This article is written by Nomentia
In an engaging opening address, Nomentia’s own Lauri Bergström and Tapani Oksala painted a vivid tableau of the ever-evolving landscape of treasury management and Nomentia’s customer-centric and dynamic approach to its developments. Three key trends emerged as focal points: financial strategy, risk management, and technological advances. Emphasizing the critical role of teamwork and leadership across organizations, the duo set up a robust foundation for the summit’s discussions.
The event kicked off in full with a deep dive into the complexities of liquidity management, as exemplified by Caverion’s finance operations amidst a strategic merger. In this session, Viljami Vainikka, Head of Group Treasury at Caverion, provided a comprehensive overview of Caverion’s liquidity landscape during a merger with Assemblin, highlighting their approach to optimizing cash visibility and addressing challenges in cash flow forecasting. He outlined Caverion’s liquidity management setup, which includes cash management across multiple currencies, numerous bank accounts, and entities, with a focus on optimizing liquidity and improving forecast accuracy.
In conversation with Tapani Oksala, Vainikka shed light on the challenges of optimizing cash visibility and underscored the importance of robust and accurate cash forecasting, leveraging technology and strategic partnerships, and the potential for integrating AI to enhance liquidity planning processes to increase efficiency and accuracy.
In the second presentation of the Nomentia Treasury Summit, Dirk Schreiber, Head of Treasury at BioNTech, shared with the audience insights into BioNTech’s journey amidst the centennially turbulent times leading toward the COVID-19 pandemic and its aftermath.
Founded in 2008, BioNTech experienced initial challenges until the onset of the COVID-19 pandemic in early 2020. Recognizing the potential of their mRNA technology for developing a COVID-19 vaccine, BioNTech swiftly pivoted its focus, leading to the rapid development and distribution of a vaccine in collaboration with Pfizer.
Schreiber highlighted the unprecedented growth and financial influx that followed the successful vaccine development, presenting BioNTech’s treasury management journey in response to these dynamic circumstances. With a surge in funds, BioNTech urgently required a robust treasury management system to manage its expanding financial operations. Despite facing initial challenges with an untested treasury function, Schreiber and his team swiftly implemented a treasury management system, leveraging Nomentia’s expertise to build BioNTech’s treasury operations.
The presentation explored the intricacies of BioNTech’s treasury transformation, emphasizing the rapid expansion of requirements for the treasury and the establishment of essential treasury guidelines and processes for future development. Schreiber emphasized the critical role of the right technology in this transformation, particularly the implementation of Nomentia’s treasury management system to provide real-time visibility into cash positions, automate trading activities, and streamline reporting processes.
The panel discussion featuring representatives from Nordea, SEB, and OP shed light on the evolving landscape of financial crime prevention and the role of banks as strategic partners.
Against the backdrop of increasing cybersecurity threats, the panel emphasized the importance of collaboration between banks and corporate treasuries in combating financial crime.
As technology evolves, it brings with it new and exciting opportunities to those companies that are able to manage their risk appetite accordingly. Unfortunately, the development of technology also provides opportunities to the criminal element. The threat landscape in the digitalized business environment is significantly more complex than before. Thanks to technology we’re living in an environment wrought with crime and fraudulent behavior. The ecosystem of crime in the digitalized financial environment is complex and ever more susceptible to human error and poor processes.
The panel’s discussions centered on the adoption of innovative technologies and best practices for enhancing security and mitigating risk in treasury operations. This session focused on the crucial role of proactive measures and strategic partnerships in safeguarding financial assets in an increasingly digital world.
According to the panel, treasury management and financial professionals would do well not to treat the fight against financial crime as a digital problem only, as the evolving threat landscape requires an adaptive and nimble approach not only to security technology but the organizational culture as well.
Fortunately, this is not a fight that businesses have to face on their own. The banking and finance industry has taken proactive steps to improve its resilience and business continuity.
On the legislative side, the EU’s DORA (Digital Operations Resilience Act) is a great example of how demands for businesses to secure their operations in the financial threat landscape is not only a digital undertaking but requires a wider scope that encompasses their operations fully.
