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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.
Article written by Patrick Kunz, Treasury Masterminds Founder
Treasury has always been expected to be calm, controlled, and reliable.
And fair enough, nobody wants a treasury team that treats liquidity like a casino night.
But the world of treasury is moving faster than ever, shaped by rapidly shifting markets, fluctuating interest rates, evolving banking technology, changing regulations, increasingly sophisticated fraud, the rise of AI, and business models that are becoming more international, digital and complex.
So the obvious question is: can treasury keep up?
But perhaps that question is too simple, because “keeping up” is not just about buying faster technology or chasing every new tool, dashboard, API, AI agent or treasury buzzword that appears on LinkedIn before lunch. It is about building a treasury function that can respond quickly, think clearly, and challenge itself before the business is forced to do so.
When people talk about treasury transformation, the conversation often turns immediately to technology, including TMS platforms, APIs, bank connectivity, payment hubs, cash forecasting tools, AI and automation, all of which are useful, relevant and capable of strengthening the treasury function. Yet technology alone does not make treasury faster.
A slow decision-making process supported by a shiny new system remains slow, a bad cash forecast displayed on a dashboard remains a bad forecast, and automating a broken process merely makes it more efficiently disappointing.
The real question, therefore, is not simply whether treasury has modern technology, but whether it also has the processes, mindset, and mandate needed to use that technology effectively.
Many treasury teams are still built around monthly reporting cycles, annual policies, and decision-making structures that assume the world politely waits for the next committee meeting.
It does not.
Treasury increasingly needs shorter feedback loops. If FX exposure changes quickly, treasury needs visibility quickly. If liquidity tightens, treasury needs to know before it becomes a board-level surprise. If banks change pricing, limits, or service quality, treasury cannot wait six months to notice.
Treasury should never become reckless, but it must evolve from static to dynamic control. Control remains central to its role, yet maintaining control can no longer come at the expense of progress.
The past few years have shown that treasury teams can no longer rely on a single base case forecast and call it a day. Interest rates can rise, currencies can swing, supply chains can break, credit markets can tighten, banks can change their risk appetite, and regulations can shift, while the business will somehow still ask treasury why nobody saw it coming.
This is where scenario planning allows treasury to add genuine strategic value, not by pretending to predict the future perfectly, which is a fantasy best left to economists and people selling expensive PowerPoint presentations, but by helping the business understand what could happen, how significant the impact could be, and which actions are available in response.
These are important business questions that treasury should be among the best-positioned functions to answer.
One of the greatest barriers to change in treasury is not technology, but habit, and “we have always done it this way” remains one of the most expensive sentences in corporate finance. Many treasury practices were created for a very different environment, with different banking structures, interest rates, levels of automation, and expectations from the business.
Established practices are not inherently bad, as treasury still depends on discipline, structure, and strong controls, but discipline should never turn into stubbornness. Treasury leaders must therefore challenge the fundamentals regularly by asking whether every bank account is still necessary, whether the cash pooling structure remains optimal, whether the foreign exchange policy is still fit for purpose, and whether forecasting genuinely supports decisions or simply continues because someone created a template in 2014. They should also consider whether the TMS is being used as a strategic platform or as a very expensive filing cabinet, and whether manual controls continue to provide meaningful protection or merely slow everything down.
The strongest treasury teams do not change everything constantly. They understand which foundations should remain stable and which practices must evolve as the business and its environment change.
Treasury is no longer focused solely on cash positioning, payments, and bank relationships. These responsibilities remain essential, and strong foundations matter more than ever, but the function is increasingly involved in broader strategic discussions covering working capital, risk management, systems architecture, data quality, financial resilience, automation, fraud prevention, liquidity strategy and even commercial decision-making.
This expanded role requires treasury professionals to become more curious, more connected to the business, more comfortable with technology, and more willing to ask difficult questions. The treasurer of the future will not simply know where the cash is, but will understand what it reveals about the business, what could put it at risk, and how the organisation should respond.
Yes, but only if treasury avoids confusing motion with progress, because keeping up is not about chasing every trend that appears. It is about building a function that moves quickly when speed matters, remains disciplined when control is essential, and stays curious when established assumptions deserve to be challenged.
