Author

Koert Grasveld

Published

30 July 2026

Estimated Read time

6Mins

Koert Grasveld, Senior Director – Payments at TerraPay, on why the experience of moving money in the travel industry will continue to converge with the experience of booking travel itself

When a traveller in Barcelona makes arrangements for their next trip to Bali, the experience feels immediate. A few clicks, a confirmation, and the journey is set. But behind that seamless user interface lies a financial chain of considerable complexity: airlines, online travel agencies, hotel wholesalers, local operators, and payment providers spanning multiple currencies, time zones, and regulatory environments that rarely align neatly with one another.

The scale of what flows through this system is considerable. UN Tourism estimates that between 1.52 billion arrivals, international tourism generated USD 1.9 trillion in receipts globally in 2025. Each of those journeys generates its own trail of payment obligations: commissions settled across continents, supplier disbursements sent into markets where banking infrastructure varies enormously, refunds processed across multiple currencies and time zones.

For decades, the infrastructure handling all of this evolved slowly. Payments moved through chains of correspondent banks, accumulating fees and delays at each step. Not only does this result in uncertain settlement times, but payees have to deal with opaque FX markups and the headache of manual reconciliation. The system functioned, but its inefficiencies were absorbed rather than resolved because they were built into margins and managed through workarounds that became institutional habits.

Today, that model looks completely different.

The Infrastructure Behind the Booking

Global travel is, by its nature, a uniquely cross-border industry. For example, in the course of operating an international flight, an airline may be required to settle fees with airport authorities in different jurisdictions, while the process of an OTA reconciling commissions with hotel partners could involve layers of intermediary wholesalers. Even the process behind a tour operator disbursing payments to local guides and experience hosts could take place in multiple markets where banking infrastructure varies enormously

In all these examples, businesses are forced to navigate the same underlying complexity, just from different points in the chain. As travel volumes rebounded following the pandemic and consumers increasingly moved to booking trips, accommodation, and experiences online, payment volumes grew sharply with them, and the limitations of legacy infrastructure became harder to absorb.

The core friction is structural. Traditional correspondent banking was designed for large, infrequent interbank transfers, not for the high-volume, lower-value disbursements that characterise modern travel payments. Each intermediary in the chain adds time, cost and increases uncertainty about final settlement amounts, leaving travel finance teams managing a system that was never built for the demands now placed on it.

The gap between ambition and reality is reflected in the G20’s cross-border payments roadmap, launched in 2020 with the goal of making international payments faster, cheaper, more transparent, and more inclusive. That those goals still feel ambitious reveals the scale of the infrastructure challenge. Data from the BIS and Financial Stability Board show that only 35% of global cross-border retail payments currently settle within one hour, against a target of 75%.

Faster Payments

Yet progress is visible where it matters most: central banks across Southeast Asia have been actively interlinking domestic fast payment systems – with the BIS-led Project Nexus. For example, bringing together the central banks of India, Malaysia, the Philippines, Singapore, and Thailand to connect their domestic instant payment systems through a single standardised platform

What is changing, then, is not simply the speed of individual transactions (though that’s still important). The more significant evolution is the emergence of payment networks that connect directly to local infrastructure – domestic rails, mobile wallet platforms, real-time payment schemes – rather than routing everything through the correspondent banking chain.

When funds move through fewer intermediaries and settle directly into local systems, outcomes improve across several dimensions simultaneously: settlement becomes more predictable, cost structures become clearer, and payment data can travel with the transaction rather than being lost along the way. For travel companies with supplier networks across dozens of markets, that combination has direct consequences for the commercial relationships at the heart of the business. Suppliers who receive payments reliably and with clear remittance information tend to be more flexible partners, and that trust has real commercial value in an industry where supplier relationships frequently determine product availability and preferential terms.

Beyond the Bank Account

Perhaps the least visible dimension of this evolution, from a corporate finance perspective, is the growing importance of mobile wallets as a payout endpoint. In many of the emerging markets that represent the travel industry’s most significant growth corridors – across Southeast Asia, sub-Saharan Africa, and parts of Latin America — mobile money infrastructure has developed ahead of, or independently from, the traditional banking system.

McKinsey has characterised Southeast Asia as a “wallet-first” region, where more than six in ten people remain unbanked yet smartphone penetration is high and wallet adoption is accelerating across urban and rural markets alike.

For travel companies expanding into these corridors, the ability to disburse to wallet endpoints determines whether payment can reach local partners in a form that is immediately usable. The World Bank estimates that remittance flows to low- and middle-income countries reached USD 685 billion in 2024 — surpassing both foreign direct investment and official development assistance combined, and illustrating how consequential payment access is for communities whose incomes depend on cross-border flows. The same logic applies, at a different scale, to the independent operators and service providers who form the supply base for much of global tourism.

The Collaborative Architecture of What Comes Next for Payments

The transformation underway in cross-border travel payments is not the work of any single institution or technology. Instead, it reflects a convergence of regulatory intent, infrastructure investment, and commercial innovation that is gradually reshaping how money moves across borders. And the direction, even where the pace remains uneven, is clear. Payment networks, banks, and fintech providers building the next layer of cross-border infrastructure are doing so with interoperability and reach as design goals, creating conditions in which the geographic and institutional barriers that have historically constrained travel payments are eroded rather than simply worked around.

For travel companies, this evolving infrastructure represents an opportunity to reconsider payment operations not as a cost centre to be minimised, but as a capability that can differentiate supplier relationships, support expansion into new markets, and provide a clearer picture of financial performance across a complex global business.

In the years ahead, as real-time payment adoption expands across emerging markets, as mobile wallet networks deepen their reach, and as data standards improve the quality of information travelling alongside transactions, the experience of moving money in the travel industry will continue to converge with the experience of booking travel itself: faster, more transparent, and far more connected to the destinations it ultimately serves.

Learn more at terrapay.com

  • Digital Payments
  • Neobanking

Author

Dan Brightmore

Published

22 July 2026

Estimated Read time

4Mins

Russell Gammon, Chief Innovation Officer at Alphatax, on why tax needs to operate on a shared foundation where information can flow and be updated consistently

The modern CFO has more responsibilities than ever before, with a 2024 study finding that over 80% had taken on additional demands in the previous two years. As the report points out, “CFO is not a finance role. It is a strategic business role whose mandate is finance.”

With multiple priorities competing for time and attention, tax sits at the centre of many of the metrics CFOs are accountable for, from cash flow and risk exposure at the operational end of the scale to corporate reputation at the strategic level. Tax functions are under growing pressure to meet these expectations, with workloads increasing even as resources and budgets in many organisations remain flat or decline.

Under these conditions, tax teams are forced into a reactive, deadline-led operating model, and it’s understandable that work is completed in cycles rather than as part of an ongoing, connected process that continuously inputs into business decisions. The problem this creates, however, is that it perpetuates a clear disconnect between the undeniable importance of tax and the role it can and should play in day-to-day financial management.

A Taxing Set of Problems

It’s a situation that has evolved over a considerable period of time. For instance, most CFOs progress through finance-led career paths, with limited exposure to the depth and breadth of tax as a defined discipline.

In addition, tax is highly specialised and fragmented. It covers multiple complex, often interrelated requirements, each with its own processes and requiring access to specific subject matter experts. Even within tax teams, knowledge is distributed across individuals.

Tax also operates in a context where interpretation is often required, and clear-cut answers are not always immediately available. Bring these issues together, and it’s hardly surprising that many organisations view tax as a risk-sensitive function that must exist in its own bubble, rather than as one integrated into broader financial strategy or front and centre for the CFO.

The many and varied supporting technologies used across the tax function inevitably reflect this fragmentation. A large, expanding list of multiple-point solutions is used to address specific requirements rather than to provide a unified view of the tax function. This means tax data is almost inevitably spread across disparate systems and teams, and as any tax professional knows, the potential for inconsistencies and errors is ever-present.

Much of the work required to manage this complexity remains manual, and even where integration exists, insights are often buried within compliance outputs rather than being fed back into planning or decision-making.

Empowering the CFO

For CFOs, this situation almost inevitably draws them towards retrospective processes and analysis, when what they need is forward-looking insight. In practical terms, this reinforces a cycle of reactive intervention and increases the likelihood that opportunities to improve tax outcomes are missed.

This is increasingly at odds with the role CFOs are expected to fulfil, particularly given the emphasis on agile decision-making and the high levels of accountability that come with the job. How, for example, can a CFO be expected to make the best decisions about business expansion or investment when they do not have a clear, connected view of the organisation’s tax position?

Addressing these challenges should start with a commitment to break down the process, expertise and information silos that have historically defined the tax function; away from managing tax as a series of separate activities and towards a more integrated approach.

Tax needs to operate on a shared foundation where information can flow between different areas and be updated consistently. CFOs should be empowered with a coherent view of the organisation’s tax position and what is happening at any given point in time, without relying on the need for remedial work or retrospective reporting.

With better, integrated visibility at their disposal, the CFO can shift their focus towards strategic planning and opportunities, while the tax team can also address potential risks before they escalate.

Data Insights

A key part of this approach is making better use of the data generated through compliance processes, treating it not simply as an output but as a source of insight that can also be fed back into planning and forecasting.

Clearly, technology has an important role to play in facilitating this transformation, particularly in reducing the manual effort associated with routine tasks and improving the accessibility of data across the organisation. Don’t forget, the objective is not to remove human judgment from tax, but to ensure that specialists can focus their time on supporting the wider business.

