This article is written by Nadia Callaghan
For decades, Treasury has operated inside an architecture defined by batch‑based finance — scheduled sync windows, overnight files, and periodic data drops. These patterns were not accidental. They reflected the technological limits of the time: ERPs processed information in bulk, banking systems were built around end‑of‑day cycles, and operational platforms pushed data only when the system could handle it. In that world, batch processing was not a compromise; it was the only viable method for moving financial information across an organisation.
But the environment Treasury supports today is fundamentally different. Modern organisations operate continuously. Payments clear instantly. Cash positions shift throughout the day. Operational systems generate financial events in real time. Treasury’s responsibilities — liquidity, exposure, risk, governance — now unfold in a landscape where waiting for the next batch cycle is not simply inefficient; it is strategically incompatible with how businesses function.
This is why APIs matter. They are not a marginal improvement or a new integration trend. APIs represent a structural shift from periodic, delayed data movement to continuous, event‑driven connectivity. They eliminate the lag that batch processing creates and replace it with immediacy. In doing so, they redefine what Treasury can see, decide, and control.
Batch‑based finance breaks down because it creates delays by design. Systems only sync at scheduled intervals, and between those windows, each platform maintains its own version of reality. Treasury, which depends on accuracy and timeliness, is disproportionately affected by these gaps. A vendor bank detail change may not propagate until the next file drop. An invoice void may remain active in downstream systems for hours. Payment status updates may conflict, creating duplicate payments or “last write wins” errors. These issues are not caused by poor process design; they are symptoms of timing.
The consequences ripple across the organisation. Procurement transactions may not appear in the ledger until the next batch run, reducing visibility into commitments and cash flow. AR and AP may operate on stale data, creating mismatches that Treasury must later reconcile. Month‑end close becomes heavier because issues surface only after batch jobs complete. Teams spend hours investigating mismatches, reprocessing failed files, and correcting timing‑related errors. Treasury becomes responsible not only for liquidity and risk, but for resolving the operational drag created by outdated integration patterns.
Responsiveness suffers most. Batch systems cannot support instant balance checks, real‑time payment status, or intraday liquidity decisions. Treasury becomes reactive, waiting for the next cycle to understand what has already happened. In a world where financial events occur continuously, this delay is not simply a technical inconvenience; it is a strategic liability.
APIs change this dynamic entirely. They allow systems to exchange data instantly whenever a financial event occurs. Instead of waiting for scheduled sync windows, information flows continuously. A payment is initiated, and the status updates immediately. A supplier record changes, and the new details propagate across the ecosystem in real time. A balance shifts, and Treasury sees it as it happens. This immediacy unlocks capabilities that batch processes cannot match.
Real‑time liquidity accuracy becomes possible. Treasury no longer relies on overnight MT940s or camt.053 files. Intraday statements and live balances provide a view of cash positions as they are, not as they were hours ago. Continuous cash visibility emerges because procurement, AP, AR, and Treasury operate from a single, unified financial truth. Reconciliation becomes more autonomous because systems no longer drift out of sync. Operational decision cycles compress from hours to minutes. Treasury becomes a real‑time operator rather than a batch‑based reviewer.
The broader ecosystem strengthens as well. Supplier data, tax calculations, financial postings, and compliance validations can be synchronised automatically. Governance improves because timing‑related errors decline. Operational risk decreases because issues surface immediately rather than hours later. Strategic capacity increases because teams spend less time correcting timing issues and more time improving processes, modelling scenarios, and partnering with the business.
This shift is already underway. Treasury integration patterns are evolving toward hybrid landscapes where batch files remain the backbone for structured, scheduled flows — statements, accounting extracts, regulatory reporting — while APIs provide immediacy for intraday balances, payment status, and straight‑through processing. Middleware platforms orchestrate the entire ecosystem, managing scale, routing, and transformation across both batch and API flows. The architecture becomes more flexible, more responsive, and more aligned with how modern organisations operate.
The implications for Treasury leadership are significant. Moving from batch‑based finance to API‑driven connectivity is not a technology upgrade; it is a transformation in how Treasury functions. Liquidity, exposure, and risk become continuous operational realities rather than end‑of‑day concepts. Governance strengthens because data is current. Operational risk decreases because issues are surfaced earlier. Strategic capacity increases because teams are freed from the operational drag created by timing gaps.