This requires using technology intelligently rather than blindly, shortening decision cycles without weakening governance and planning for multiple scenarios instead of treating the base case as destiny. Above all, treasury must recognise that it cannot become strategically relevant while remaining permanently reactive. The world is changing rapidly, and while treasury has no reason to panic, it can no longer afford to stand still.
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 our partner, Atlar
Corporate debt is among the most useful tools a company has, but only when it is managed well. Whether you are tracking external bank loans and credit facilities or managing intercompany lending across subsidiaries, good debt management protects liquidity, controls costs, and supports growth. This guide covers what finance and treasury teams need to know about both external and internal (intercompany) debt: the core processes, the common pitfalls, and the practices that keep you in control.
Corporate debt management is the process of tracking, organizing, and optimizing a company’s borrowing across all debt instruments and entities. It encompasses everything from recording loan terms and monitoring repayment schedules to calculating interest obligations and assessing the impact of debt on cash flow.
For finance and treasury teams, debt management sits at the intersection of several core functions: cash management, cash flow forecasting, financial reporting, and risk management. The debt a company carries directly affects its liquidity position, its ability to invest, and its obligations to lenders and other stakeholders.
In practice, corporate debt falls into two broad categories:
Both types require careful tracking, documentation, and management, but they come with distinct challenges. External debt is governed by covenants and banking relationships. Internal debt is governed by transfer pricing rules, tax regulations, and the need for arm’s-length terms. This guide covers both in depth.
Debt is a fact of life for most companies of any size. How a company manages it shapes its liquidity, its borrowing costs, and its standing with lenders and investors.
Cash flow visibility
Debt repayments, both principal and interest, are among the largest and most predictable cash outflows a company faces. Without a clear picture of upcoming obligations across all loans and entities, treasury teams risk cash shortfalls, missed payments, or inefficient allocation of surplus cash. Integrating debt data into your cash flow forecasting process is essential for accurate liquidity planning.
Cost optimization
The cost of debt is not fixed. Interest rates fluctuate, hedging instruments expire, and refinancing opportunities arise. Finance teams that actively monitor their debt portfolio can identify opportunities to reduce borrowing costs, whether by refinancing at a lower rate, restructuring repayment schedules, or paying down high-cost debt with surplus cash.
Covenant compliance
Most external debt comes with financial covenants—conditions the borrower must meet, such as maintaining certain leverage ratios or minimum cash balances. Breaching a covenant can trigger penalties, accelerated repayment, or even default. Proactive monitoring ensures you stay within limits and can act before issues arise.
Regulatory and tax compliance
Intercompany loans, in particular, are subject to scrutiny from tax authorities. Transfer pricing regulations require that intercompany lending be conducted at arm’s length, that is, the interest rate, repayment schedule, and other terms must reflect what unrelated parties would agree to in comparable circumstances. Failure to comply can result in significant tax adjustments and penalties.
Financial reporting and audit readiness
Accurate debt records are a prerequisite for reliable financial reporting under standards like IFRS and GAAP. Auditors review loan documentation, interest calculations, and repayment histories. Maintaining a centralized record of all debt instruments streamlines the audit process and reduces the risk of misstatements.
Before diving into management practices, it helps to understand the main types of debt that finance and treasury teams typically deal with.
| Debt instrument | Description | Typical use |
|---|---|---|
| Term loan | Bank loan with a fixed repayment schedule. Bilateral (one lender) or syndicated (several). | Acquisitions, capex, general corporate purposes |
| Revolving credit facility (RCF) | Credit line drawn, repaid, and redrawn up to a set limit. A committed liquidity backstop. | Working capital, liquidity buffer |
| Corporate bond | Debt security issued to investors, typically with a fixed coupon and maturity. | Large-scale, long-term financing |
| Senior secured note | Bond backed by specific assets, with priority over unsecured creditors in default. | Leveraged finance, PE-backed companies |
| Unsecured bond | Bond backed by the issuer’s general creditworthiness, not specific collateral. | Investment-grade issuers |
| Convertible bond | Bond convertible into equity under set conditions, blending debt and equity. | Growth-stage companies, lower-cost debt |
| Bridge loan | Short-term financing until permanent funding is arranged. | M&A transactions, IPO preparation |
| Intercompany loan | Loan between two entities in the same corporate group. | Internal capital allocation, subsidiary working capital |
A key distinction in any debt portfolio is between fixed-rate and variable-rate (also called floating-rate) instruments.