In this context, the tax function takes on a different, more strategic role, with CFOs empowered to draw it into their decision-making processes rather than engaging with it only at the point of reporting, as so many still do today.

Learn more at alphatax.com

  • Artificial Intelligence in FinTech
  • Digital Payments

Author

Dan Brightmore

Published

12 May 2026

Estimated Read time

5Mins

Q&A – Inez Berkhof-Hollander, EMEA Vice President at the global B2B payments network TreviPay discusses the future for B2B payments

Your research with 550 senior UK and European business buyers found that AI is now widely used in B2B payments. Where is it being implemented, why, and are there any risks here?

    “What we’re seeing is that AI adoption in B2B payments is less about experimentation and more about removing friction from complex, high‑volume processes that were historically manual. We see AI currently mostly used on the AP side, not so much on the AR side yet.

    Today, AI is most commonly applied in three areas: invoice processing and data extraction; payment routing; and reconciliation. The undervalued opportunity is still on the AR side. For exception handling, dispute management and in credit and risk decisioning. These are all pain points where accuracy, speed and scale really matter. Particularly in industries with high invoice volumes or complex payment terms.

    The business driver is clear… Suppliers want faster time to cash. Buyers want fewer errors and disputes. And finance teams want better cash predictability.

    That said, the risk isn’t the technology itself – it’s how it’s governed. In B2B, when AI decisions sit close to credit, compliance and customer relationships; black‑box models without explainability, or automation without appropriate guardrails, can introduce operational and regulatory risk. The most effective applications we see are those where AI augments human decision‑making. Rather than replacing it entirely, there is clear auditability and accountability built in.

    In other words, AI is already delivering tangible value in B2B payments, but the winners will be those who treat it as an enterprise capability, not just a standalone feature.”

    Looking wider – the research also examined friction within the payments process. What were the most important areas that suppliers can leverage to their competitive advantage?

      “One of the clearest signals from the research is that payment experience has become inseparable from the overall customer experience and the commercial relationship.

      The biggest opportunities sit at the intersection of flexibility and predictability. Suppliers that make it easy for buyers to pay – through compliant and accurate invoicing, aligned payment terms, and transparency throughout the lifecycle – are easier to do business with as they reduce disputes and accelerate cash flow. Hence, ultimately they will increase customer loyalty.

      What’s interesting is that many of these levers are not new, but they are finally being treated as strategic. Invoice accuracy, payment visibility, dispute resolution, and alignment between sales and finance are no longer just operational hygiene; they are differentiators. In competitive markets, the ability to offer consistent terms across regions, customized invoicing or reporting or to accommodate how buyers want to pay without creating internal complexity, is increasingly decisive.

      From an O2C perspective, friction often appears at handovers: from order to invoice, from invoice to payment, and from payment to reconciliation. Suppliers that invest in smoothing those transitions – rather than optimising individual steps in isolation – are better positioned to compete on experience without eroding margin.”

      Your report shows 82% of buyers value invoice customisation. Why has something traditionally seen as back-office admin become such a decisive competitive factor?

        “Because invoices are no longer just accounting documents – they’re a key part of the buyer experience.

        In B2B, invoices often trigger downstream processes on the buyer side: approval workflows, ERP/PO matching, compliance checks, and even cash forecasting. When invoices don’t align with a buyer’s internal requirements – whether that’s formatting, data fields or references – friction is inevitable. That friction shows up as delayed payments, disputes, and strained relationships.

        What the 82% figure really tells us is that buyers are under pressure themselves. Finance teams are expected to do more with less, manage risk more actively, and support the wider business – all while maintaining control. Invoice customisation helps them do that.

        For suppliers, this is a powerful insight. Meeting buyers where they are, instead of forcing one‑size‑fits‑all processes, has moved from ‘nice to have’ to a strategic necessity. It’s also a clear example of how O2C capabilities directly support revenue protection and growth – not just operational efficiency.”

        What was the regional difference in your data that surprised you the most?

          “What stood out most was not just what differs by region, but why.

          Across Europe, Pay by Invoice (or ‘Net Terms’) remains dominant, but the expectations around speed, visibility and automation vary significantly. In some markets, buyers are primarily focused on control and compliance; in others, on efficiency and working capital optimisation. Regulatory maturity, banking infrastructure and ERP penetration all play a role in shaping those expectations.

          What surprised me was how consistently these regional nuances translate into different definitions of ‘good experience’. The markets that move fastest are not necessarily those with the most advanced technology, but those where finance, procurement and payments strategies are more closely aligned.

          For suppliers operating pan‑European or globally, this reinforces the importance of flexibility. A single market‑specific approach rarely scales. The winning strategies are built around a common O2C backbone, with local adaptability layered on top.”

          Pay by Invoice remains dominant in Europe, but you also highlight digital wallets and even stablecoins. How do you see the payment mix evolving over the next 3-5 years?

            “Pay by Invoice will remain the backbone of B2B payments in Europe for the foreseeable future. And that’s not a sign of stagnation, but of trust in a model that supports credit, risk management and commercial flexibility at scale.

            Where we will see change is behind the scenes. Greater digitisation, faster settlement, and better integration between invoicing, payments and reconciliation will progressively modernise how Pay by Invoice operates.

            When it comes to alternative instruments like stablecoins, the conversation is still early, but it’s becoming more serious. Their potential value lies in settlement efficiency and cross‑border use cases, rather than replacing core commercial constructs like trade credit. Whether they become relevant at scale will depend on regulation, risk frameworks and clear economic benefit for both sides of the transaction.

            What’s important is that B2B payment evolution will be pragmatic, not disruptive for its own sake. Buyers and suppliers will adopt new rails where they reduce friction or risk – not because they’re new, but because they meaningfully improve the O2C lifecycle.

            Learn more at trevipay.com

            • Artificial Intelligence in FinTech
            • Digital Payments

            Author

            Dan Brightmore

            Published

            29 April 2026

            Estimated Read time

            6Mins

            Andrew Power, Head of UK&I at Tricentis, on why the right approach to AI can deliver the foundation for more resilient, predictable systems

            Artificial intelligence is reshaping software delivery in financial services. Code that once took teams weeks to develop can now be generated and deployed in a matter of hours. This isn’t just about faster delivery; it changes the fundamentals of how software is built and how it behaves in production.

            Financial institutions have moved quickly to integrate AI across core systems, from customer operations to anti-money laundering (AML) and software development to capture efficiency and innovation gains. UK parliamentary evidence shows adoption is already widespread, with the majority of firms using AI, and more planning to follow.

            But as adoption spreads and becomes more embedded within key systems, so does exposure. Risk is no longer confined to individual defects, but shaped by how quickly those defects can spread across interconnected environments.

            AI has removed the limits on how quickly software can be created, but not on how confidently it can be trusted, and financial institutions can now generate and deploy code faster than they can safely validate it.

            This creates a new paradox: AI is both accelerating the pace of software change and increasing the speed and scale at which failures can materialise.

            Machine-Speed Failure

            AI-driven development shortens the distance between change and consequence. Software updates can move through the pipeline from creation to production with significantly less friction. However, this also reduces the time available to identify, flag and contain any issues before they have an impact.

            AI-driven software changes don’t just move fast, they scale fast. Unlike traditional failures, these are systemic risks. A single misstep in an AI-generated update can propagate unpredictably.

            For financial services, this is especially significant when key systems are deeply interconnected, spanning complex layers of infrastructure, integrations, and third-party services. Even a minor defect can propagate quickly across systems, amplifying its impact.

            What would once have been contained can now escalate, cascading across systems and causing wider disruption that affects customers, operations and, in some cases, market activity. In financial services, this is not just a technical issue but a business risk with direct implications for customer trust, regulatory compliance and financial stability. The challenge is no longer simply identifying defects but maintaining confidence in what is being deployed.

            This risk is already being felt across the sector. Institutions are accelerating delivery to meet customer expectations and competitive pressures, but often without corresponding advances in validation. Tricentis’ research shows 68% of financial services organisations anticipate outages or serious incidents due to poor software quality.

            Regulatory Pressure for AI is Increasing

            The issue is also drawing attention from regulators. Earlier this year, the UK Treasury Committee warned that current approaches to AI in financial services are inadequate and could expose customers and the wider system to “serious harm”, highlighting the need for stronger guardrails, clearer accountability and more robust oversight to deploy it safely.

            Traditional resilience frameworks were never designed for systems evolving in real time, and AI can no longer be treated as a marginal technology risk. It must become central to how organisations manage and assess resilience.

            This marks a shift from software quality being an engineering concern to a board-level issue of operational resilience. If machine-speed change is the new operational hazard, then failure to address it becomes a strategic issue rather than a technical one. With that in mind, financial leaders must acknowledge AI’s dual role as both a driver of risk and a mechanism for preventing it.

            AI as Both a Safeguard & Source of Risk

            AI also offers the most effective and scalable way to manage the risks it introduces. Advanced AI-driven validation, continuous monitoring and risk-prioritised testing can identify issues earlier than any manual process, helping reduce the likelihood they reach production.

            In effect, the same AI that accelerates software creation must now be applied to validation and governance – operating at the same speed and scale.

            The same capabilities that facilitate rapid software production can be applied to validation and governance, continuously evaluating system behaviour, detecting anomalies and prioritising testing based on potential business impact, rather than volume. This allows organisations to move beyond rigid approaches and towards more adaptive, responsive quality models that more accurately reflect the way AI behaves.

            Instead of relying on standard periodic testing cycles, systems can be validated on an ongoing basis. This enables earlier intervention before issues escalate.