In the 4th presentation of the day, Stefan Müller from Eaton discussed the digitalization of bank account management (BAM) during the Nomentia’s Treasury Summit. Previously, BAM was cumbersome and fragmented, involving manual tasks, email exchanges, and Excel spreadsheets. Eaton recognized the inefficiencies and partnered with Nomentia in 2019 to modernize their BAM processes.
The transformation involved leveraging advanced digital technologies to automate tasks like account openings, closures, signatory changes, and transaction monitoring. This shift required comprehensive cleanup of account and signer data, process documentation, and target workflows. By mid-2021, the project was underway, and by March 2022, the new BAM system was live.
Today, Eaton manages BAM operations on one centralized platform, gaining efficiency, control, and compliance. Automated reconciliations and streamlined workflows have reduced manual efforts significantly. The treasury function has seen tangible benefits, including the closure of 200 accounts and the removal of over 200 signers and 2,300 permissions.
The digitalization of treasury operations has offered opportunities for greater control and efficiency. Real-time data access enables informed decision-making and proactive risk management. Automation of routine tasks frees up time for strategic analysis. However, increased reliance on digital platforms necessitates robust security protocols to mitigate cybersecurity risks.
Karin Wahlgren’s presentation on SKF Group’s global payment transformation journey provided a glimpse into the realities of treasury management.
By embracing automation and strategic decision-making, SKF Group transitioned from manual to automated payment processes, achieving significant efficiencies and cost savings. 
The success story of SKF Group underscores the transformative impact of technology on global payments, offering valuable lessons for organizations seeking to enhance their treasury operations. Wahlgren’s insights into strategic decision-making and project management underscored the importance of leadership and innovation in driving treasury transformation initiatives.
The fifth presentation of the day offered an intriguing exploration into the cash flow forecasting processes on a state treasury level. The talk provided a unique perspective on national financial stability. By employing sophisticated tools and techniques, State Treasuries ensure sufficient cash reserves to meet the country’s financial obligations in all situations. The presentation highlighted the critical role of treasury management in safeguarding national financial interests, underscoring the importance of rigorous planning and preparedness.
In the final talk of the day, Hubert Rappold, Chief Sales Officer at Nomentia, delivered a thoughtful keynote address emphasizing the evolving role of treasury teams in the digital era.
Despite the traditional focus on liquidity management and risk mitigation, technological advancements are reshaping treasury operations. While there’s a tendency to overemphasize the immediate impact of emerging technologies, it’s crucial to maintain a realistic perspective, considering both short-term expectations and long-term implications. Drawing parallels with the Gartner Hype Cycle, Rappold highlighted the trajectory of technologies like AI, emphasizing the need for a balanced understanding of their capabilities.
Advanced technologies such as AI, machine learning, and natural language processing offer significant potential for enhancing decision-making processes and streamlining workflows in treasury operations. However, it’s essential to prioritize efficiency and accuracy, leveraging real-time data for strategic initiatives like liquidity management and risk mitigation. As treasury functions evolve, professionals assume a more strategic role, contributing to overall business growth by driving innovation and leveraging advanced technologies.
Treasury Mastermind is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below to get more information.
This article is written by our partner, FIS
Receivables finance (RF) has long been a cornerstone of corporate finance, enabling businesses to convert outstanding invoices into immediate liquidity. By selling their receivables to a funder, companies may access cost-effective funding and reduce risk, while investors may gain exposure to short-duration, diversified assets at a competitive return.
However, as recent events surrounding First Brands Group illustrate, this structure remains vulnerable to risks beyond credit, such as fraud. These vulnerabilities highlight the need for greater scrutiny and the adoption of new technologies.
Fraud in RF transactions typically manifests through misrepresentation of receivables quality, double pledging of assets and fabrication of invoices. These risks arise because RF relies heavily on the integrity of the originator’s reporting and servicing processes. If invoices are falsified or pledged to multiple financiers, the asset base becomes compromised, exposing investors and lenders to significant losses.
The First Brands case underscores these vulnerabilities. The U.S. auto parts supplier, which filed for Chapter 11 reorganization in September 2025, allegedly engaged in widespread financial misconduct, including doctoring invoices and double-counting receivables to secure billions of dollars in financing.
Several market features of RF contribute to fraud risk:
These factors can make RF particularly vulnerable when governance fails or liquidity pressures incentivize aggressive accounting.
