What we have been trying to solve
When we speak with treasury and finance teams about technology, the conversation usually starts with a process. Reporting takes too long. The forecast procedure is difficult and with high efforts. Intercompany settlement still requires a spreadsheet. Hedge accounting creates too much work at month-end. Someone in treasury spends half the day answering questions that the system technically already contains the answer to.
Behind those individual issues is usually the same structural problem: the process works, but too much effort is required between one part of treasury and the next.
That is the thinking behind the latest additions to Nomentia’s Smart Treasury Suite.
We have been extending the suite in areas where treasury teams need stronger insight, more forward-looking decision support and better continuity between analysis and action. Some of the capabilities use AI. Others automate processes that have remained surprisingly manual. What connects them is that they work on the same treasury foundation rather than introducing another standalone layer that needs to be maintained separately.
Here is what is changing and, more importantly, what it means in practice.
Nomentia Analytics: Start with a trusted reporting baseline
One of the most common finance routines is still surprisingly repetitive. For example payment data is exported, cleaned, moved into a familiar workbook, turned into pivot tables and checked against the previous period. The process works, but it has to work again next month - with the same effort again.
Nomentia Analytics brings that recurring reporting closer to the operational data itself.
Out-of-the box dashboards and reports are created and maintained by Nomentia and cover common questions e.g. around payment value and volume, currencies, counterparties, geographies, payment types and rejection patterns. The deliberate choice here is consistency. A standard dashboard should mean the same thing every time it is opened.
For teams that need something more specific, the Nomentia self-service reporting provides flexibility on the same underlying data. We keep a clear distinction between the built-in logic that Nomentia owns and the custom logic the customer creates.
Natural-language interaction adds another way into the information. Together with Nomentia AI, a user can approach a more ad-hoc question conversationally rather than turning every new management request into another reporting project - and AI building the dashboards.
The outcome I care about is simple: routine dashboards should already be there, while unusual questions should become cheaper and faster to answer with the help of AI.
Nomentia Predictive Forecasting: give the manual forecast an independent reference point
I do not believe AI alone should take ownership of a company’s cash flow forecast.
Treasury still needs business input. A model cannot know that a subsidiary expects a delayed customer payment because a contract negotiation has changed, or that a planned investment has moved to another quarter, unless that information exists in the data.
What AI can provide is a useful second perspective.
Nomentia Predictive Forecasting analyses historical cash flow data and produces a separate AI-generated reference forecast. It can automatically evaluate different statistical approaches and identify the model that performs best for the individual time series. The result is then available alongside the existing forecast rather than replacing it.
That side-by-side view changes the conversation.
When the subsidiary forecast and the system-generated reference are close, treasury gains another reason to be comfortable with the assumption. When they are far apart, the difference becomes something worth investigating. But customers can choose to take over the prediction into their forecast. Or even skip the manual subsidiary forecast to save a lot of effort.
The aim is therefore broader than forecast accuracy. It is forecast confidence. Treasury can see what the business expects, what historical behaviour suggests and, later, what actually happened.
Nomentia AI and AI Agents: let treasury ask the system directly and get work done with AI
There is a strange inefficiency in financial software: the answer can already be in the system, while finding it still depends on knowing exactly where to click.
A treasury analyst may want to know which payments were rejected today. The CFO may ask how much was paid to a counterparty last month. A new team member may simply need to understand how to perform a process. Each question can start another navigation exercise.
Nomentia AI gives users a natural-language route into the treasury information they are already authorised to access.
The governance around that interaction is the part we have spent a great deal of time thinking about.
The language model does not become the calculation engine for treasury. Financial figures and calculations come from deterministic Nomentia platform services. The AI operates within the permissions of the person asking the question. When it supports an action that changes something in the platform, the proposed change requires explicit confirmation. Existing approvals in the underlying treasury process remain in place.
The same principle extends to AI Agents saving efforts in process execution. Approved MCP-capable AI clients like Claude, ChatGPT or Microsoft Copilot can interact with Nomentia through the user’s authentication and the same permissions and controls.
This gives organisations a governed route for AI-agent interaction without creating a parallel version of treasury outside the platform.
For me, this is one of the most important design principles in the entire release: AI should make treasury easier to work with while preserving the control model treasury already depends on.
Intercompany Netting: reduce the work created inside the group
Intercompany activity is another good example of a process that can appear simple until the number of entities, currencies and obligations increases.
The gross amount of internal transactions can create a surprisingly large amount of operational work. Positions need to be matched, differences investigated, confirmations collected and settlement payments prepared. When that happens through spreadsheets and email, treasury becomes the coordinator of a process that is difficult to scale.