            AI can also help organisations better understand the complexity of their own systems. By analysing dependencies across applications and infrastructure, it becomes possible to identify which processes are most critical and where failures would have the greatest impact.

            From Acceleration to Control

            There is a clear mismatch in how financial organisations approach AI. While many are leveraging AI to accelerate development, far fewer are evolving their validation and governance to keep pace, and it’s in this gap that risk emerges.

            This is the “confidence gap”, where organisations can create software faster than they can safely deploy it.

            To address this imbalance, firms must treat software quality as a core component of their AI strategy. Development and validation must move forward together. Governance must adapt to continuous, AI-driven change. This requires a move from static testing and coverage metrics to continuous, risk-based validation, where software is assessed in real time based on potential business impact.

            If AI is the engine driving software creation, validation must act as the braking system – built in, not bolted on at the end. At machine speed, gaps in control become points of failure. The aim is not to slow innovation, but to ensure it progresses in a way that is sustainable and safe. When validation keeps pace with development, firms can move quickly and competitively, whilst maintaining control over how risk is introduced and managed.

            This is a change we are seeing across large enterprises adopting AI-driven quality approaches, where validation, monitoring and governance are increasingly orchestrated together rather than treated as separate processes.

            Preventing the Next Outage

            The financial sector has already seen how quickly failures can escalate in complex, interconnected environments. In March, an IT error at Lloyds Banking Group exposed the private financial information of nearly half a million customers, prompting the bank to issue £139,000 in compensation.

            Such incidents aren’t isolated: over the last two years, more than 33 days of unplanned banking outages have been reported to Parliament, underlining the scale of the issue.

            As AI increases the velocity of change, it also raises the stakes for getting it wrong. But the irony is that it also provides the tools needed to prevent these failures from happening in the first place. AI is both contributing to the risk of outages and becoming the most effective way to prevent them.

            By applying AI to continuous validation, monitoring and risk detection, organisations can spot issues earlier, understand their potential impact and intervene before disruption occurs. This shifts the focus from reacting to outages to preventing them, and it’s where the paradox becomes constructive. AI doesn’t have to be a source of instability.

            With the right approach, it can become the foundation for more resilient, predictable systems. Those that fail risk trading innovation for instability. In the AI era, speed without confidence is simply another form of risk.

            Learn more at tricentis.com

            • Artificial Intelligence in FinTech
            • Cybersecurity
            • Cybersecurity in FinTech
            • Fintech & Insurtech

            Author

            Dan Brightmore

            Published

            19 March 2026

            Estimated Read time

            5Mins

            Radi El Haj, CEO of global payment technology provider RS2, on the shift toward programmable, data-driven financial infrastructure designed for a real-time global economy.

            The financial industry is entering a new phase of infrastructure modernisation. While cryptocurrencies and blockchain continue to dominate headlines, a more pragmatic evolution is reshaping banking from within: tokenised deposits embedded directly into core payment systems.

            Tokenised deposits represent a practical bridge between legacy banking infrastructure and next-generation real-time capabilities. Unlike crypto-native assets, they remain fully regulated bank liabilities. But with the added advantage of programmability, automation and real-time settlement logic built directly into the banking stack.

            The recently launched Cari Network by five US regional banks signals this shift. It demonstrates how banks are beginning to rethink bank-to-bank payments and settlement at the infrastructure layer.

            Moving away from batch-based clearing toward programmable, real-time funds allows institutions to enhance efficiency, reduce settlement risk and modernise core systems without stepping outside regulatory guardrails.

            For banks re-entering acquiring, upgrading issuing, or consolidating fragmented payment systems, tokenised deposits represent not a parallel innovation, but an embedded evolution of core processing.

            What Tokenised Deposits Really Change

            At their foundation, tokenised deposits are digitally represented, insured banking liabilities. The critical distinction is that they remain part of the regulated banking system. This preserves trust, governance and compliance – the pillars that underpin institutional finance.

            The transformational value lies in programmability at the infrastructure level. When business logic is embedded into the payment instrument itself, banks can automate reconciliation, conditional settlement, liquidity allocation and multi-party disbursements in real time. Instead of adding layers of complexity on top of legacy systems, tokenisation integrates intelligence directly into the core ledger and processing environment.

            For banks operating across issuing, acquiring and cross-border settlement, this reduces friction between systems and enables a more unified, real-time operating model.

            AI as the Operational Intelligence Layer

            Tokenisation alone is not sufficient. To operate at scale, programmable deposits require an intelligent control layer. Artificial intelligence and machine learning provide that layer.

            AI can forecast liquidity requirements across issuing and acquiring portfolios, optimise routing decisions in real-time, detect anomalous behaviour and automate compliance monitoring. As transaction volumes increase and settlement windows compress, predictive intelligence becomes critical to maintaining resilience and control.

            In multi-bank or multi-ledger environments, AI also plays a key interoperability role. It reconciles cross-network flows, identifies bottlenecks and dynamically allocates capital across settlement channels. This is where infrastructure maturity matters most.

            Banks that embed AI-driven operational intelligence directly into their payment processing architecture will be best positioned to deliver speed without sacrificing stability.

            Infrastructure is the Real Challenge

            Tokenised deposits are not a feature — they are an architectural shift. Scaling them requires cloud-native, modular processing platforms capable of integrating with existing payment rails, regulatory frameworks and cross-border networks. Without modern infrastructure, tokenised deposits risk remaining contained pilots.

            For banks modernising acquiring or issuing capabilities, this becomes a broader transformation programme: upgrading the core ledger, harmonising payment rails, embedding real-time analytics and ensuring seamless interoperability across domestic and international networks.

            This is where strategic infrastructure partners become critical. Institutions need platforms that combine:

            • Cloud-native core processing
            • Real-time settlement capabilities
            • Embedded AI-driven monitoring and liquidity management
            • Open APIs for cross-network interoperability
            • Regulatory-grade resilience and auditability

            Only then can tokenisation move from concept to scalable reality.

            Embedding Innovation Into the Banking Ecosystem

            Payments innovation succeeds when it strengthens the banking ecosystem rather than bypassing it. Tokenised deposits offer a path to modernisation that reinforces trust, compliance and regulatory clarity. When combined with AI-enabled operational intelligence, they create a responsive infrastructure capable of supporting real-time commerce, embedded finance and cross-border settlement at scale.

            Institutions that approach this as an integrated infrastructure strategy — rather than a point solution — will see the greatest impact:

            • Reduced settlement risk through programmable fund controls
            • Improved liquidity optimisation across issuing and acquiring flows
            • Real-time fraud detection powered by AI
            • More efficient cross-border routing and capital allocation

            This is not about replacing banking infrastructure. It is about rebuilding it intelligently.

            The Next Phase of Real-Time Banking

            The launch of initiatives like the Cari Network signals the beginning of a broader industry evolution. As tokenised deposits mature, collaboration between banks, FinTechs and technology providers will determine how effectively they scale.

            The strategic question for banks is not whether tokenisation delivers value — it is whether their infrastructure is prepared to support it.

            Those that invest in modern, modular processing platforms capable of integrating tokenisation and AI at the core will establish long-term competitive advantage. They will move beyond incremental upgrades toward a unified, intelligent payments architecture.

            Tokenised deposits represent more than a technological enhancement. They reflect a shift toward programmable, data-driven financial infrastructure designed for a real-time global economy.

            For banks and technology providers operating at the intersection of issuing, acquiring and settlement modernisation, this marks the beginning of a new era — one defined not simply by faster payments, but by smarter, more resilient infrastructure.

            About RS2

            RS2 is a leading global provider of payment technology solutions and processing services, offering a unified approach to managing payments across all channels for banks, integrated software vendors, payment facilitators, independent sales organizations, payment service providers, and businesses worldwide. RS2’s platform stands out as a robust cloud-native solution designed for both issuing and acquiring operations. With its advanced orchestration layer seamlessly integrating all aspects of business operations, clients gain access to comprehensive analytics, reporting tools, and reconciliation features. This empowers businesses to effortlessly expand their global footprint through a single integration, while also gaining valuable insights into payment processes and customer behavior, enhancing operational efficiency, increasing conversion rates, and driving profitability.

            Learn more at RS2.com

            • Artificial Intelligence in FinTech
            • Blockchain & Crypto
            • Digital Payments
            • Embedded Finance

            Author

            Lyall Cresswell

            Published

            10 December 2025

            Estimated Read time

            6Mins

            Lyall Cresswell, Founder & CEO, TEG on how integrated payments are unlocking growth for SMEs in the UK’s £170bn transport and logistics sector

            Consumer fintech is booming. From instant payments to embedded finance, digital innovation has transformed how individuals manage money, access credit, and transact with businesses. Yet in B2B markets, embedded finance adoption remains stubbornly low. The question is: why?

            Instant settlement alone doesn’t solve this problem. But when combined with embedded compliance it transforms how fragmented B2B markets operate. This infrastructure enables large enterprises to scale their supplier bases from dozens to thousands while giving SME carriers immediate access to working capital, all without personal financial risk.

            The answer becomes clear when you examine the UK’s £170 billion logistics sector. Employing over 8% of the workforce, it’s a low margin industry ripe for financial innovation, but in reality, highly fragmented with many SME operators. Large operators at the top of the supply chain are simply unable to verify, onboard and manage large networks of suppliers through traditional methods. This creates delays and friction.  I’ve watched this dynamic play out over 25 years building TEG. Smaller operators tell us the same story: ‘I need money now, not next month’. Cash flow isn’t just an inconvenience, it’s existential.