The First Brands saga has accelerated calls for digital transformation in RF oversight. Advanced technology and reporting platforms can reduce fraud risk through:
The collapse of First Brands is a cautionary tale for all stakeholders in the RF ecosystem. While RF remains a powerful liquidity tool, its resilience depends on effective governance and technological safeguards. Platforms that deliver real-time transparency, automated controls and immutable records are no longer optional: They are essential to maintaining trust and confidence in this asset.
In essence, resilient frameworks are often built on digital efficiency and the irreplaceable insight of experienced practitioners.
As institutional investors continue to seek exposure to trade finance assets and corporates aim to unlock working capital, the combination of advanced technology and human expertise within complex RF structures will help to shape the market’s future.
While digitalization may stand as the frontline defense against fraud, it’s equally vital to maintain effective human oversight by having seasoned professionals conduct independent reviews and engage in regular dialog with originators and funders.
This interplay between technological innovation and expert judgment helps ensure that not only are anomalies flagged automatically, but also the nuances of complex transactions are properly understood and addressed. In essence, resilient frameworks are often built on digital efficiency and the irreplaceable insight of experienced practitioners.
Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click the button below.
This article is written by Nomentia
Why are manual treasury processes expensive?
Manual treasury processes become expensive because they require recurring effort to collect balances, prepare payment files, update forecasts, check approvals, and reconcile data. Even when each task seems manageable, the combined impact can reduce efficiency, slow down decision-making, and increase operational risk.
Treasury teams are used to making imperfect systems work.
A spreadsheet here. A bank portal there. A local ERP export from one entity, a payment file from another, and a cash forecast that still depends on email updates from the business. None of these workarounds may look dramatic on their own. In many organisations, they are even seen as normal.
The problem is that “normal” can become expensive.
Manual treasury operations rarely create one large, visible cost line. Instead, they create a pattern of hidden costs: time spent collecting data, delays in decision-making, duplicated effort, payment exceptions, outdated forecasts, missed visibility, and control gaps that only become urgent when something goes wrong.
That is why treasury automation ROI should not only be discussed as a technology question. It is also an operating model question. How much time does treasury spend managing the process instead of managing cash, liquidity, payments, and risk?
The cost of manual work is often underestimated because it is distributed across people, entities, systems, and routines.
A treasury analyst may spend hours preparing a daily cash position. A regional finance team may manually upload payment files. Another person may validate bank data, check approvals, update forecasts, or investigate why one bank statement does not match the expected format.
Each task may be manageable. Combined, they create a significant operational burden.
This is also why many teams struggle to build a cash forecasting business case. The value of better forecasting is not limited to “faster reporting”. It is the value of better decisions: knowing earlier where liquidity is needed, reducing dependency on outdated data, improving confidence in funding decisions, and giving leadership a clearer view of what may happen next.
External research points in the same direction. PwC’s 2025 Global Treasury Survey notes that treasury teams are under pressure to improve cash visibility, cost efficiency, and risk management, while leading organisations increasingly adopt real-time liquidity tools, AI-enhanced forecasting, and centralised payment models. HSBC also highlights that cash flow forecasting has remained a key treasury priority, reflecting the need for precise and timely forecasts in a volatile environment.
In other words, manual treasury processes are not only inefficient. They can slow down the organisation’s ability to respond.
Cash visibility is one of the clearest examples of hidden treasury cost.
When balances are collected manually across banks, accounts, currencies, and entities, treasury may technically have the data, but not necessarily in time to act on it. The team may know yesterday’s position, but not today’s. It may have a consolidated view, but only after several people have updated files, checked bank portals, and reconciled different formats.
That delay matters.
Without timely visibility, companies may keep too much cash idle in one place while borrowing elsewhere. They may struggle to identify trapped cash. They may make liquidity decisions based on incomplete information. They may also spend valuable time explaining numbers instead of improving them.
Nomentia positions its Smart Treasury Suite around visibility, control, and predictability across payments, cash, liquidity, and risk, integrating with ERPs, banks, and other systems. For companies operating across multiple banks and entities, that integration layer is not just technical infrastructure. It is the foundation for turning fragmented data into usable treasury insight.