Fixed-rate debt carries a set interest rate for the life of the loan, providing cost certainty. The borrower knows exactly what each interest payment will be, which simplifies cash flow forecasting.
Variable-rate debt is tied to a benchmark rate plus a margin (or spread). The benchmark rate is a reference interest rate published by a central authority or derived from market transactions. The most widely used benchmarks in corporate lending are:
The interest cost on a variable-rate loan fluctuates as the benchmark rate changes. For example, a loan priced at three-month EURIBOR + 2.00% will see its interest rate reset every three months based on the prevailing EURIBOR rate. If the three-month EURIBOR is 2.50%, the all-in rate is 4.50%. If EURIBOR moves to 3.00% at the next reset, the all-in rate becomes 5.00%.
Many companies hold a mix of fixed and variable-rate debt. The balance between the two, and the use of hedging instruments to manage rate exposure, is a fundamental decision in debt management.
Companies with variable-rate debt often use hedging instruments to protect against adverse interest rate movements. The most common types are:
Tracking hedging instruments alongside the underlying debt they relate to is important for accurate interest expense forecasting, hedge accounting under IFRS 9 or ASC 815 (US GAAP), and understanding the company’s true interest rate exposure.
External debt management means keeping full visibility and control over your borrowing from banks, bondholders, and other third-party lenders. For companies with several banking relationships, entities, and currencies, that is both operationally demanding and strategically important.
Effective debt management begins before the first loan is drawn. Treasury teams work with the CFO, FP&A, and sometimes external advisors to determine how much capital the company needs, for what purpose, and over what time horizon. These inputs drive the choice of instrument.
Key considerations at this stage include:
Once the instrument type is selected and lenders are identified, the terms are negotiated and formalized in legal documentation. For a bank loan, this typically includes a loan agreement (or credit agreement) and any related security documents. For a bond, it involves an indenture (the legal contract between the issuer and a trustee who represents bondholders) and an offering memorandum (the disclosure document provided to prospective investors).
Key terms to document and track include:
This documentation is the single source of truth for each debt instrument and should be stored centrally where the treasury and finance team can access it.
With documentation in place, the next step is to register every loan in a centralized debt register—whether that’s a dedicated module within a treasury management system (TMS), an ERP system, or (for smaller portfolios) a well-structured spreadsheet. Without this, companies that borrow from multiple banks often end up managing each relationship through separate portals, each with its own statement formats and reporting cycles, making it difficult to assemble a consolidated view of total debt and upcoming obligations. A centralized register with multi-bank connectivity eliminates this fragmentation.
For each instrument, the register should capture:
This register becomes the foundation for everything that follows: interest calculations, cash flow forecasting, covenant monitoring, and stakeholder reporting.
Once loans are registered, the treasury team must track ongoing interest obligations accurately. For fixed-rate debt, this is straightforward—the interest amount is known in advance. For variable-rate debt, interest calculations require more attention.
The key inputs to a variable-rate interest calculation are:
For example, a €10 million loan at three-month EURIBOR + 2.00% with an Actual/360 day-count convention and a 91-day interest period would be calculated as: (Principal × (EURIBOR + Margin) × Days in Period) / 360.
Automating these calculations, rather than relying on manual spreadsheet updates, reduces errors and ensures that your cash flow forecasts always reflect the latest rate environment.
Debt servicing costs, comprising both interest payments and principal repayments, are often among the largest line items in a company’s cash outflow forecast. Integrating debt data directly into your cash flow forecasting model ensures that upcoming obligations are accurately reflected in your projected cash position.
In a 13-week cash flow forecast, debt-related outflows should typically appear as distinct line items, separating interest payments from principal repayments, within the outflow section of the forecast. This granularity helps treasury teams identify periods where debt payments coincide with other large outflows (such as payroll, tax, or supplier payments) and take action to ensure sufficient liquidity.