            The barrier isn’t payment speed alone. It’s trust at scale. Integrated payment networks, combining instant settlement with embedded compliance and verification, create the infrastructure that enables these fragmented markets to operate differently.

            Large enterprises don’t limit themselves to a small pool of known suppliers by choice. They do so because onboarding and compliance costs make broader collaboration prohibitively expensive. Each new supplier relationship requires verification of insurance, licensing, VAT status, and payment setup. This friction doesn’t just slow things down, it fundamentally constrains supply chains.

            Recent research we conducted across six leading UK third party logistics providers (3PLs) revealed the scale of this challenge: 83% audit fewer than 10% of their subcontractors annually, and only 33% use eSourcing technology. These aren’t signs of negligence. They’re symptoms of a system where verification and onboarding are simply too resource intensive to scale.

            Traditional payment solutions, from early payment programmes to invoice finance, address cash flow symptoms but miss the fundamental barrier. Without infrastructure to verify and onboard new trading partners confidently, enterprises remain trapped working with familiar suppliers even when capacity constraints or cost pressures demand alternatives. Meanwhile, SME carriers aren’t just delayed in payment, they’re excluded from opportunities entirely.

            This dynamic turns large enterprises into inadvertent gatekeepers, not by choice, but because they lack the infrastructure to safely open their networks. The result is a continuous loop: constrained supplier choice for buyers, limited market access for SMEs, and a fragmented sector unable to collaborate efficiently. The solution requires rethinking the relationship between payments and compliance entirely. Integrated payment networks, embedding compliance verification directly into payment workflows, solve both problems simultaneously.

            Building Trust Infrastructure Through Verified Payment Networks

            The breakthrough comes when payment infrastructure and compliance verification integrate seamlessly. At TEG, we’ve built this through SmartPay’s integration with Trustd, our digital identity verification platform, embedding compliance directly into payment workflows.

            The model is straightforward: carriers are verified once through real time checks of KYC, AML, VAT status, operating licences, and insurance credentials. Once verified, they can transact across the entire network. This “verify once, transact everywhere” approach removes the need for repeated onboarding across different customers or business units.

            The operational impact has been significant: 90% faster invoice processing, 80% fewer supplier queries, with over 1 million invoices paid through the platform in 2025. By year end, the TEG rollout will connect 2,500 customers with 7,500 suppliers, demonstrating adoption at scale across the logistics sector.

            But the real transformation lies in shifting from credit based to transaction based finance models. Many carriers have historically relied on credit cards and overdrafts to bridge cash flow gaps, costly stopgaps that eat into already thin margins. Traditional invoice finance excludes many SMEs because lenders must manage risk without transparency, often retaining portions of invoice value and demanding personal guarantees.

            SmartPay changes this by leveraging verified transaction data to provide instant, non recourse access to full invoice value minus fees. No retention, no personal guarantees, simply immediate working capital based on actual trading activity. This unlocks early payment facilities for carriers who previously had no alternative to expensive short term credit.

            This creates powerful network effects. As more carriers join the verified payment network, enterprises gain confidence to work with a broader supplier base. More suppliers mean better capacity, more competitive pricing, and greater resilience. For SME carriers, verified status opens doors to opportunities previously out of reach.

            Verification Infrastructure and Working Capital Access

            It’s crucial to understand that verified payment networks operate on two distinct but complementary tracks.

            Unlocking working capital addresses the SME challenge. In a sector where margins run as low as 2% and payment cycles stretch to 90 days, liquidity is existential. Without working capital, SMEs can’t hire staff, expand capacity, or invest in growth. They’re forced to choose clients based on payment terms rather than strategic fit.

            Instant settlement delivers immediate access to working capital for wages, fuel, and expansion. The UK Small Business Plan identifies late payments as one of the biggest barriers to SME growth—instant settlement directly addresses this constraint, enabling carriers to accept larger contracts and scale their operations.

            These two tracks reinforce each other. Enterprises gain access to a larger, verified supplier base. SMEs gain both market access and the working capital to serve those opportunities effectively. The result is a more efficient, collaborative market structure.

            The Fragmented Market Opportunity

            While logistics provides the proving ground, this model applies to any fragmented B2B sector where compliance complexity limits collaboration. Construction, facilities management, and professional services all face similar dynamics: thin margins, extended payment terms, high onboarding friction, and SME suppliers excluded from opportunities.

            The key requirement is neutral, collaborative infrastructure that provides a standardised verification model without competing with participants. In sectors where supplier qualification is straightforward, instant payment alone may suffice. But in regulated industries with complex credentialing requirements, verified payment networks become essential infrastructure.

            The value isn’t in handling compliance alone. It’s in creating a trusted, shared layer that all participants can use without concern that the platform itself will compete with them.

            The transformation only occurs when you solve both problems simultaneously: enterprises need neutral, trusted verification infrastructure to expand their networks confidently, and SMEs need instant settlement to operate sustainably within those networks. In fragmented markets where no single player can create industry wide standards, this shared infrastructure becomes essential. Address one without the other, and you’ve solved neither.

            Trusted Collaboration at Scale

            The narrative around embedded B2B finance needs reframing. It’s not about faster payments. It’s about removing the friction that prevents enterprises and suppliers from working together effectively—it’s about enabling trusted collaboration at scale. True transformation happens when payment infrastructure, compliance verification, and transaction transparency operate seamlessly together to unlock cash flow and expand market access for both sides.

            Across TEG’s network of over 9,000 logistics businesses, we’ve seen how verified payment networks can reshape fragmented markets. Large enterprises can finally collaborate with the breadth of suppliers their operations demand. SME carriers can access opportunities and capital previously out of reach. The entire sector operates more efficiently.

            This is the path to unlocking B2B embedded finance adoption: build infrastructure that solves the whole problem. Verify once, transact everywhere, and unlock cashflow. When enterprises can open their networks confidently and SMEs can operate sustainably within them, you create the conditions for genuine market transformation.

            The technology exists. The business case is proven. We’ve demonstrated it works at scale. The question now is which sectors will move first to build the trust infrastructure their markets desperately need.

            Learn more at teg.tech

            • Digital Payments
            • Embedded Finance

            Author

            Dan Brightmore

            Published

            18 September 2025

            Estimated Read time

            2Mins

            Embat and MicroFin strategic alliance delivers AI-powered cash management, reconciliation and real-time visibility for finance teams managing complex, multi-entity operations

            Embat, the leading European financial management and treasury platform, has formed a strategic partnership with MacroFin, part of Cooper Parry Digital and the UK’s leading NetSuite Alliance Partner. The collaboration combines MacroFin’s market-leading NetSuite implementation expertise with Embat’s next-generation treasury technology. The alliance will help finance teams tackle the growing complexity of international operations.

            MacroFin has been recognised as NetSuite Alliance Partner of the Year since 2021, reflecting its reputation and expertise for delivering the UK’s most complex ERP implementations. Following its acquisition by Cooper Parry, MacroFin has further solidified its position as one of the UK’s premier NetSuite partners.

            Facing the Challenge to Transform

            As companies scale – particularly in sectors such as SaaS, e-commerce, retail, and hospitality – their finance teams face challenges to transform that outgrow traditional tools such as Microsoft Excel. Multi-currency operations, multiple legal entities, high transaction volumes, and increased regulatory demands. This partnership ensures NetSuite clients have access to Embat’s treasury platform bidirectionally connected to NetSuite, offering:

            • Real-time cash visibility across accounts and currencies
            • AI-powered bank reconciliation that cuts manual processing time by up to 90%
            • Advanced forecasting to support strategic planning
            • Automated treasury operations to streamline day-to-day processes
            • Seamless NetSuite integration for consistent, efficient workflows
            • TellMe, Embat’s AI-powered treasury analyst, which enables finance teams to save up to 75% of their time on manual tasks. Freeing them to focus on strategic decision making

            Treasury Management

            “Treasury management has evolved from a back-office task to a strategic driver of business growth and efficiency. By working with MacroFin, we’re making advanced treasury technology accessible to NetSuite clients who need real-time visibility and automation to manage complexity with confidence.”

            Theo Wasserberg, Head of UK&I at Embat

            “When clients face complex international and multi-entity challenges, we look for solutions that go beyond NetSuite’s native functionality. Embat’s direct integration and AI-driven automation deliver the clarity and efficiency CFOs need in today’s environment.”

            Ross Latta, Co-Founder of MacroFin

            This partnership underscores Embat and MacroFin’s shared commitment to innovation in financial technology and toempowering CFOs and finance teams with tools that enhance both operational efficiency and strategic insight.

            About Embat

            Embat is a leading European financial management and treasury platform that enables finance teams in medium and large companies to centralise all operations from banking relationships to their financial management processes. It allows finance teams to save up to 75% of their time on manual tasks by using TellMe, our AI-powered treasury analyst, so they can focus on strategic decision-making. The main functions of Embat are treasury automation, automated accounting, and payments. Clients experience cost savings (by optimising their working capital management), time savings, reduced errors and an increased quality of life.

            About MacroFin with 3RP and the CP Digital Family

            MacroFin is a UK-based consultancy specialising in finance-led ERP (Enterprise Resource Planning) transformations centred around the NetSuite platform. Founded in 2018 by chartered accountants, their approach emphasises embedding finance expertise at every stage of implementation. They offer services including NetSuite implementation, optimisation, training, support, and custom development. 

            In 2024, MacroFin joined Cooper Parry to form CP Digital alongside 3RP and Cloud Orca, creating a digital transformation hub with wider expertise and tech partnerships.