Batch processing still has a place. Payroll, end‑of‑day settlements, and certain legacy environments will continue to rely on structured, scheduled flows. But batch cannot support the real‑time liquidity and operational speed required today. It cannot provide the immediacy needed for global operations, continuous financial events, or instant decision cycles. It cannot keep pace with the dynamic organisations Treasury now serves.
API‑driven Treasury is therefore not a trend; it is the inevitable response to a world that no longer moves in batches. Leaders who embrace API connectivity will gain sharper liquidity accuracy, continuous cash visibility, faster operational execution, stronger governance, fewer errors, and a unified financial ecosystem. They will build Treasury functions capable of operating with confidence in real time, not simply reporting on what happened yesterday.
The end of batch‑based finance is not a critique of the past. It is an acknowledgement that the operating reality of modern business has changed — and Treasury must change with it. APIs provide the architecture for that future. The organisations that adopt them will move faster, see more clearly, and operate with greater control. Those that cling to batch‑based finance will increasingly find themselves managing complexity rather than mastering it.
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 a contribution from our partner, Embat
Accounting with the best financial team is a critical factor of success for any business, so nothing is more important for the CFO than surrounding themselves with the right people, this is what will allow you to enhance your role and focus on value generation from a much more strategic than operational perspective.
Traditionally, the financial domain was characterised by the mastery and application of a series of technical knowledge, which when well used not only allows one to ‘explain the past’, but also to generate reliable information for business decision making thus minimising the risk of errors.
It is the advance of technology itself, which has allowed them to redefine their role, following the same line of evolution as that of the CFO themselves, that is, towards a vision much more focused on the company’s business and strategy and not merely focused on explaining what has happened and on regulatory compliance.
This reconversion of the area requires the need for professional profiles that not only have a solid “technical” knowledge, but also have the necessary skills to take advantage of the benefits offered by the new technologies available.
It is above all a change in the culture of the area that must accompany and support the evolution of the business itself, adopting new ways of working, based on collaboration, experimentation and continuous learning, while at the same time requiring a rethinking of the operating model, including the automation of tasks and the redefinition of internal processes.
Combining analytical rigor with business intuition, technical precision with the flexibility to adapt to changes in the environment, is essential when it comes to building a financial team, where technical expertise becomes a necessary (and mandatory), but not sufficient, skill.
It is therefore necessary for financial professionals to have a broader understanding of the business they manage, in order to be able to adapt as quickly as possible to changes, which are becoming faster and faster.
The evolution of the CFO in today’s business strategy
Discover the evolution of the CFO and their relevance in today’s business landscape.
Being able to translate and being able to communicate complex information in such a way that it can be used for decision making by the rest of the organisation, which generally speaks a different ‘language’ and does not usually have the same technical knowledge, requires the development and good application of what are defined as ‘soft skills’.
Empathy, proactive attitude, autonomy, thinking critically about how things are done, adapting to new scenarios, interacting with interdepartmental teams, are critical and essential skills that any finance team must have in order to turn data into analysis, business opportunities into results and strategy into profitability for the company.
This is where the CFO takes on a central role, in the sense of being able to integrate the different skills of the financial team, identifying both their strengths and weaknesses, thus ensuring that all members of the team work towards the same common goal.
Therefore, it becomes relevant to promote diversity within the financial team not only in terms of the incorporation of people with different professional experiences, but also with other ways of thinking and approach, in order to encourage the generation of innovative ideas that can become creative solutions to the problems that arise.
A diverse finance team can also be better prepared to meet the challenges of a globalized marketplace. Companies operating in multiple countries need teams that understand the particularities of each region, both from a technical and cultural perspective.
On the other hand, it is necessary to promote a culture of open and ‘bidirectional’ communication between the CFO and the members of their team, where the contributions of each one of them are valued, something that is relevant to strengthen the group and thus tend to achieve the proposed objectives.
Trust is another essential requirement for building a cohesive team, especially when confidential and strategic information must often be managed, which is why it is essential to guarantee its integrity. Likewise, it must be bidirectional, thus generating a climate of security that reinforces open communication, as well as the responsible assumption of risks and the ability to learn not only from the successes achieved, but also from the failures.
