Treasury at the Speed of Business – Back Office No More: The Rise of the Command Centre
Written by Sharyn Tan (Views are my own) The future of treasury operations is undergoing a profound transformation, shifting from a traditional back-office function focused on static balance sheet management to a dynamic, always-on command center that orchestrates liquidity in real time. This evolution is driven by technological advancements, particularly the rise of stablecoins, tokenized deposits, and broader digital asset integration. These tools are enabling treasurers to manage not just cash positions, but the velocity of money, optionality in funding sources, and risk exposure instantaneously across borders and currencies. Historically, treasury departments operated in batches: end-of-day sweeps, periodic forecasting, and reliance on correspondent banking networks that introduced delays, high costs, and limited visibility. Today, with stablecoins like USDC and USDT surpassing hundreds of billions in market capitalization and annual on-chain transaction volumes in the trillions, treasury is becoming programmable and predictive. Fiat currencies, stablecoins, and tokenized deposits—digital representations of traditional bank deposits issued on blockchains—are coexisting in a seamless ecosystem. This allows for composable liquidity, where funds can be moved, converted, or deployed programmatically without intermediaries or settlement windows. Instant Visibility and Predictive Forecasting One of the most immediate benefits is real-time visibility. Traditional systems often provide delayed snapshots, but blockchain-based infrastructure delivers continuous, transparent ledgers. Treasurers can monitor global cash positions down to the second, track inflows and outflows automatically, and trigger actions like sweeps or FX conversions when balances hit predefined thresholds. This reduces idle capital buffers—2.5–4% in traditional setups can equate to tens of millions —and improves capital efficiency. Forecasting evolves from reactive to predictive. AI-driven tools analyze historical patterns, market data, and real-time flows to anticipate liquidity needs. For instance, systems can automatically rebalance across entities, optimize for yield on excess balances, or position funds closer to operational hotspots. In cross-border scenarios, stablecoins enable near-instant settlement (often in seconds or minutes), slashing costs and FX exposure compared to multi-day traditional wires. Liquidity as a Composable Network The core shift is viewing liquidity as a dynamic network rather than isolated pools. Stablecoins act as an interoperability layer, connecting disparate systems and enabling 24/7 operations. Tokenized deposits, issued by regulated banks, offer similar programmability while staying within the banking framework—often with deposit insurance and direct balance sheet integration. Reports indicate banks are increasingly favoring tokenized deposits for institutional use, as they plug into existing treasury workflows without disrupting regulatory treatment. This coexistence creates optionality: treasurers can choose the optimal form of money for each use case—stablecoins for fast cross-border payments, tokenized deposits for wholesale settlement, or traditional fiat for certain compliance needs. Programmable features, like smart contracts, automate complex workflows: conditional payments upon milestone achievement, automated collateral transfers, or yield-earning while funds are in motion. Challenges on the Path Forward Achieving this future isn’t just about adopting technology—it’s about building trust, interoperability, and cultural change. Treasurers must develop fluency in digital assets, including understanding blockchain mechanics, wallet management, and on-chain risks. Governance frameworks for programmable money are essential to mitigate smart contract vulnerabilities or de-pegging events, even as regulations like the U.S. GENIUS Act (passed in 2025) provide clearer guardrails for stablecoins, requiring 1:1 reserves and transparency. Interoperability remains a hurdle: not all blockchains or systems communicate seamlessly, necessitating standards and partnerships. Cultural shifts are equally critical—treasury teams historically risk-averse must embrace experimentation while maintaining robust controls. New ecosystem partnerships—with fintechs, blockchain platforms, and traditional banks—are vital for scaling. The Treasurer’s Strategic Imperative Ultimately, the future of treasury isn’t about going digital for novelty—it’s about accelerating decision velocity. Technology becomes a liquidity enabler, turning treasury from a pure cost center into a strategic partner to help drive business value. Treasurers who thrive will treat digital tools as extensions of their toolkit: optimizing velocity to free working capital, reducing borrowing costs, and earning yield on otherwise idle funds. Those who view these innovations as risk multipliers will lag, while forward-looking leaders will build predictive, composable operations that respond instantly to opportunities and threats. In a world of always-on global finance, the treasury command center isn’t a distant vision—it’s emerging now, redefining how organizations will manage money at the speed of business. Also Read Join our Treasury Community 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. 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Franklin
AI in fintech: Separating the show from the work