            MacroFin has implemented NetSuite for leading brands like Babylon, Depop, PensionBee, and Zego, achieving average go-live in four months.

            • Artificial Intelligence in FinTech
            • Digital Payments

            Author

            Nell Walker

            Published

            17 September 2025

            Estimated Read time

            6Mins

            The proof, as they say, is in the pudding – and the evidence of TealBook’s increasingly-successful evolution lies in its client relationships

            We talked endlessly about data and AI at DPW New York 2025. A universal truth is that the successful implementation of AI requires clean data; it doesn’t have to be perfect, but businesses certainly need to have a decent handle on their data before adopting AI tools successfully. 

            To help make this a reality, North American data and software company TealBook has recently announced a legal entity-based data model. It’s designed to resolve supplier records to the correct legal entities, map parent-child relationships, and enrich profiles with verifiable attributes, enabling accurate supplier data to flow seamlessly into procurement systems and AI applications. “This is part of a 12-year journey for TealBook,” says Stephany Lapierre, the company’s Founder and CEO. “Our vision has always been to build a way to enable procurement organisations to have high quality data with a lot of integrity, in order to give them the trust they need to put data directly into their systems. 

            “Twelve years ago, we underestimated the complexity of getting large enterprises to trust a third-party data solution. As part of our journey, we started using AI early on to find information where it exists on supplier websites and databases, and start creating digital profiles in a structured way for procurement to access it, match it to their vendor master, and use it.”

            TealBook’s evolution

            But, again, at the beginning, TealBook couldn’t be sure whether the data was high enough quality. In 2017, the company was primarily known as a supplier discovery application, positioned as a pre-sourcing engine to help procurement teams identify alternative suppliers. At the time, TealBook’s data and models enabled it to determine which companies were similar to others, allowing users to search and find comparable suppliers to expand their sourcing options.

            “But that was just a way for us to deliver something that was underserved in the market,” Lapierre continues. “Then our customers started asking for certificates, which are hard to collect and match. They needed cleaner data. They felt they were under-reporting. So in 2018, we started to see whether our technology could refine the data more, and focused on certificates and supplier diversity. We collected great use cases along this journey, and the vision never wavered.

            “Just last year we released a new technology – completely different, really sophisticated – allowing us to pull from a lot more data sources, and we have provenance so our customers can actually verify where the data’s coming from. We can match it to vendor masters. And now, we also have this new model that includes 230 million verifiable global legal entities from across 145 countries’ registries. We marry this with global parent and child hierarchy, which is really hard for our customers to match themselves.”

            Partnership with Kraft Heinz

            Now, after 12 years of that vision, TealBook is deeply proud of what it’s achieved. Part of its ability to get to this point is due to early adoption from key customers. Kraft Heinz is a business which Lapierre describes as a “co-innovation partner”, and has been invaluable in helping TealBook achieve its recent goals.

            From the perspective of Stefanie Fink, Head of Global Data and Digital Procurement at Kraft Heinz, the partnership has been an immediately valuable one. “It really started with having a visionary, like-minded relationship,” she says. “That’s an important piece of it, because my vision for procurement is that we are partners in our enterprise. 

            “In order for us to do our jobs, we have to bring in the right data for use. This is where Stephany’s partnership and vision really resonated. We were really looking for diversity and we could make things easier for our partners, while making sure we had the right people in our ecosystem. We also had to lift up the hood and see what was underneath everything we’ve got. Stephany brought our vision to life. TealBook has evolved too, as we’ve seen; it’s more about orchestration and software-as-a-service. It has been a partnership of need and we cannot continue to do other things without this kind of partnership around data.”

            When initially dabbling with this relationship, Fink was clear that Kraft Heinz had no desire to be taking care of more stuff. What she wanted from TealBook was a strong focus on good quality data. After last year’s product release from TealBook, Kraft Heinz already saw its data enriched by 25%. The recently-announced new data model gives the business and TealBook’s other customers the right structure tied to a legal entity, which is a highly credible anchor. “We’re able to do entity resolution – all automated – remove all the duplicates, and then you start with a clean, digitised vendor master,” says Lapierre. “That’s what brings further enrichment.”

            The challenge of assessing data quality

            Assessing its data before involving TealBook was important for Kraft Heinz, but challenging for such a large organisation. “We had to fail first and fail fast,” says Fink. “We tried some AI around fixing things early, but that didn’t work for us. It was a real eye-opener, realising where this next evolution could take us regarding focusing on AI and agents for the right things, not the meaningless things. Before, we were asking agents to tell us if things were duplicates, when we should have been asking: what do these suppliers offer? Where is the innovation? Where is the value?”

            What surprised Fink most when looking under Kraft Heinz’s hood was the lack of attention that was being paid to what the business was doing. “It was amazing that nobody had questioned it sooner,” she says. “So I said, let’s take this as a crawl, walk, run approach, and I have a wonderful CPO who really understands where we want procurement to go as a function. She was excited about us just getting it done and getting people involved, and that’s what it takes: real pride in ownership of the data.”

            Getting engrossed in GenAI

            True partnership and an all-in approach has enabled Kraft Heinz to work successfully with AI – something some businesses are struggling with as the conversation around artificial intelligence grows louder. For Lapierre, as the CEO of a tech company, adopting AI successfully has meant trying and failing and being fully entrenched in AI as it has evolved.

            “We’ve been using AI in our technology since 2016,” she states. “We’re an early adopter. We’d be talking about scraping data, and data in the cloud, and AI models, and our customers’ pupils would widen in surprise. We’ve come a long way and the market has come a long way. 

            “The technology we deliver today wouldn’t be possible without the AI tools now at our disposal. We used to build models; we don’t do that anymore. We spend a lot of time investing in engineers to build and test models, and that’s made us so much more efficient. I use GenAI every day for so many things now, and I’m encouraging my team to be so involved in AI. That’s how you build expertise, and you need really strong expertise to use GenAI well. 

            “Getting good with AI is about taking risks and having a leadership team that pushes for new things, and suddenly the successful use of AI becomes a habit.”

            Author

            Rob Israch

            Published

            29 August 2025

            Estimated Read time

            4Mins

            Rob Israch, President at finance automation specialists Tipalti, reflects on the post-hype AI landscape for innovation in financial services

            The initial excitement around AI In finance is shifting toward a more practical focus on real business value. Many companies were swept up in the early enthusiasm. However, companies are now leaning toward integrating artificial intelligence more meaningfully into core workflows to deliver lasting value.

            While 92% of companies plan to increase their AI investments over the next three years, just 1% of leaders say their organisations are truly AI mature. True maturity means AI drives measurable outcomes and is central and streamlined into daily operations.

            So for finance teams, this shift is critical. In an economy shaped by changes in inflation, tariffs and taxes, every investment must deliver clear ROI and help the business by streamlining operations, enhancing forecasts and adopting predictive analytics.

            As companies push for sustainable growth and a thawing IPO market signals possible opportunities, scalable and integrated AI solutions will be key to business success.

            Building for Real Problems, Not Hypothetical Gaps

            Most companies agree that innovation in the finance department is key to unlocking the next level of growth. However, despite growing ambition to adopt AI and automation, 84% of finance teams still rely heavily on manual processes. Leaving little leftover time for strategic thinking.

            To truly drive value, AI must be applied not just tactically, but strategically for each business. Research shows that while 74% of companies have adopted AI, only 4% have advanced capabilities that drive clear business value. Real impact is delivered when the technology goes beyond simple workflow automation and becomes a source of real-time, predictive insight across the finance function.

            Take treasury operations, for example. Traditionally, treasury teams have faced mounting challenges in managing cash flow, forecasting liquidity, and overseeing global bank relationships. With AI-powered tools, finance teams can now gain real-time, intelligent cash visibility across thousands of banks, ERP systems, and data sources. This transformation not only empowers leaders to make faster and smarter decisions but also underscores the importance of streamlined systems within the finance function.

            From a Surplus of Tools to One Unified Platform

            What businesses don’t want is extra layers of complexity; they need a straightforward, unified platform that solves real problems.

            Large enterprises may seek ‘AI-first’ products and invest in cross-functional AI platforms. But they typically have the resources to fund extensive IT teams or consultants to customise these systems. However, for most businesses, this level of support isn’t a reality. So, businesses without reams of IT people, benefit more from a consolidated system that delivers efficiency and scalability. This allows them to stay focused on growth and innovation. 

            If AI is seamlessly embedded within these solutions, it can enhance performance without increasing complexity. Whether improving automation, workflow management or operational efficiency, AI should be an integral part of the product.

            Staging the Runway for the Next Stage of Growth

            Companies that fully integrate AI will be more ready for sustainable growth. However, integration is just the start… Once AI is embedded, organisations must focus on how it can deliver real, strategic value. This means designing solutions not only to automate processes but to provide actionable insights. Currently, only 26% have developed the skills to move beyond AI conceptually and deliver real value. In the finance function, using AI strategically can lower processing costs by 81% and speed up processing times by 73%.

            As more advanced models are integrated into workplaces systems, they can predict payment patterns, cash flow trends, and vendor behaviour. In today’s dynamic environment, companies that have sustainable, AI-powered solutions centred on usability and scalability are best positioned for the next stage of growth.

            The Continued Road to AI Maturity

            As finance teams navigate a more mature AI landscape and prepare for future growth, the focus is shifting from individual features to foundational value. With investors sharpening their focus, they seek durable business models. The companies that succeed will be those that have applied AI to maximise their investment.

            These companies haven’t just chased metrics; they’ve spent the past few years strengthening their foundations and embedding AI deeply into their architecture.

