keen to learn from others who are thinking about the same challenges, and to contribute to a broader conversation about how better infrastructure can support the future of advice.
When Technology Stops Being the Hard Part: The Real Constraint on Scale
By Patrick Byrne, Co-founder and CEO, Struan.ai
I’ve spent most of my career helping to grow technology-led businesses. Most often, I’ve been brought in when growth was the ambition, but the wheels were starting to wobble.
Years ago, the main risk was obvious. Would the technology work at all? Could it scale? Could the team actually build what had been promised to customers or investors? Infrastructure was expensive. Engineering talent was scarce. Shipping even something modest took time, money and a fair amount of nerve.
That environment shaped how a lot of us learned to build companies.
Today, that constraint has largely gone away. Cloud platforms are easy to access. Tooling is mature. AI has lowered the barrier to building and iterating to the point where small teams can move at a speed that would have felt unrealistic not that long ago. In many cases, the product gets built. It ships. It works.
And yet, despite all of that, growth still feels harder than it should.
I remember this very clearly in one of my former businesses. In 2017, as CEO, we kicked off what was meant to be a straightforward CRM migration. The plan was sensible enough. Four months end-to-end. Clean up the data, move systems, improve visibility, then get back to growing the business.
Seven years later, that project was still technically ‘ongoing’.
Not because the technology didn’t work. The tools were fine. The vendors did their part. The issue was everything wrapped around the technology. Data ownership was unclear. Processes changed faster than they were documented. Edge cases kept appearing. People worked around problems rather than fixing them, because there was always something more urgent to do.
Where Things Start to Strain
What I see repeatedly is execution starting to lag as momentum builds.
As organisations grow, the volume of everyday work rises quickly. Sales activity increases. Marketing needs to operate consistently, not just when there’s time. Customers need onboarding, support and follow-up. Different stakeholders need different reports to meet their own agendas. Controls tighten. None of this is optional, and most of it relies on context, judgement and continuity.
This kind of work doesn’t lend itself to an organisation that was once dynamic and nimble. Suddenly, everything is a priority and everything is urgent. So, more people are hired.
At a small size, teams cope. People know what’s going on. Gaps get filled informally. Someone stays late. Someone remembers how a thing was done last time. As volume increases, those informal fixes start to break down. Processes end up spread across tools, documents and inboxes. Important details live in people’s heads. Things still get done, but more slowly, and with less confidence.
When problems surface, they’re often written off as one-offs. In reality, they’re early signals that the operating model is under strain.
Predictable Reactions
When pressure builds, most organisations reach for the same levers.
They hire more people. They add more tools. They outsource parts of the operation.
Sometimes that helps, at least temporarily. But it usually introduces new trade-offs. More people means more overhead and more management. More tools mean more things to manage. Outsourcing can reduce visibility at the exact point where clarity matters most.
This is how many businesses drift into an awkward middle ground. The product works. Demand exists. The team is capable. But progress feels like running through treacle. Growth becomes something to manage carefully, rather than something to lean into.
What’s Usually Missing
In almost every case, the same things show up.
There isn’t a clear operating model for execution, or if there is, it’s not followed.
In organisations that scale well, execution isn’t something that happens between meetings or when people find the time. It’s treated as a system. There is ownership. There are rules, controls and clear escalation paths. Outcomes are visible and repeatable, rather than dependent on who happens to be involved on a given day.
AI can help here, but only if it’s applied in the right place. Used simply to assist individuals, it has limited impact. Applied to running defined workflows, it starts to change how work actually gets done.
Sales, marketing and operational processes benefit far more from reliability than creativity. When execution is predictable, people can spend their time on decisions, relationships and direction instead of firefighting.
Why Struan Exists
Struan came out of seeing this pattern first-hand, over decades of building high-growth businesses, operating at the edges of cashflow constraints.
While building an AI-first business that demanded a high level of control and consistency, it became clear that the real challenge wasn’t technical capability. It was execution. Specifically, who owned it, how it was run day to day, and what happened when things inevitably drifted.
Struan was built as a managed service to address that gap. It is delivered by a team with decades of experience building, scaling and running high-growth businesses, often in environments where cashflow was tight, stakes were high and there was no room for theoretical solutions. Between us, we have lived through most of the realities organisations face as they grow: performance issues that are hard to confront, people problems that drain energy, systems that fail at the worst possible moment, clients who don’t pay on time, difficult customer relationships, cashflow pressure, cultural changes as teams scale, multi-site complexity, poor management decisions, and the cost of reacting too slowly when things start to go wrong.
That experience is distilled into how Struan operates. We don’t sell tools or frameworks and leave clients to make them work. We take responsibility for execution itself, embedding AI into real workflows and running them on our clients’ behalf. The surface-level problems vary from business to business, but the underlying causes are remarkably consistent. By addressing those causes directly, Struan delivers practical impact where it matters most: reliable execution, reduced operational drag and the confidence to scale without losing control.
The Takeaway
The tools to build faster, operate leaner and scale more confidently are already here – accessible, proven and improving rapidly. What’s missing is conviction.