Payments are another area where manual processes can appear cheaper than they really are.
At first glance, uploading files through bank portals or managing payments across local workflows may seem acceptable. The team knows the process. The banks are connected somehow. Payments are executed. Work continues.
But payment operations carry a high cost when they depend on scattered portals, inconsistent approvals, manual file handling, and local exceptions.
The hidden costs include time spent preparing and checking payment files, resolving format issues, validating approvals, tracking payment statuses, and answering questions from subsidiaries, AP teams, banks, and auditors. More importantly, weak payment control can increase exposure to duplicate payments, missed cut-offs, fraud attempts, and compliance issues.
This is where payment automation benefits become easier to explain. Automation is not only about faster payment execution. It is about standardising the process, improving traceability, reducing manual intervention, and making payment control easier to prove.
Forecasting is often where manual treasury processes become most visible to leadership.
The CFO does not necessarily see how many files were collected, how many emails were sent, or how many adjustments treasury made before the forecast was ready. But the CFO does see when the forecast is late, when confidence is low, or when the numbers change without a clear explanation.
A manual cash forecast can still be useful. Many experienced treasury teams are excellent at working around incomplete data. But as the business grows, expands into new markets, adds banks, or inherits systems through acquisitions, the limits become harder to ignore.
Forecasting depends on data quality, timing, ownership, and repeatability. If treasury spends too much time gathering inputs, it has less time to analyse drivers, challenge assumptions, and model scenarios. A forecast that takes days to prepare may already be outdated when it reaches decision-makers.
This is why the business case for treasury automation should include both time savings and decision quality. Faster data collection is valuable. But the larger value often comes from giving treasury more time to interpret what the numbers mean.
Manual controls are often built around expertise. The team knows which approvals are needed, which files need checking, which bank deadlines matter, and which exceptions require escalation.
That works until complexity increases.
As more entities, banks, users, and payment types are added, control becomes harder to manage consistently. Processes may differ across countries. Approval rules sit outside the system. Audit trails may require manual reconstruction. Exceptions depend on individual knowledge rather than embedded workflows.
In a stable environment, this may go unnoticed. During growth, restructuring, audit, staff changes, or periods of financial pressure, it becomes a risk.
The Nomentia Treasury Trends Report 2026 describes treasury teams facing pressure to deliver real-time insights, stronger controls, and more strategic input, often while dealing with fragmented systems and limited IT support. The report is based on 384 treasury and finance leaders across the Nordics, DACH, Benelux, and the UK.
That is the reality many treasury teams recognise: expectations are rising faster than operational capacity.
A strong treasury automation ROI discussion should not begin with software features. It should begin with operational impact.
From there, TMS cost savings become easier to frame. The value may come from fewer manual hours, lower operational risk, more efficient payment execution, improved cash visibility, reduced dependency on spreadsheets, or stronger audit readiness.
The most useful business case is not a generic promise that automation saves money. It is a structured estimate of where the organisation currently loses time and where better treasury processes could create measurable improvement.
Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click the button below.
This article is written by Cobase
For an industry built on numbers, banking has always struggled with something more basic: speaking the same language.
Ask any treasury team trying to connect to banks globally and you’ll hear a familiar frustration. The expectation is simple – money is digital, banks are global, so connectivity should be straightforward. In reality, it rarely is. What looks like a plumbing issue is something deeper: a system that was never designed to be unified in the first place.
Modern banking didn’t emerge as a coordinated network. It grew in fragments. National systems were built to serve domestic economies, shaped by local regulation, infrastructure, and political priorities. Payment schemes evolved independently. Messaging formats were defined in isolation. Even basic concepts like how to confirm a payment or report a balance took different forms depending on where you looked.
The result is not just variation, but incompatibility.
SWIFT is often held up as the closest thing to a global standard. And in one sense, it is. It created a common messaging layer that banks across the world could use. But it never standardised what happens after the message is sent. Two banks can receive the same SWIFT instruction and process it in entirely different ways – different cut-off times, different validations, different interpretations.
This is where the idea of “bank connectivity” begins to unravel. The challenge is not just reaching a bank, but dealing with how each bank behaves once you do.