            • Artificial Intelligence in FinTech

            Author

            Akbar Hussain

            Published

            23 July 2025

            Estimated Read time

            5Mins

            Akbar Hussain, Co-founder and Chief Legal & Compliance Officer at TerraPay, on cross-border payment innovation

            Every transaction tells a story. Most pass by unnoticed: familial remittances, a gift, a balance topped up. But behind the scenes, every transfer or cross-border payment sets off a chain reaction of checks, rules, and decisions. Signals are assessed. Contexts are weighed. Trust is verified.

            Cross-border payments don’t operate in a vacuum. They move through regulatory frameworks and risk assessments, often in milliseconds. And as more and more transfers pass through this complex system, there is a growing need for infrastructure that knows not just how to move money effectively but how to govern its movement wisely.

            Small Transactions, Big Stakes

            There’s a myth in the payments world that small transactions carry small risk. That compliance obligations only apply at scale. Or that low-value payments fly under the regulatory radar. But in a globally connected system, nothing operates in isolation.

            Small transactions power financial inclusion: school fees, emergency loans, micro-business payments. They are frequent, personal, and essential. And when repeated millions of times across loosely monitored corridors, they can create risk patterns with system-wide consequences.

            When oversight is thin, even a modest flow of funds can be exploited for money laundering, fraud, or sanctions evasion. The notion that scale is only measured by individual ticket size ignores how quickly volume and velocity can multiply exposure. The risk isn’t always in the size of a transaction, it’s in how little is known about it.

            Risk also doesn’t scale linearly. A seemingly harmless payments corridor can, over time, become a blind spot for illicit flows if the right compliance checks aren’t embedded. That’s why building safeguards into the infrastructure, not just the interface, of any payments system is critical.

            Ultimately, there’s no such thing as a low-value transaction when the cost of failure is measured in trust.

            Innovation vs Regulation

            In much of the FinTech world, there’s still a belief that building effective cross-border payment systems means choosing between two paths: innovate fast or regulate carefully, as if the two can’t coexist. But this is a false choice. There is no sustainable growth in cross-border finance without regulatory credibility. Any system built to avoid or defer oversight will ultimately collapse, hollowed out by its own shortcuts.

            In reality, we shouldn’t think of compliance as a barrier to scale but rather as a condition of scale. It’s what unlocks markets, builds durable infrastructure, and earns the trust of partners, governments, and users. Trust isn’t a switch that flips at go-to-market; it’s something built transaction by transaction, jurisdiction by jurisdiction.

            That means licensing, yes. But it also means culture. It means embedding compliance into the architecture of your systems, the rhythms of your operations, and the priorities of your leadership. When regulatory design is built in from the start—rather than patched on later—it helps power growth.

            Systemic Risk Has No Borders

            One of the defining features of modern financial infrastructure is its interdependence. There are no isolated risks anymore. A lapse in one system—a poorly monitored corridor, a flawed due diligence model, an unvetted partner—doesn’t stay local. It echoes outward. Financial crime doesn’t respect borders. Neither does reputational damage.

            This is particularly true in high-risk markets, where traditional institutions are limited or absent, and the appetite for speed often overshadows prudence.

            These are also the places where financial inclusion efforts matter most—and where failure risks cutting people off entirely. Getting it wrong in these contexts risks shutting out the unbanked and underbanked from the systems designed to serve them, reinforcing the very barriers this industry claims to dismantle.

            Financial institutions that choose to operate in these environments must do so with heightened accountability. The organizations that lead with integrity understand this and act accordingly: investing in real-time monitoring, adapting to regulatory shifts, and holding their partners to the same standard.

            Building for the Future with Cross-Border Payments

            There’s an understandable appeal to silver-bullet solutions: AI for fraud detection, blockchain for traceability, real-time everything. These technologies are powerful, and when applied with care, they can significantly enhance the robustness of compliance systems. But they’re not infallible. When adopted without scrutiny, they risk masking deeper structural weaknesses beneath a surface-level sense of control.

            The more sustainable approach is rarely the flashiest. It’s incremental, data-driven, and adaptive. It prioritizes experimentation over assumption and refinement over scale for scale’s sake. Using anonymised data to test systems, deploying AI to extend—rather than replace—human oversight, and continuously evolving alongside the regulatory environments these systems must serve: this is where long-term resilience is built.

            Trust, in Practice

            To design for trust is to design for complexity. It means making peace with the regulatory landscape and recognizing that compliance isn’t a one-off exercise but a constant, evolving discipline that must move in step with innovation—not trail behind it.

            It may not be the flashiest part of the story, or the one that makes the headlines, but any serious player in the cross-border economy must learn to balance the urgency of go-to-market with a deep, operational understanding of compliance and security. Regulation isn’t something to be welded on later. It’s something to be baked in from the start.

            • Digital Payments

            Author

            Nell Walker

            Published

            Estimated Read time

            6Mins

            The proof, as they say, is in the pudding – and the evidence of TealBook’s increasingly-successful evolution lies in its client relationships.

            We talked endlessly about data and AI at DPW New York 2025. A universal truth is that the successful implementation of AI requires clean data. It doesn’t have to be perfect, but businesses certainly need to have a decent handle on their data before adopting AI tools successfully. 

            To help make this a reality, North American data and software company TealBook has recently announced a legal entity-based data model. It’s designed to resolve supplier records to the correct legal entities, map parent-child relationships, and enrich profiles with verifiable attributes, enabling accurate supplier data to flow seamlessly into procurement systems and AI applications. “This is part of a 12-year journey for TealBook,” says Stephany Lapierre, the company’s Founder and CEO. “Our vision has always been to build a way to enable procurement organisations to have high quality data with a lot of integrity. That way, you give them the trust they need to put data directly into their systems. 

            “Twelve years ago, we underestimated the complexity of getting large enterprises to trust a third-party data solution. As part of our journey, we started using AI early on to find information where it exists on supplier websites and databases. We also started creating digital profiles in a structured way for procurement to access it, match it to their vendor master, and use it.”

            TealBook’s data evolution

            But, again, at the beginning, TealBook couldn’t be sure whether the data was high enough quality. In 2017, the company was primarily known as a supplier discovery application. It was positioned as a pre-sourcing engine to help procurement teams identify alternative suppliers. At the time, TealBook’s data and models enabled it to determine which companies were similar to others. This meant users could search and find comparable suppliers to expand their sourcing options.

            “But that was just a way for us to deliver something that was underserved in the market,” Lapierre continues. “Then our customers started asking for certificates, which are hard to collect and match. They needed cleaner data. They felt they were under-reporting. So in 2018, we started to see whether our technology could refine the data more. We focused on certificates and supplier diversity. We collected great use cases along this journey, and the vision never wavered.

            “Just last year we released a new technology – completely different, really sophisticated – allowing us to pull from a lot more data sources. We have provenance so our customers can actually verify where the data’s coming from. We can match it to vendor masters. And now, we also have this new model that includes 230 million verifiable global legal entities from across 145 countries’ registries. We marry this with global parent and child hierarchy, which is really hard for our customers to match themselves.”

            Partnership with Kraft Heinz

            Now, after 12 years of that vision, TealBook is deeply proud of what it’s achieved. Part of its ability to get to this point is due to early adoption from key customers. Kraft Heinz is a business which Lapierre describes as a “co-innovation partner”, and has been invaluable in helping TealBook achieve its recent goals.

            From the perspective of Stefanie Fink, Head of Global Data and Digital Procurement at Kraft Heinz, the partnership has been an immediately valuable one. “It really started with having a visionary, like-minded relationship,” she says. “That’s an important piece of it, because my vision for procurement is that we are partners in our enterprise. 

            “In order for us to do our jobs, we have to bring in the right data for use. This is where Stephany’s partnership and vision really resonated. We were really looking for diversity and we could make things easier for our partners, while making sure we had the right people in our ecosystem. We also had to lift up the hood and see what was underneath everything we’ve got. Stephany brought our vision to life. TealBook has evolved too, as we’ve seen; it’s more about orchestration and software-as-a-service. It has been a partnership of need and we cannot continue to do other things without this kind of partnership around data.”

            When initially dabbling with this relationship, Fink was clear that Kraft Heinz had no desire to be taking care of more stuff. What she wanted from TealBook was a strong focus on good quality data. After last year’s product release from TealBook, Kraft Heinz already saw its data enriched by 25%. The recently-announced new data model gives the business and TealBook’s other customers the right structure tied to a legal entity, which is a highly credible anchor. “We’re able to do entity resolution – all automated – remove all the duplicates, and then you start with a clean, digitised vendor master,” says Lapierre. “That’s what brings further enrichment.”

            The challenge of assessing data quality

            Assessing its data before involving TealBook was important for Kraft Heinz, but challenging for such a large organisation. “We had to fail first and fail fast,” says Fink. “We tried some AI around fixing things early, but that didn’t work for us. It was a real eye-opener, realising where this next evolution could take us. Particularly regarding focusing on AI and agents for the right things, not the meaningless things. Before, we were asking agents to tell us if things were duplicates, when we should have been asking: what do these suppliers offer? Where is the innovation? Where is the value?”

            What surprised Fink most when looking under Kraft Heinz’s hood was the lack of attention that was being paid to what the business was doing. “It was amazing that nobody had questioned it sooner,” she says. “So I said, let’s take this as a crawl, walk, run approach. I have a wonderful CPO who really understands where we want procurement to go as a function. She was excited about us just getting it done and getting people involved, and that’s what it takes: real pride in ownership of the data.”

