What is a modern treasury foundation?
A modern treasury foundation connects the data, workflows, permissions, controls and reporting needed across treasury processes so teams can work with a consistent financial picture.
Treasury has accumulated technology faster than it has removed complexity
Most treasury teams do not suffer from a complete lack of technology. They have bank connectivity, ERP systems, trading platforms, payment processes, spreadsheets, reporting tools and often some form of payment or treasury management system. Individual processes may already be highly automated.
The difficulty appears when treasury needs to connect them.
A cash position may come from bank data. The short-term outlook comes from a forecast assembled elsewhere. Payment information has its own workflow. Intercompany positions sit in another process. A specialist system may handle financial instruments and exposures. Hedge accounting can still depend on a workbook maintained at month-end. When the CFO asks a question that crosses several of these areas, treasury becomes responsible for rebuilding the overall picture.
That is the real cost of fragmentation. It is measured less by the number of systems than by the amount of work required between them.
Fragmentation becomes visible when a decision crosses process boundaries
A treasury process can work perfectly well in isolation and still contribute to a fragmented operating model.
A payment can be processed correctly without automatically improving the liquidity view. A cash forecast can be well constructed without giving treasury an easy way to test what happens when assumptions change. A hedge can be economically appropriate while its accounting treatment depends on a separate month-end process. A payment report can contain all the necessary data, yet an analyst still needs to export, clean, and rebuild it before management sees it.
These are not necessarily technology failures. They are gaps between processes.
For treasury professionals, those gaps create additional work precisely when speed matters most. A question about available liquidity can become a search across cash balances, expected payments, credit facilities, forecasts and contingent commitments. A question about a forecast variance can require several versions of the same plan. A question about an unusual payment pattern can turn into another spreadsheet exercise.
The more strategic treasury becomes, the more expensive those gaps become because management increasingly expects answers during the decision, rather than several hours or days afterwards.
A foundation creates continuity between treasury decisions
A reliable treasury foundation begins below the dashboard.
Bank and ERP connectivity provide the operational data. Treasury processes turn that data into controlled activity across payments, liquidity, financial instruments and risk. Intelligence can then help users interpret what is happening or anticipate what may happen. Nomentia Analytics turns the result into information treasury can explain to management.
The important part is continuity between these layers.
When payment data, cash positions and treasury workflows share the same underlying structures, treasury no longer needs to reconstruct as much context manually. When reporting uses governed data from the operational process, users spend less time questioning which number is current. When AI operates through the same permissions and controls as the user, natural-language access does not need to create a new route around treasury governance.
This is why the foundation matters particularly as AI becomes part of treasury.
AI makes governance more important, not less
Generic AI has changed expectations around how people interact with software. Users increasingly expect to ask a question directly rather than learn where a specific report or screen is located.
That can be very valuable in treasury. A user may want to ask which payments were rejected today, what the current cash position is, or how much was paid to a particular counterparty. The system already holds the answer. The challenge is making it accessible without weakening the controls around the information.
AI in treasury therefore needs to inherit the operating model. Access needs to reflect the permissions of the person asking. Financial calculations need a reliable system basis. Proposed changes need appropriate confirmation and approval. The interaction needs to remain traceable.
With those conditions in place, AI can reduce the distance between a question and an informed decision. Without them, it simply adds another layer that treasury needs to govern.
Modern treasury also needs three views of the future
A connected foundation also changes forecasting.
Traditional cash flow forecasting attempts to answer a necessary question: what does finance currently expect to happen? That view remains essential because business input contains knowledge that historical data cannot provide.
Nomentia Predictive Forecasting adds another perspective. Historical actuals can be analysed to produce an AI-generated reference forecast, giving treasury an independent baseline against which manual assumptions can be compared. Instead of asking whether the AI or the subsidiary is “right”, finance can investigate why the two views differ.
Scenario analysis adds the next question: what happens if the assumptions change?
A forecast expresses the current expectation. A scenario allows treasury to examine the consequences of a different one. Together, these capabilities help finance move from one forward-looking number towards a more informed discussion about uncertainty, liquidity headroom and financial risk.
That matters because CFOs rarely ask treasury only for the most likely outcome. They also want to know what could change it and how prepared the organisation would be.
Control should continue when insight becomes action
The same principle applies to processes such as intercompany netting and hedge accounting.
Intercompany positions can create significant operational activity inside a group. When matching, confirmations and settlement are heavily manual, treasury spends time moving and reconciling cash that already belongs to the same organisation. A more structured intercompany netting process can reduce unnecessary settlement activity while giving treasury a clearer view of internal liquidity.
Hedge accounting presents a different challenge. The economic hedge may be understood, but IFRS 9 or other local GAP documentation, effectiveness assessment and accounting entries create a separate control burden. When these activities depend on disconnected spreadsheets, the operational hedge and its accounting evidence become two processes that need to be reconciled later.
A connected foundation keeps more of that context together. Treasury remains responsible for the judgement, while the system provides a more controlled process around the evidence.
Modular does not have to mean fragmented
There is an important distinction between modularity and fragmentation.
A modular treasury environment allows a company to introduce capabilities according to its priorities. Fragmentation occurs when those capabilities do not share enough context, data or governance and the treasury team has to connect them manually.
This distinction matters for organisations that do not want a multi-year transformation simply to improve one part of treasury. Nomentia’s 2026 research found strong interest in modular approaches, particularly among more technologically mature treasury teams. At the same time, integration complexity was the most frequently cited barrier to treasury modernisation.
The implication is straightforward. Companies want flexibility, but they do not want flexibility to create another integration problem.
A modern foundation should therefore make it possible to improve treasury incrementally while maintaining continuity between the modules that are introduced.
Measure the foundation by the effort behind the answer
The practical test for a treasury architecture is not how many functions it contains. It is how much manual work remains between an important question and a reliable answer.
How long does it take to explain the cash position? How many sources need to be reconciled before finance trusts a forecast? Can treasury understand the effect of changing assumptions without creating another workbook? Can an unusual payment be investigated from the operational data behind it? Can the organisation trace a hedge from the underlying exposure to the accounting evidence?
These are better measures of maturity than the number of applications in the technology landscape.
Treasury will always remain complex because the decisions it supports are complex. A stronger foundation does not remove that expertise. It gives treasury professionals a better environment in which to apply it.
One foundation, more useful decisions
The next stage of treasury modernisation is therefore less about digitising another isolated task and more about connecting the decisions that already depend on one another.
Payments affect liquidity. Liquidity affects forecasts. Forecasts create questions about scenarios and funding. Exposures lead to hedging decisions. Hedges create accounting consequences. Nomentia Analytics and Nomentia AI help treasury interpret the activity across those processes.
When the foundation underneath them is reliable, treasury can move through those questions with less reconstruction and greater confidence.
That is what gives finance more time for the work that still requires people: understanding what the numbers mean, deciding what matters and explaining the implications to the business.