Over the years, the industry has made repeated attempts to smooth this out. None have fully succeeded. Not because the technology wasn’t good enough, but because the incentives never aligned. Banks compete. Regulators don’t coordinate globally. And legacy systems – often decades old – continue to run critical infrastructure that no one is willing to replace lightly.
The expectation of a unified system persists. But it’s built on a false premise.
Banking isn’t fragmented because something went wrong. It’s fragmented because that’s how it was built.
Few ideas in banking have generated as much optimism in recent years as APIs.
They arrived with the promise of simplicity. Clean, modern interfaces. Real-time data. Standardised access. Compared to the heavy, file-based integrations of the past, APIs looked like a reset moment, a chance to finally make bank connectivity behave like the rest of the digital world.
And in some ways, they delivered.
Large banks began exposing endpoints for payments and reporting. Developers could interact with bank systems without navigating layers of legacy protocols. In controlled environments, things worked exactly as advertised.
But step outside those environments, and the picture changes.
APIs in banking are not a single standard. They are dozens, sometimes hundreds, of individual implementations. Each bank defines its own structure, its own authentication methods, its own limits. Even when two banks claim to follow the same framework, the differences show up quickly – in edge cases, in error handling, in performance under load.
The regulatory push behind open banking added momentum, but also confusion. PSD2 created a baseline, but it was never designed for corporate treasury. It focused on retail use cases, with limited scope for bulk payments, complex approval flows, or multi-entity structures. For large organisations, it solved a small part of a much bigger problem.
Meanwhile, neo-banks and aggregators entered the picture, offering simplified access and faster onboarding. They improved the experience at the edges, particularly for account opening and basic transactions. But they didn’t remove the need to engage with traditional banks. In many cases, they simply added another layer to manage.
The result is a familiar pattern in financial infrastructure. New technology doesn’t replace the old – it accumulates around it.
APIs didn’t eliminate fragmentation. They made it more dynamic.
From the outside, bank connectivity looks deceptively simple. Payments go out, balances come in, and everything appears to move through a single system.
What’s less visible is the machinery underneath.
For companies operating across multiple countries, connectivity is not one connection, it’s dozens. Each bank brings its own requirements. File formats differ. Security models vary. Some require certificates, others tokens. One bank processes payments in batches, another in real time. Cut-off times shift by region, sometimes by product.
Even within the same bank, behaviour can change depending on the channel used. An API might support one set of payment types, while host-to-host supports another. Documentation doesn’t always reflect reality. Test environments behave differently from production. Exceptions are handled inconsistently.
None of this is unusual. It’s the normal state of the system.
This is why, despite all the talk of innovation, older methods remain firmly in place. Host-to-host connectivity – direct, file-based integration – continues to handle a large share of corporate payments. It’s not elegant, but it’s predictable. It does what it’s supposed to do, at scale, without surprises.
In certain markets, local standards dominate. EBICS, for example, is deeply embedded in parts of Europe. It works not because it’s globally relevant, but because it reflects the specific needs of those markets. In those contexts, it often outperforms more “modern” approaches simply by being consistent.
And then there’s SWIFT, still acting as the global fallback. When no direct connection is available, SWIFT is usually there. Not perfect, not always efficient, but broadly accepted.
Put all of this together, and a pattern emerges. There is no single best way to connect to banks. There is only a set of trade-offs.
The real work is not choosing one method, but managing all of them at once, and making them behave as if they were one.
That work increasingly sits in a layer most corporates never set out to build, but inevitably do: an orchestration layer that absorbs differences between banks, channels, and formats, and presents something coherent on top.
This is where platforms like Cobase operate.
Rather than trying to standardise banks themselves, Cobase standardises the interaction with them. It connects across SWIFT, EBICS, APIs, and host-to-host channels, translating between formats, normalising data, and embedding bank-specific behaviour into a central system. A payment instruction created once can be converted automatically into whatever each bank requires. Data coming back – balances, statuses, confirmations – is aligned into a consistent structure.
The complexity doesn’t disappear. It is relocated.
Instead of sitting in day-to-day treasury operations spread across teams, spreadsheets, and manual fixes, it is contained within a controlled layer designed to handle it.
Because in the end, the hardest part of bank connectivity is not building connections.
It’s making them invisible.
Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click the button below.