Thus, forming a financial team is a process that requires a certain “science” in the selection of the best talents with the necessary technical knowledge for the development of their functions, as well as the purest “art”, since it must be complemented with the ability to adapt, innovate and collaborate closely with other areas of the company.
In this way, a balanced integration between art and science is what really determines the difference between a financial team that is oriented to the administration of resources, and another that is dedicated to the generation of value through continuous 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 Nadia Callaghan
Treasury has quietly become one of the most powerful levers for improving financial performance. In many organisations, it is still treated as a protective cost-centre function, focused on liquidity, compliance and risk management. Yet the businesses that outperform today are those that recognise treasury as a value creator. From my experience, optimising finance returns is not only about taking more risk; it is also about tightening the fundamentals that determine how efficiently money moves through the organisation.
The first and most immediate source of value comes from strengthening collections. Cashflow improves dramatically when organisations collect what they are owed, when they are owed, without leakage or delay. Accounts receivable often suffers from fragmented ownership, inconsistent follow‑up and manual allocation processes that slow everything down. Commission collections can be even more complex, especially in industries where revenue is shared across multiple parties. When treasury leads a disciplined approach to collections, supported by real‑time ageing visibility, automated reminders and clear accountability, liquidity improves almost instantly. Faster allocation of incoming cash reduces unapplied balances, improves forecasting accuracy and frees capital that would otherwise sit idle.
Cost discipline is the second major lever. Operating expenses are rarely fixed; they simply feel that way because they are not reviewed often enough. Treasury can materially improve returns by treating bank fees and partner contracts as commercial agreements rather than administrative necessities. Regular fee reviews reveal charges for services no longer used, pricing tiers based on outdated volumes and FX or payment fees that are significantly above market rates. Debt‑side partner contracts often contain renewal clauses, utilisation fees or covenant‑related costs that can be renegotiated when treasury brings data to the conversation. Organisations that review these agreements quarterly typically achieve meaningful cost reductions without changing their operating model.
Once collections tighten and costs come under control, surplus liquidity becomes visible. Idle cash is one of the most common drags on returns, and yet it is also one of the easiest to fix. Treasury can deploy surplus funds into safe, yield‑generating instruments such as money market funds, notice accounts, term deposits or custody accounts for short‑term securities. These options provide daily liquidity, low risk and significantly better returns than traditional operating accounts. Even modest yields create meaningful profit when applied to large balances that previously sat dormant.
Centralising liquidity amplifies these gains. Cash pooling allows organisations to treat group‑wide cash as a single strategic asset rather than a collection of isolated balances. Physical pooling sweeps cash into a master account, reducing external borrowing and enabling centralised investment strategies. Notional pooling aggregates balances virtually, optimising interest without the complexity of intercompany loans. Both approaches reduce reliance on external debt, lower interest expense and increase the organisation’s ability to generate returns from its own liquidity.
The final lever is automation, which is often underestimated in its impact. Manual treasury processes consume time, introduce errors and prevent teams from focusing on value‑creating activities. Automating bank reconciliations, AR allocation, commission matching, payment runs, forecasting and intercompany settlements reduces operating costs and strengthens control. Automation also improves data quality, which in turn improves decision‑making. Treasury teams that operate with clean, real‑time data can model scenarios more accurately, anticipate liquidity needs earlier and respond to market conditions faster.
Optimising returns is not a single initiative; it is a discipline. When treasury strengthens collections, reviews expenses with commercial rigour, deploys surplus cash intelligently, centralises liquidity and automates manual processes, it becomes a profit engine rather than a cost centre. The organisation benefits from improved cashflow, reduced leakage, lower operating costs and higher returns on liquidity. Treasury’s role shifts from safeguarding the business to powering it, creating a financial foundation that supports growth, resilience and strategic ambition.
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 a contribution from our content partner, Kyriba
There is a quiet revolution happening inside the world’s most forward-looking finance organizations, and most treasury teams are watching it from the hallway. Artificial intelligence is no longer a pilot program, a buzzword in a vendor deck, or a problem for IT to solve. Treasury AI adoption is actively reshaping how cash is managed, how risk is quantified, and how financial leadership earns its seat at the strategic table.