Intercompany Netting brings that activity into a more structured workflow.
Gross obligations can be consolidated into net positions and settlement instructions, disputes can be solved easily, reducing the number of movements that ultimately need to take place. For treasury, that can improve more than process efficiency. It also creates a clearer view of internal liquidity and reduces the amount of cash being moved unnecessarily around the group.
This is an area where the value becomes much stronger when netting, payments and liquidity are considered together rather than as separate processes.
Hedge Accounting: bring IFRS 9 evidence into the controlled process
FX and interest rate hedging is another area where the economic decision and the accounting process can become disconnected.
Treasury identifies an exposure and enters a hedge. Then comes the documentation, effectiveness assessment, OCI treatment and accounting entries required to maintain the hedge relationship under IFRS 9 or other local GAP.
For many teams, a significant portion of that evidence is still managed through spreadsheets and month-end routines.
Nomentia Hedge Accounting supports the entire hedge lifecycle under IFRS 9 from initial designation through subsequent hedge events and final settlement. The system generates formal hedge documentation, supports effectiveness assessment, and generates accounting entries according to the defined hedge accounting treatment.
The initial supported scope includes FX forwards, FX swaps and single-currency interest-rate swaps, with eligible hedged items including highly probable foreign-currency transactions and relevant FX and variable-rate exposures.
The value is not simply that a calculation becomes automated. The bigger improvement is continuity. The hedge relationship, its documentation and its accounting treatment remain part of a controlled and auditable workflow rather than being reconstructed around period-end.
Scenario Analysis: bring the “what if?” question into the same financial picture
Forecasting tells treasury what is currently expected. Scenario analysis addresses the question that normally comes immediately afterwards: what happens if the assumption changes?
This can be a movement in FX, a different liquidity assumption or another financial change that treasury needs to understand before a decision is made.
Scenario Analysis is intended to bring that what-if perspective into the same decision environment, so treasury can compare alternative outcomes without breaking the analysis out into another offline model. It also helps keep contingent factors, including guarantees, visible when finance assesses the broader liquidity picture.
We will go into the capability in more detail separately. At suite level, its role is straightforward: give treasury a structured way to move from “this is our current expectation” to “this is how the financial position changes under a different assumption.”
These capabilities become more useful when they are connected
It is easy to look at these developments as six separate product announcements. That would miss the part I find most important.
Consider one treasury question: Can we stand behind our liquidity position for the next quarter?
Nomentia Analytics helps explain what has already happened. Nomentia Predictive Forecasting provides an independent reference for what may happen. Scenario Analysis tests how that position changes when assumptions move. Nomentia AI gives users a faster way to interrogate the information. Intercompany Netting can improve the use of liquidity already inside the group. Nomentia Hedge Accounting keeps the risk-management decision connected to its accounting evidence.
None of these decisions exist completely on their own.
That is why we have been building the suite around a shared foundation of connectivity, treasury data, workflows, controls and reporting. Intelligence becomes much more useful when it already understands the operating context around the answer.
Where should treasury start?
The answer will be different for each organisation.
A team spending a day every month rebuilding payment reports has a very different first priority from a treasury function that already has strong visibility but lacks confidence in its forecast. A company with many subsidiaries may see the greatest immediate value in netting. Another may have mature risk management but still rely heavily on spreadsheets to meet its IFRS 9 requirements.
I would start by looking for the manual bridge that creates the most friction around an important financial decision.
Where does information have to leave the system before it becomes useful? Where does one expert become the bottleneck for everyone else? Where does the team repeatedly reconcile two versions of the same number? Where is a critical control dependent on a spreadsheet? Where does management ask a question that treasury cannot answer while the conversation is still happening?
Those areas tell you where the foundation needs to strengthen first.
The Smart Treasury Suite is modular for exactly that reason. Treasury teams should be able to improve one area without beginning a wholesale system replacement, while still knowing that the next capability can build on the same operating foundation.
The direction of modern treasury
Treasury technology has spent many years automating individual activities. That work remains important, but the next challenge is how those activities support one another.
A payment should contribute to the liquidity picture. The liquidity picture should support the forecast. The forecast should be testable under different scenarios. Risk decisions should remain connected to their controls and accounting consequences. Nomentia Analytics should explain what happened. Nomentia AI should help users reach the information faster without creating a shortcut around governance.
That is the direction we are taking with the Smart Treasury Suite.
For treasury and finance teams, the practical outcome should be a working environment where less time is spent assembling the financial picture and more time is available to interpret it, challenge it and decide what should happen next.
Marc Vietor
Chief Product Officer, Nomentia