The real barriers to AI adoption are fear and trust. Fear of getting it wrong. Fear of disrupting something that currently works. A lingering suspicion that this only applies to technology companies with deep pockets and specialist teams.
That thinking is already out of date.
The organisations that thrive over the next decade will be defined by leadership that recognises what AI makes possible and acts on it before the competition does. Because competitors will act. In every sector, in every vertical, someone is already working out how to do more with less, move faster and operate with greater consistency. The gap between organisations that embrace this shift and those that hesitate will widen quickly and may not close again.
The question isn’t whether AI will reshape your market. It’s whether you’ll ride the wave or be swept away by it.
Financial Regulation Innovation Lab awards £50,000 each to four fintechs to accelerate consumer wealth support
The Financial Regulation Innovation Lab (FRIL) today announced the four fintechs selected to receive grants through its latest Future of Wealth Innovation Call, delivered by FinTech Scotland in partnership with SuperTech WM.
The six‑week programme concluded on 15 January with a Showcase Day, where 21 fintechs presented solutions to the challenge: helping consumers make informed financial decisions and access more tailored wealth support, while keeping pace with evolving regulation.
Throughout the programme, and against the backdrop of the joint HM Treasury-Financial Conduct Authority (FCA) Advice Guidance Boundary Review (AGBR) which seeks to help close the UK’s advice gap by clarifying how firms can provide more meaningful support under the Consumer Duty, participants took part in workshops and deep dive sessions to develop, refine and tailor their propositions to real world industry needs and potential pilots with partners. The FCA was involved throughout and provided both valuable clarity and guidance.
The Innovation Call was delivered with the support of 10 strategic partners: PwC, Barclays, Lloyds Banking Group, Sopra Steria Financial Services, NatWest Group, M&G, BNP Paribas Personal Finance. , Dudley Building Society, Wesleyan and Standard Life; alongside academic partners at the University of Strathclyde and the University of Glasgow, and Growth Builders, which supported delivery.
Following the Showcase Day, four fintechs were selected to receive £50,000 each to further develop their solutions. Over the grant period, the awardees will continue to collaborate with industry and academic partners to test, validate and accelerate their innovations towards adoption and scale.
The winners are:
Finspector is an AI-powered compliance platform that automates the review and monitoring of financial promotions across text, images, video, and social media. It helps regulated firms reduce risk, evidence compliance, and scale marketing activity with confidence across jurisdictions.
Planda is a behavioural AI platform that helps financial services firms move beyond outdated segmentation to deliver hyper-personalised customer engagement. By connecting data across enterprise workflows, Planda builds dynamic customer segments that evolve in real-time, enabling institutions to personalise at scale and deepen relationships.
Amplified Global uses AI and Machine Learning to help firms assess, simplify, and demonstrate consumer understanding at scale, ensuring they meet compliance obligations with confidence. Its technology analyses and enhances intelligibility, helping organisations turn complexity into clarity. Through a guided digital journey, it makes content more engaging, measurable, and human – redefining how people connect with information.
Afternoon’s the new data + AI first operating model for advice firms. Data collection is automated with a focus on completeness and quality. AI modules automate work, allowing a doubling of clients with the same team and with less risk from meeting to report in under 2 minutes.
Aleks Tomczyk, Chief Executive, FinTech Scotland, commented:
“The Advice Guidance Boundary Review is pivotal to widening access to meaningful financial support across the UK. Too few people are saving adequately for retirement, and historically advice has skewed towards higher earners. Government, regulators and industry are aligned on helping the wider population make better‑informed financial decisions. By funding these four winning projects and opening real‑world pilots with partners, we’re accelerating practical solutions that improve consumer decision‑making and access to support, while helping firms operate confidently within the advice–guidance boundary.”
Kate Murray, Strategic Projects Lead, Scottish Widows & Lloyds Banking Group, said:
“We want to fill the advice gap that currently exists in Britain and ultimately, enable people to have a much more prosperous financial future. The Innovation Calls present such a massive opportunity. We at Lloyds Banking Group are changing the way we do change and innovate to go faster. Bringing in outside thinking, technology, and just a completely different perspective can help us achieve that.”
Hilary Smyth Allen, Chief Executive, SuperTech WM, added:
“Partnership matters because that’s how you really get things done with impact. Through the partnership with FRIL, we’ve been able to work across a broader spectrum of the ecosystem. Consumers come in all shapes and sizes, and so does the industry that services them. Innovation for us means we are maximising outcomes for those consumers.”
Crawford Taylor, CEO & co-founder, Afternoon Finance, stated:
“The advice gap is real, and firms are under growing pressure to support more people, with better outcomes, under tighter regulation. Afternoon exists to make that possible, using data and AI to remove friction, reduce risk and radically improve how advice is delivered.
This funding allows us to continue to accelerate our mission: helping advice firms support more clients, more effectively, without compromising quality, compliance or trust. Being selected as one of just four winners from over twenty fintechs is a huge validation of the approach we’re taking.”