The question is no longer whether AI will transform treasury. It already is. According to Kyriba’s 2026 CFO Survey, approximately 92% of global CFOs are integrating AI into some of their processes and decision-making. The only question is whether yours will be among those driving that transformation, or scrambling to catch up with those who did.
Let’s be honest about what the hesitation often looks like: concern about data security, skepticism about ROI, uncertainty about where to start, and (perhaps most dangerously) the comfort of the familiar. These are understandable instincts. Treasury has always been a function defined by precision and caution. But those same instincts, left unchecked, become an existential liability when the competitive landscape is moving at the speed of AI adoption.
Consider what’s at stake. While your team manually reconciles bank statements and consolidates cash positions across 40 entities, an AI-enabled competitor is receiving real-time global liquidity intelligence before the market opens. While your analysts are building this week’s FX exposure model in Excel, a peer institution’s system has already flagged a correlated risk in a currency pair you haven’t touched yet. The gap isn’t just operational efficiency; it is strategic foresight. And in treasury, the cost of delayed foresight is measured in basis points, counterparty risk, and missed working capital optimization, sometimes in the tens of millions.
Waiting for AI to be “proven” in treasury is like waiting for the internet to be proven in banking. The proof is already in, and the cost is being paid by those still waiting.
Strip away the hype and the financial case for treasury AI adoption is concrete and compounding. Cash flow forecasting, historically the most labor-intensive and least accurate function in the treasury toolkit, is being transformed by machine learning models that learn from ERP data, payment patterns, and external signals simultaneously. According to Kyriba customer data, organizations deploying AI forecasting are reporting 30-50% improvements in forecast accuracy, translating directly into lower precautionary cash buffers and higher yield on deployed liquidity.
On the risk side, AI is enabling dynamic FX hedging programs that adjust in near-real-time to exposure changes rather than quarterly rebalancing cycles, a structural advantage in volatile macro environments. For organizations with complex intercompany structures, AI-powered netting and pooling optimization is consistently surfacing working capital improvements that manual treasury operations simply cannot detect at the required speed or granularity.
Treasury teams deploying AI automation in cash positioning, payment processing, and reporting are reclaiming 15-25 hours per analyst per week, time that elite treasury organizations are reinvesting into capital structure strategy, M&A support, and board-level financial risk advisory. That is not incremental improvement. That is a fundamental repositioning of what treasury contributes to the enterprise.
The AI fears circulating in treasury circles deserve acknowledgment, but not accommodation. Concerns about model explainability are legitimate; the answer is to demand transparency from vendors and build internal AI literacy, not to abstain. Concerns about data security are valid; the answer is rigorous governance frameworks, not a blanket moratorium on adoption. Concerns about job displacement deserve a thoughtful response: treasury teams that adopt AI don’t shrink; they evolve. The analysts who once built cash reports become the strategists who interpret AI-generated intelligence for the CFO and the board.
What is worth examining honestly is whether vague discomfort is masquerading as prudent risk management. Every month a treasury organization delays AI adoption is a month of compounding disadvantage: in forecast quality, in working capital efficiency, in FX risk management, and ultimately in the credibility of finance leadership as a strategic partner to the business.
CFOs and treasurers are uniquely positioned to lead enterprise AI adoption, not just within finance, but as a model for the broader organization. Treasury sits at the intersection of data, risk, and strategy. The function already commands the systems, the governance instincts, and the cross-functional relationships needed to deploy AI responsibly and at scale. The organizations that seize this moment will not simply become more efficient treasury departments. They will become the intelligence engines of their enterprises, providing the real-time financial visibility and predictive risk insight that transforms how the C-suite makes decisions.
That is a future worth leaning into. The technology is mature enough to deliver. The business case is clear enough to defend. The only variable that remains is leadership conviction.
Imagine a treasury team that had fully embraced AI in cash forecasting, FX risk, liquidity optimization, and reporting. How much more would they know? How much faster would they move? And how much more would the business trust them with? If the honest answer unsettles you even slightly… what, specifically, is holding you back?
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.