For companies with variable-rate debt, forecasting also involves projecting future interest costs under different rate scenarios—typically a base case, an upside scenario (rates fall), and a downside scenario (rates rise). The impact compounds quickly at scale: a 100 basis point increase in EURIBOR on a €50 million floating-rate loan increases annual interest expense by €500,000. This kind of scenario analysis helps treasury teams understand rate sensitivity, inform hedging decisions, and prepare accordingly, particularly when hedging instruments are not tracked alongside the underlying debt, making net exposure hard to assess.
Financial covenants are conditions embedded in loan agreements that require the borrower to maintain certain financial metrics. Breaching a covenant, even a technical breach with no immediate financial consequence, can erode lender confidence, trigger reporting obligations, and in severe cases lead to acceleration of repayment or default.
The most common financial covenants include:
Monitoring covenants requires up-to-date financial data, not just from your debt register but from your accounting and treasury systems as well. Companies typically test covenants quarterly, aligned with their financial reporting cycle. A centralized platform that combines debt data with real-time cash positions and financial metrics makes this significantly more manageable.
Best practice is to track covenant headroom—the difference between the actual metric and the covenant threshold—on an ongoing basis, rather than only at test dates. This early warning system gives treasury teams time to take corrective action (such as reducing discretionary spending, accelerating receivables, or negotiating a temporary waiver with lenders) before a breach occurs. It’s worth noting that non-financial covenants, such as negative pledge clauses that can be triggered by corporate restructurings or asset disposals, are a common and often overlooked cause of default events, and deserve the same proactive tracking.
As loans approach maturity, treasury teams must plan for repayment or refinancing well in advance. A maturity profile, showing when each debt instrument comes due, is an essential planning tool.
Key considerations when managing maturities include:
Maintaining banking relationships: Regular communication with lenders builds trust and can lead to more favorable terms.
CFOs, board members, auditors, lenders, and investors all need visibility into the company’s debt position. Effective debt reporting should clearly present:
A well-structured debt report, updated regularly and easily accessible, builds confidence among stakeholders and supports better decision-making. Modern treasury platforms generate these reports from centralized data, reducing the manual effort of assembling information from multiple sources.
An intercompany loan is a loan between two entities in the same corporate group, for example a parent funding a subsidiary or one subsidiary lending surplus cash to another. The lender books a receivable and recognizes interest income; the borrower books a payable and interest expense. The concept is straightforward, but managing intercompany debt brings regulatory, tax, and operational complexity that external debt does not.
Intercompany loans serve several important purposes:
Before establishing an intercompany loan, consider whether it’s the most appropriate mechanism. Alternatives include equity contributions (injecting capital rather than lending it), dividend distributions (moving cash between entities by distributing profits), management fees (charging one entity for services provided by another), or having the subsidiary borrow externally. Each option carries different implications for tax, balance sheet structure, and regulatory compliance.
Key questions to evaluate:
Transfer pricing regulations in most jurisdictions require that intercompany loans be structured at arm’s length. The OECD’s Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations provide the international framework, and most countries have adopted some version of these rules.
Setting arm’s-length terms involves:
Interest rate benchmarking
The rate charged on an intercompany loan should be comparable to what a third-party lender would charge the borrowing entity, taking into account the borrower’s credit profile, the loan amount, tenor, currency, and whether the loan is secured. Common approaches include referencing published benchmark rates (e.g., EURIBOR or SOFR) plus an appropriate credit spread, or using transfer pricing databases that compile comparable loan transactions.
Repayment schedule and maturity
Define a realistic repayment schedule that aligns with the borrower’s expected cash flows, and set a defined maturity date. Tax authorities may challenge loans with indefinite terms or no realistic repayment prospect as lacking economic substance, potentially reclassifying them as equity contributions, which would eliminate interest deductibility for the borrower and convert interest income to dividend income for the lender.
Security
Decide whether the loan will be secured against specific assets. This decision affects the arm’s-length interest rate, since secured loans typically carry lower rates than unsecured ones.
Formal documentation is the foundation of tax compliance and audit readiness for intercompany loans. Tax authorities can, and regularly do, reclassify the loan as an equity contribution.