            Getting engrossed in GenAI

            True partnership and an all-in approach has enabled Kraft Heinz to work successfully with AI. This is something some businesses are struggling with as the conversation around artificial intelligence grows louder. For Lapierre, as the CEO of a tech company, adopting AI successfully has meant trying and failing and being fully entrenched in AI as it has evolved.

            “We’ve been using AI in our technology since 2016,” she states. “We’re an early adopter. We’d be talking about scraping data, and data in the cloud, and AI models, and our customers’ pupils would widen in surprise. We’ve come a long way and the market has come a long way. 

            “The technology we deliver today wouldn’t be possible without the AI tools now at our disposal. We used to build models; we don’t do that anymore. We spend a lot of time investing in engineers to build and test models. That’s made us so much more efficient. I use GenAI every day for so many things now. I’m encouraging my team to be so involved in AI. That’s how you build expertise. You need really strong expertise to use GenAI well. 

            “Getting good with AI is about taking risks and having a leadership team that pushes for new things. Suddenly, the successful use of AI becomes a habit.”

            Author

            Dan Brightmore

            Published

            10 June 2025

            Estimated Read time

            4Mins

            Russell Gammon, Chief Solutions Officer at Tax Systems, on the benefits of AI in automating routine processes to make time for higher level strategic tasks

            In the past two and a half years since the launch of ChatGPT – and the likes of Copilot – the world has been gripped with generative AI fever. However, after the initial rush of enthusiasm, many businesses today are taking a more cautious approach. Trying to identify tangible benefits and use cases that can prove its worth before making costly investments.

            One industry where the use cases are becoming more evident day by day is Financial Services. Repetitive and time-consuming tasks, traditionally completed manually with all the risk of human error that entails, can now be automated. Capabilities such as machine learning, generative AI, and advanced data analytics algorithms are being used to help ensure organisations remain compliant through delivering accurate, timely calculations, tax filings and reports. And creating clearer visibility.

            AI Revolution

            By automating routine processes, such as data analysis and reconciliation, finance executives can spend more time on higher level strategic tasks. AI can also provide insights beyond the capacity of humans thanks to its ability to crunch vast volumes of data, It can uncover trends that might otherwise go unnoticed. This enables real-time reporting and analysis with AI insight forming the basis of smarter decision-making.

            For finance, this is just the beginning of the AI revolution. Look deeper into any finance sector and a huge variety of more specialised applications are revealed. Take the tax industry, for example, where a sizeable cohort of professionals still spend a considerable amount of time checking long lists of numbers on invoices or using spreadsheets to track spending. Not only is this work frustratingly boring, it is also prone to human error. AI has the potential, at a single stroke, to handle such tasks.

            Navigating Choppy Regulatory Waters

            Staying in the tax-related field, AI can also play a pivotal role in handling incoming regulations, such as Pillar Two. Multinational corporations are grappling with the complexities of this legislation. AI is emerging as a game changing tool in compliance management, transforming tax reporting, risk mitigation, and regulatory adaptation.

            AI is being used to automate compliance and reporting processes. It can streamline data aggregation, ensure accurate reporting, and adapt to evolving regulations. AI-powered compliance tools optimise the evaluation, monitoring, and reporting of Pillar Two obligations. This can reduce complexity and improve precision. They can also integrate and standardise financial data across jurisdictions, improving consistency in tax computations.

            These solutions seamlessly connect disparate systems, extracting and harmonising data from multiple sources regardless of format. By normalising and processing this information in line with BEPS regulations, AI can swiftly identify potential compliance risks. Advanced algorithms can flag irregular transactions between related entities and pinpoint inconsistencies in transfer pricing. This helps to detect possible profit-shifting activities before they become regulatory concerns. AI thus has the potential to change compliance management from a costly obligation to a strategic advantage.

            Be Wary of AI’s Limitations

            So, there is clearly a lot of potential for AI to transform financial services in terms of daily operations and compliance. However, it is important to remain wary of its limitations. Chief amongst them, is AI’s propensity to ‘hallucinate’ or make information up if it can’t find the right answer. That casts a shadow over the accuracy of all of its output. And underlines the importance of professional gatekeepers who can verify AI content and ensure it is correct.

            AI also currently lacks the ability to interpret subtle context, which humans can more easily respond to. This can feed into spurious responses and misinterpreted data. However, with the right training, monitoring and oversight, AI tools can overcome such weaknesses.

            Supporting, Not Replacing, the Human Touch

            Understandably, given AI’s potential, many are concerned about the impact on jobs. If AI can digest thousands of lines of data and spit out a report in seconds, what do we need interns for? But it’s important to see AI as an augmentation of existing human talent, not a replacement for it.

            As noted above, the possibility of hallucination means that qualified professionals will always have a role to play in quality checking output. So, what we are seeing is the development of a symbiotic relationship wherein professionals are freed from the drudgery of repetitive grunt work. They can focus on more strategic objectives, while AI handles it under their careful eye.

            For the tech-savvy Gen-Z entering the workplace today, this is a hugely positive change. The finance and tax industries have become a less attractive career option for this generation, due to the traditional processes and lack of technological innovation. What graduate wants to spend their days entering data after years of studying their chosen subject? With AI ready as a helping hand, they can enter the workplace and use their skills and knowledge to assess the technology’s output, rather than spending hours manually doing it themselves. The finance industry is now in a position to embrace this opportunity that AI has presented. And encourage new talent into the industry.   

            Given the financial services sector is plagued with skills shortages, and ever-growing workloads, employers can now offer more attractive career opportunities. Furthermore, striking the right balance to drive improved efficiency, productivity and performance and reap the rewards of an AI-enabled future. 

            • Artificial Intelligence in FinTech

            Author

            Mark Andreev

            Published

            6 June 2025

            Estimated Read time

            4Mins

            Mark Andreev, COO at Exactly, presents a practical guide to tackling e-commerce fraud with payment tokenisation

            Tokenisation can solve a big problem… e-commerce fraud is a growing threat that continues to impact online businesses worldwide. According to recent figures from Statista (2025), global e-commerce losses due to online payment fraud are projected to exceed $100 billion by 2029. As fraudsters increasingly exploit IT vulnerabilities, it is imperative for online and brick-and-mortar businesses to fortify their cybersecurity posture.

            Amidst the current security challenges, payment tokenisation emerges as a technology to future-proof business operations and is projected to reach USD 28.97 billion worth by 2033.

            This guide explores the concept of payment tokenisation, emphasising its value and role in ensuring credit card payment processing standards for merchants.

            What is Payment Tokenisation?

            Tokenisation is the process of substituting sensitive data with non-sensitive values – tokens. It works as a key layer of protection for stored data by replacing card numbers with illegible, surrogate values.

            During a transaction, payment details are securely transmitted to a trusted payment provider via hosted payment page or through direct API integration.

            In the hosted payment page flow, the customer is redirected to a secure payment page operated by the payment provider. Here they can enter their payment information. The provider handles data collection, encryption, and transaction authorisation, keeping sensitive information off the merchant’s servers.

            In the API integration flow, the merchant’s website collects payment details using secure client-side tools. In this case, the merchant is responsible for ensuring full PCI DSS compliance, as sensitive data passes through their systems.

            Following a transaction, sensitive card data is substituted by a special character sequence. The translation of characters into randomised values refers to the tokenisation process.

            For merchants who are not PCI DSS compliant, storing sensitive information on their side is not allowed. In these cases, the third-party payment provider retains the sensitive data and the tokens for future use, while merchants don’t retain any sensitive information.

            This method is one of the key cybersecurity best practices to ensure payment providers remain compliant with PCI DSS and is also crucial for merchants using API integration to store sensitive data.

            Different Types of Tokens

            There are different types of tokens available to merchants, offering different levels of complexity and security. Simple tokens refer to randomised reference numbers that are unidentifiable and unrelated to customer data. They provide a high level of security when implemented correctly by a reputable payment provider.

            On the other hand, token vaults represent a more complex system of payment security and data handling. Essentially, token vaults are encrypted repositories of original payment data associated with tokens from each customer transaction. Depending on the type of payment gateway integration, either the merchant or the payment provider may retrieve the payment information as needed. Token vaults can also be deployed in cloud environments, mitigating the need for extensive infrastructure.

            The Value of Tokens

            In an era where cybersecurity is paramount, failing to secure customer data can come at significant costs. Recently, the IT systems of the UK’s most prominent retailers suffered significant downtime following a series of cyberattacks. They were prevented from serving their customers as a result. As the consequences of these attacks continue to linger, affected UK retailers are working overtime to get back on track. In these situations, the use of tokenisation payment security has partly helped prevent what could have been a catastrophic breach. Reducing the risk of a lateral exploitation of customer data. In fact, using payment tokens, retailers avoid the need to encrypt and retain sensitive payment details. This lowers the risk of attacks, breaches, and noncompliance with ever-changing payment processing and data security policies.

            Tokenisation also enables seamless customer experiences, addressing a crucial customer demand – convenience. In fact, with tokenisation enabling one-click checkouts, customers avoid re-entering card details and access a seamless shopping experience, meeting an important need for comfort and familiarity for consumers.

            Finally, from a regulatory perspective, compliance with PCI DSS is mandatory for payment providers and merchants specifically using API integration within payment gateways to store sensitive information. In this regulatory context, tokenisation becomes a straightforward strategy to meet fundamental data handling legal requirements. In an era of rising cyber threats and increasing customer expectations, tokenisation offers merchants a scalable, effective, and future-ready approach to safeguarding sensitive data, building trust, and preserving business integrity.

