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!

Unlock unparalleled value with a single ticket that gets you free access to five industry-leading technology shows. Welcome to Cloud & AI Infrastructure, DevOps Live, Cloud & Cyber Security Expo, Big Data & AI World, and Data Centre World.

Tech Show London has it all. Don’t miss this immersive journey into the latest trends and innovations.

Discover tomorrow’s tech today

Unleash Potential, Embrace the Future. Hear from the greatest tech minds, all in one place.

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.

GLOBAL INSPIRATION, LOCAL IMPACT

Seize the opportunity to be inspired by global visionaries. Furthermore, with speakers from the UK, USA, and beyond, prepare to be inspired by transformative concepts and actionable strategies from technology insiders, ensuring your business stays ahead in an ever-evolving technology landscape.

Where the future of technology takes the stage

Secure your competitive edge at Tech Show London, the UK’s award-winning convergence of the industry’s brightest tech minds.

On 12-13 March 2025, gain vital foresight into the disruptive technologies reshaping your market, and position your organisation at the forefront of technology’s next frontier.

If you’re defining your business’s tech roadmap, register for your free ticket to join us at Excel London.

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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?”