This article is a contribution from our partner, Embat Theo Wasserberg, Head of UK&I at Embat Fintech’s AI moment in 2025 exposed the gap between demos and real impact. Operational AI, not pilots, is reshaping finance workflows and decision-making. At Google’s Gemini Founders Forum this year, they had a term for what happens when AI looks impressive in demos but never changes how work gets done: AI theatre. Finance and fintech teams know this performance well. They sat through it all year. The pilot that would “transform cash visibility.” The dashboard that would “revolutionise forecasting.” The platform that would “finally connect everything.” Exciting presentations. Polished decks. Then back to hunting through spreadsheets for yesterday’s cash position. 2025 wasn’t the year AI-infused fintech modernisation failed. It was the year we learned what separates the show from the work. What Actually Happened in 2025 2025 didn’t deliver the fintech AI revolution everyone predicted. Instead, we saw something more valuable: growing awareness of what modernisation actually requires. AI Pilots Are Easy, AI-First Workflows Are Not Teams stopped pretending AI deployment was simple. Painful experience helped people distinguish between “AI pilots” (exciting to demo, impossible to scale) and “AI-first workflows” (boring to build, essential to operations). Whether it’s payments, banking or treasury, everyone can list a dozen AI use cases they were pitched or watched a demo of. The challenge wasn’t innovation, identifying a problem on paper or imaginative solutions. It was turning the exciting demo into something banking operations, payment processing teams, and treasury departments could trust and use daily. Top-down AI mandates produced impressive presentations that never changed how work got done. We learned that real progress happens when the people closest to the work can design and own their agents. The lesson: without the right infrastructure, AI can’t scale beyond the team that built it. The Board-Level AI Gap A recent Think & Grow report reveals that only 32% of UK startups and scaleups have AI expertise at board level, trailing the 40% of FTSE 350 tech firms that have appointed specialists. This gap risks stifling growth amid strong investor interest in AI. However, there’s a stark divide by company size. Scaleups with over £50m revenue are more than three times as likely to have AI expertise (50%) compared to their smaller counterparts (15%), though 32% of companies overall plan to make appointments in the next year. As fintech evolves toward AI-first workflows, board-level AI knowledge becomes essential to distinguish hype from scalable operations, ensuring startups maximise funding and compete effectively. Breaking the 30% Automation Ceiling For twenty years, finance automation followed the same principle: if X happens, do Y. That approach created value – automating maybe 30% of manual work – but it also created a ceiling [Deloitte Survey, 2024; McKinsey Report, 2024]. Real life rarely follows rules perfectly. A customer pays two invoices in one transaction. Someone mistypes a reference number. A file format changes. Suddenly, the system freezes, and a human must step in. The promise of efficiency evaporates in exception handling. AI, by contrast, doesn’t require every rule to be predefined. It understands intent. You tell it the desired outcome, and it figures out how to achieve it. That’s the difference between 30% automation and 99%. It’s also the difference between a system that merely saves time and one that transforms how finance operates. The real breakthrough in 2025 was understanding this wasn’t just incremental improvement. It was a different category of capability. The Contained Value Breakthrough One of 2025’s most important lessons came from understanding what didn’t work, and why.Early AI mistakes involved treating it as a cosmetic upgrade atop legacy systems. Teams that succeeded took a different approach: contained value. Contained value means specific, auditable use cases where you know what AI will do, who it serves, and how success will be measured. Not “transform X process or industry.” Instead: automate reconciliation first, then forecasting, then cash visibility. This builds confidence, one use case at a time. The teams that flipped from cost centre to strategic partner did so by making AI agents accountable for specific outcomes. Not vague efficiency targets, but measurable work removed: reconciliation time cut by 75%, forecasting accuracy above 90%, audit prep compressed from weeks to days. They stopped talking about AI strategy and started retiring manual processes. They killed familiar workflows when data showed better paths, even when it made people uncomfortable. We Watched Finance’s Role Fundamentally Shift Something deeper was happening beneath the surface of failed pilots and stalled initiatives. Finance itself was evolving. In a revealing shift, HSBC found that 64% of CFOs at large organisations now consider treasurers part of the C-suite, reflecting a mindset change: finance is no longer viewed purely as a cost centre, but as a catalyst for insight and strategic agility [HSBC Corporate Risk Management Survey, 2024]. This wasn’t just finance functions – whether treasury, payments operations, or banking teams – getting better at their traditional tasks; they were becoming something entirely different. Digital adoption is central to solving this challenge: 80% of CFOs expect digital tools to dominate operations by 2025, while 30% of finance tasks are fully automatable [Deloitte Survey, 2024; McKinsey Report, 2024]. By modernising tools and processes, companies can both attract top talent and unlock productivity gains.Over the next five years, 69% of CFOs expect greater emphasis on data analytics, 60% anticipate more scenario planning, and 55% say finance will become a more embedded strategic partner across the business [Cherry Bekaert CFO Survey, 2025]. But you can’t advise strategy while drowning in exception reports. The Real Shift Isn’t Technical What 2025 ultimately revealed is that modernisation isn’t a technology contest, it’s a cultural reckoning. Finance operations are not evolving just because the new tools are powerful. They’re changing because leaders finally confronted how much of their operating model depends on institutional memory, heroic manual work, and processes that only “function” because people quietly filled the gaps. Modernisation begins not when teams deploy agents, but when they stop accepting complexity,…