The loan agreement should include, at a minimum:
The agreement should be signed by authorized representatives of both entities and stored in a centralized document management system alongside the group’s transfer pricing documentation.
Both entities must record the loan on their books: the lender as a receivable, the borrower as a payable. Interest accruals should be calculated and posted at the agreed intervals (typically monthly or quarterly), using the same methodology and rates on both sides.
Regular reconciliation between the lender’s and borrower’s records is essential. Discrepancies, which commonly arise from timing differences in posting, different FX rates used for translation, or simple data entry errors, should be identified and resolved promptly. Ideally, this happens as part of a monthly close process rather than being left to quarter-end or year-end.
For group financial consolidation, intercompany loans and the associated interest income and expense must be eliminated. The receivable on the lender’s books and the payable on the borrower’s books should net to zero. Discrepancies at consolidation are one of the most common causes of delayed month-end closes in multi-entity groups.
Intercompany loans are not “set and forget.” Treasury teams should continuously monitor:
Spreadsheet reliance
Many finance teams still track intercompany loans in spreadsheets, which leads to formula errors, version control problems, and a lack of audit trail. As the number of entities and loans grows, the risk of misstatement increases.
Mismatched balances
The lender and borrower frequently record different balances for the same loan, which surfaces during reconciliation and can delay the month-end close. Establishing a single source of truth, where both entities reference the same loan record, is the most effective way to prevent this.
Non-arm’s-length terms
If the interest rate or other terms on an intercompany loan don’t reflect what unrelated parties would agree to, tax authorities may adjust the taxable income of one or both entities. This risk increases when rates are set informally or not updated to reflect changing market conditions. Regular benchmarking against published reference rates and comparable third-party transactions is essential.
Missing or incomplete documentation
Without a formal loan agreement specifying all material terms, tax authorities may reclassify the loan as an equity contribution. Standardized loan agreement templates, enforced consistently across the group, help prevent this.
Untracked FX exposure
When intercompany loans are denominated in a currency other than the functional currency of either entity, exchange rate movements can create significant unrealized gains or losses. Without centralized tracking, these exposures may go unhedged and unmonitored, introducing volatility into both entities’ financial results.
Poor visibility into cash impact
Intercompany debt obligations are sometimes excluded from the group’s cash flow forecast, creating blind spots in liquidity planning.
These practices apply to both external and intercompany debt, reflecting the approaches used by treasury teams managing complex, multi-entity debt portfolios.
Centralize your debt register
Keep all debt, external and intercompany, in one register. It underpins accurate interest calculations, forecasting, covenant monitoring, and audit readiness (see Step 3 under Managing external debt).
Automate interest and repayment calculations
Manual calculations are a persistent source of error, especially for variable-rate loans whose rate resets periodically. Automating them, and feeding the results into your forecast, keeps projections in step with the latest rates. For EURIBOR-linked loans, that means pulling in the daily rate publications automatically.
Integrate debt data with cash flow forecasting
Treat debt servicing as a first-class line item in your forecast, for both external and intercompany debt (see Step 5 under Managing external debt).
Use scenario analysis for rate exposure
For material variable-rate debt, model the effect of a 50, 100, or 200 basis point move in your benchmark rate on interest expense and cash outflows. This informs hedging decisions and gives the CFO and board a clear read on rate sensitivity.
Maintain rigorous documentation standards
Every loan needs a signed agreement on file, with all amendments, waivers, rate changes, and covenant calculations stored centrally. For intercompany loans, this underpins transfer pricing compliance; for external debt, it supports covenant reporting and lender communication.
Conduct periodic portfolio reviews
Review the full portfolio at least quarterly. Check whether refinancing could lower costs, whether the fixed and variable mix still fits the environment, whether intercompany terms still reflect market rates, and whether covenant headroom is sufficient. Involve treasury, FP&A, and tax.
Build stakeholder-ready reporting
Standardize reporting on total debt, maturity profiles, interest costs, covenant metrics, and currency exposure, for the board, lenders, auditors, and investors. A centralized platform generates these from live data.
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. Click below to register and connect with Treasury professionals worldwide
This article is written by Monkey
In every commercial relationship, one element plays a central role in shaping financial stability, supplier relationships, and supply chain performance: payment terms. Though often seen as a simple detail in a contract or invoice, payment terms have a powerful impact on a company’s cash flow, working capital, and long-term operational resilience.