            • Cybersecurity in FinTech
            • Digital Payments

            Author

            Dan Brightmore

            Published

            26 February 2025

            Estimated Read time

            2Mins

            Tech Show London is coming to Excel March 12-13. Register for your free ticket now!

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            Dive into a world where cutting-edge ideas shape your tomorrow. Tech Show London is the epicentre of technology innovation in London and beyond, hosting the brightest minds in technology, AI, cyber security, DevOps, and cloud all under one roof.

            The Mainstage Theatre is not just a stage; it’s a launchpad for innovative ideas. Witness a stellar lineup featuring world-renowned experts from across the tech stack, influential C-level executives, key government figures, and the vanguards of AI and cybersecurity. All ready to share ideas set to rock the industry.

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            • Cybersecurity
            • Data & AI
            • Digital Strategy
            • Event Newsroom
            • Infrastructure & Cloud

            Author

            Sean Galea-Pace

            Published

            14 November 2024

            Estimated Read time

            6Mins

            Tonkean is built differently. Tonkean is a first-of-its-kind intake and orchestration platform. Powered by AI, Tonkean helps enterprise internal service…

            Tonkean is built differently.

            Tonkean is a first-of-its-kind intake and orchestration platform. Powered by AI, Tonkean helps enterprise internal service teams like procurement and legal create process experiences that transform how businesses operate. The transformation hinges on four key functionalities, intake, AI-powered orchestration, visibility, and business-led configuration (no-code), which internal teams leverage to use existing tools better together, automate complex processes across teams and tools, and empower employees to do better, higher-value work. 

            Jennifer O’Gara is the Senior Director of Marketing, Director People and Talent at Tonkean. O’Gara’s route into procurement came when Tonkean became active within the space. “While we initially focused on solving complex process challenges across entire enterprises, we quickly realised how much procurement could benefit from this approach,” she explains. “Procurement processes are inherently complex and collaborative and cross-functional, making them a perfect fit for Tonkean’s orchestration capabilities. We were right. Since we entered the market, we’ve been blown away by how enthusiastically process orchestration has been received. That’s keeping us excited about procurement.”

            This year, DPW Amsterdam 2024’s theme was 10X, with a focus on the importance of companies aiming for a moonshot mindset instead of an incremental approach. As far as O’Gara is concerned, achieving 10X improvements in performance is within reach for procurement, but it requires a shift in how the function thinks about growth. “It’s not just about doing more of the same faster—it’s about fundamentally rethinking the processes that drive your business,” reveals O’Gara. “Your processes are like your company’s infrastructure. When you optimise at the process level, you don’t just create incremental gains; you can fundamentally transform the way you operate at scale. You can remove bottlenecks permanently, facilitate easier collaboration org-wide, and drive true, reliable automation across all your teams and systems. The result is exponential performance improvements that can be sustained over time. Aiming for 10X isn’t just a lofty goal—it’s achievable. The key is focusing your improvement efforts at the process level.”

            However, the journey to 10X isn’t straightforward. Some organisations believe they can just layer new technology on top of old processes. According to O’Gara, this won’t unlock 10X growth and will still leave your company lagging behind. “Getting to 10X starts, instead, with building better processes—and moving away from the idea that any one technology will do the trick,” she says. “For example, AI. AI is powerful, but it’s just a tool, and it’s only valuable if used strategically. To truly unlock 10X improvements in performance, you need to integrate technologies like AI into your core processes in a way that’s structured, strategic, and scalable. You will only ever be as innovative or adaptive or as effective as your processes are dynamic, dexterous and dependable. How do you build better processes? That’s where process orchestration comes in.”

            Process orchestration refers to the strategy — enabled by process orchestration platforms — of coordinating automated business processes across teams and existing, integrated systems. These processes can facilitate all procurement-related activities. Importantly, they can also accommodate employees’ many different working preferences and styles.

            Instead of simply adding to an organisation’s existing tech stack, process orchestration allows companies to use their existing mix of people, data, and tech better together. One promise of process orchestration is to finally put internal shared service teams like procurement in charge of the tools they deploy.

            This goes a long way towards solving one of the enterprise’s most vexing operational challenges: the inefficiency of over-complexity born of too much new technology. It also allows procurement teams to truly make their technology work for them and the employees they serve. As opposed to making people work for technology. Process orchestration breaks down the silos that typically separate working environments. No longer do stakeholders have to log in to an ERP or P2P platform to submit or approve intake requests, just for example. The technology will meet them wherever they are.

            “It helps you create and scale processes that can seamlessly connect with all of your existing systems, databases, and teams, while accommodating the individual needs of your employees and meeting them in the tools they already use,” adds O’Gara. “Orchestration allows you to automate processes across existing systems—like ERP, P2P, and messaging apps—so data flows automatically between them. It allows you to surface technologies like AI when and where they’re most impactful for stakeholders.”

            Speaking of AI, it remains one of the biggest buzzwords in procurement. Indeed, anything that offers Chief Procurement Officers cost savings and efficiency will prick their ears, but the question remains: can the industry fully trust it? O’Gara believes it is ‘overhyped.’ “When it first emerged, it wasn’t just seen as a new tool—it was almost treated like magic,” she explains. “The hype still hasn’t died down, and that’s been a problem. It’s created unrealistic expectations and skewed perceptions of what innovation with this sort of technology actually entails; I can’t tell you how many procurement leaders have admitted to us that they’re getting pressure from the C-suite to invest in AI-powered tools just because they have ‘AI’ in the name.”

            While clear with her scepticism regarding generative AI’s current place in the market, O’Gara recognises its potential. “Generative AI’s potential is huge—especially if it’s deployed strategically at the process level,” she reveals. “It could truly transform procurement, shifting teams from transactional roles to strategic partners who are involved early in the buying process and appreciated for their unique expertise—and for the unique business value procurement alone can deliver. But AI on its own isn’t going to save procurement. The reality is, many organisations jumped into the AI hype without a real strategy, and that’s why they haven’t seen its full value yet. The key is integrating AI thoughtfully into core processes—that’s when we’ll start seeing its real potential.”

            With an eye on the future, O’Gara expects the next year to continue to revolve around AI adoption, but in ways that deliver real value. “I think we’ll see procurement truly stepping into a more strategic role, with businesses recognising procurement as a key partner, not just a back-office function,” she says. “This shift will be driven in part by new technology, especially process orchestration and AI, helping procurement bridge gaps in communication and collaboration across teams. Another big trend will be the rise of personalised, consumer-like experiences in procurement—making buying and approval processes smoother, more intuitive, and better tailored to the needs of individual users. It’s an exciting time, and we’re just scratching the surface of what’s possible.”

            Author

            Nell Walker

            Published

            13 August 2024

            Estimated Read time

            4Mins

            For a company like TealBook, data is king. The organisation helps businesses to navigate the complex supplier landscape by offering…

            For a company like TealBook, data is king. The organisation helps businesses to navigate the complex supplier landscape by offering a foundation of high-quality data. This is something that’s often sorely missing in procurement.

            “We have a data problem,” Stephany Lapierre, CEO and Founder of TealBook, told us when we caught up with her at the DPW NYC Summit in June. “It’s always been my view that we don’t have a software or people problem – it’s data. If we could achieve better data – no matter the data stack, no matter the maturity, no matter the vertical – it would be truly transformative.”

            Creating a data foundation

            Lapierre has watched procurement’s attempt to tackle advanced technology without good data. Simply buying software is the easy part. Some have even tried to build their own architecture around that software. However, that’s often unsuccessful and highly manual. This is what led to the creation of TealBook.

            “We’re in this pursuit of how we can deliver to the market,” Lapierre states. “We’ve been building a trusted data foundation for eight years.” More recently, the second version of TealBook’s service is significantly more powerful than the first. This allows it to ingest data at speed and set up new data sources within a couple of hours. “The more data sources, the more suppliers we’re covering, the more attributes per supplier. And, the more signals to improve the TrustScore and the confidence behind the quality of our data.”

            Never ignore the fundamentals 

            The fact that quality data is all too often overlooked in procurement in favour of advanced technology was something of a theme at the DPW NYC Summit. The opinion of Lapierre is that there’s little point in implementing advanced tech without first having usable data in place. Many others at the event felt the same.

            “It’s like buying a house because you love the house, but paying no attention to its foundation, plumbing, or electrics,” she explains. “Procurement has been buying up technology solutions, wanting to see the workflow, the UI, what it can do. However, people aren’t asking where that data comes from. How is it being evaluated? What about the compliance side of having suppliers populating a portal?

            “Procurement has more and more requirements to get more and more data, so filling the gaps becomes more difficult. There are also increasing demands for transparency, and for regulators to have better quality information. When you’re reporting something, you have to really trust that information. That’s how you give confidence to your board or leadership team.”

            A shift in focus

            The upside of this disconnect is that Lapierre fully expects the pursuit of better data to be a key trend in procurement over the next few years. “I’ve found that no-one talks about the data layer in procurement,” she states. “They brush it under the rug or underestimate how critical it is to use data to feed large language models for better insights. As data becomes more accessible, the need for a trusted data foundation becomes more important. You need good data posture.”

            With this very topic being discussed openly at prestigious events like the ones DPW hosts, procurement professionals and leaders are actively working towards solving this blockage. “The problems have to be solved in order to leverage the exponential value of Gen AI, automate workflows, and bring intelligence in across all these functions,” Lapierre continues. 

            “Consider: what would it mean to your business if you could actually solve that data problem, drive better outcomes, and truly digitise the procurement function?”