For large enterprises, especially those managing complex supplier ecosystems, understanding and strategically defining payment terms is essential. With modern financial solutions, such as reverse factoring and supply chain finance platforms like Monkey, companies can optimize payment terms in a way that benefits both buyers and suppliers.
Payment terms are the conditions under which a buyer agrees to pay a supplier for goods or services. They define:
Essentially, payment terms determine the timing and structure of cash flows between companies.
Longer payment terms can help buyers preserve cash longer, improving working capital. On the other hand, shorter terms accelerate cash flow for suppliers, helping them maintain operations smoothly.
Finding the right balance is critical, especially in industries where supply chain continuity depends on suppliers’ financial health.
Fair and transparent payment terms foster trust and long-term partnership. When suppliers receive predictable payments, they can plan production, invest in capacity, and maintain service levels.
Unfavorable or inconsistent terms can damage relationships, increase turnover in the supplier base, and create operational risks.
Strategic payment terms should support financial health across the supply chain, not just the buyer’s balance sheet.
When suppliers struggle with liquidity, the entire supply chain becomes more vulnerable. Late payments or excessively long payment terms can result in production delays, inventory shortages, reduced quality, higher supplier financing costs and strong payment terms, combined with financing tools, help mitigate these risks.
Modern financial solutions allow companies to extend payment terms responsibly, without harming suppliers. One of the most effective methods is reverse factoring, which works like this:
This model shifts the credit risk from the supplier to the buyer, resulting in lower financing costs for suppliers, extended payment terms for buyers without creating financial stress and more stability across the entire supply chain.
Clear, standardized payment terms reduce administrative complexity and improve financial predictability. They help companies to accelerate invoice approvals, to reduce disputes, to simplify reconciliation and to enable better planning and forecasting
When combined with technology and supply chain finance, payment terms become a strategic tool, not just a contractual formality.
Monkey provides a comprehensive digital ecosystem that connects buyers, suppliers, and financial institutions to transform the way companies manage payment terms and working capital. Through the platform, organizations gain:
By leveraging reverse factoring solutions, Monkey enables buyers to offer competitive payment terms while boosting liquidity for suppliers, strengthening the entire supply chain. Payment terms are far more than a line on an invoice. They influence cash flow, operational stability, supplier relationships, and overall business performance.
When companies combine clear payment terms with modern financing solutions, they can extend liquidity, support supplier growth, reduce financial risks, improve working capital efficiency and build stronger, more resilient supply chains.
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. Click below to register and connect with Treasury professionals worldwide
In this 45-minute live session, Treasury Masterminds and SisID explore how Verification of Payee works in real treasury environments, where it delivers the most value, and where stronger processes are still required. This is not a discussion about regulation alone. It’s a practical conversation about payment controls, fraud prevention, and the realities of implementing VoP within corporate treasury.
In this 45-minute live session, Treasury Masterminds, ETR Digital, and Calculum explore how organisations can bridge the gap between working capital analysis and liquidity generation. This is not a discussion about dashboards and reporting. It’s a practical conversation about how companies can use data to make better decisions, unlock liquidity, and build more effective working capital strategies.
In this 45-minute live session, Treasury Masterminds and SAP Taulia explore where working capital gets stuck and what treasury teams can realistically do to improve it. This is not a discussion about working capital theory. It’s a practical conversation about where liquidity is lost, how organisations can improve visibility and control, and what actions can make a measurable difference.
We are excited to sit down with Emma West, the driving force behind one of the world’s most influential finance events—EuroFinance.
Emma’s career spans prestigious names like the Financial Times and The The Economist Group, but her path to becoming a leader in the treasury and payments space is as fascinating as the events she curates.
Join us for a special episode of the Treasury Masterminds podcast featuring Meticulous Tendai Dube, a seasoned treasury professional who has led teams across Africa and the Middle East.
Join us for a fresh take on treasury with Pavlos Panagitsas, Junior Treasury Analyst at Avramar, ESG enthusiast, and founder of ESG news platform ESGenre.
