Nomentia Cash Flow Forecasting
Nomentia Cash Flow Forecasting is the treasury forecasting module of the Smart Treasury Suite, built for group treasury teams. It merges ERP, bank, subsidiary and treasury data into one rolling forecast, with AI-generated reference forecasts beside manual inputs.
What is Nomentia Cash Flow Forecasting?
Nomentia Cash Flow Forecasting is the cash forecasting module of the View pillar of the Nomentia Smart Treasury Suite. It is one component of a wider platform whose other pillars, Connect, Pay, Manage, Optimise and Advise, cover bank connectivity, payments, treasury management and analysis. What follows describes the forecasting module alone, not the full suite. The module builds and manages cash flow forecasts from ERP, treasury, subsidiary and bank data in one place. Four capabilities are put forward: flexible rolling forecasts, AI-generated reference forecasts, side-by-side comparison of manual and AI figures, and configurable models and scenarios. Rolling forecasts are assembled from accounts receivable, accounts payable, bank data and treasury instruments, and timing or amounts can be adjusted without altering the source data. The AI reference forecast is derived from the customer's own material: historical bank transactions, ERP actuals and past forecasts. The models look for recurring timing and amount patterns, and around three years of consistent history is recommended for the best accuracy. This forecast does not replace subsidiary or treasury forecasts; it sits beside them as an objective reference. Subsidiaries keep entering or uploading their figures through controlled templates with validation rules and deadlines. An Auto-select option can evaluate and apply the best-performing model, and users choose the source transactions, model, horizon, sensitivity and scope for each use case, whether receivables, payables, entities or scenarios. Forecast versions can be frozen and kept for plan-versus-plan and plan-versus-actual analysis, so accuracy becomes measurable rather than anecdotal. Multi-currency handling includes exchange rate integration, with figures shown in transaction, entity or group currency and aggregation by country, region, division, subgroup or group. Data reaches the module through the suite's connectivity layer: ERP systems including SAP, Oracle NetSuite, Microsoft Dynamics 365, Oracle Fusion and Sage, plus banks, trading platforms and market data. The publisher is Nomentia Oy, headquartered in Espoo, Finland, with more than 250 employees, seven offices and over 1,400 customers across Europe. The platform is cloud-native SaaS running on Microsoft Azure. A separate in-app assistant, Nomentia AI, is offered elsewhere in the suite, with an MCP server announced for summer 2026.
What it does
- Build rolling cash flow forecasts from accounts receivable, accounts payable, bank data and treasury instruments in one place
- Generate an AI reference forecast from historical bank transactions, ERP actuals and past forecasts
- Compare manual forecasts and the AI forecast side by side in the reports, with no export or reconciliation
- Combine subsidiary submissions with ERP, bank and treasury flows in a single forecast
- Freeze forecast versions and track accuracy over time through plan-versus-plan and plan-versus-actual analysis
- Simulate scenarios by adjusting amounts and timing without touching the source data
- Aggregate by country, region, division, subgroup or group, in transaction, entity or group currency
When to use Nomentia Cash Flow Forecasting / When not to
A quick filter to help you decide if Nomentia Cash Flow Forecasting is the right fit.
When to use Nomentia Cash Flow Forecasting
- Group treasury teams managing multi-entity, multi-currency and multi-bank cash positions across several countries
- Finance organisations that collect forecasts from subsidiaries and need controlled templates, validation rules and submission deadlines
- Companies running several ERP systems in parallel, such as SAP, Oracle NetSuite, Microsoft Dynamics 365, Oracle Fusion or Sage, that want a single consolidated forecast
- Treasury and controlling teams that want to measure forecast accuracy over time through frozen forecast versions and plan-versus-actual analysis
- Capital-intensive sectors named by the vendor: automotive, construction, retail, healthcare, manufacturing, pharmaceuticals, technology, transport and logistics, utilities and trading
When not to use Nomentia Cash Flow Forecasting
- Small businesses and teams expecting a self-service sign-up: access runs through a negotiated enterprise subscription, with no online registration anywhere on the site
- Buyers who need a published price, a free plan or a free trial before speaking to a salesperson, since none of the three is advertised
- Newly created entities or businesses without a consistent banking history: around three years of consistent data is recommended for the best AI accuracy
- Teams hoping to hand forecasting over to a machine entirely, as the AI produces a reference forecast alongside subsidiary and treasury input rather than replacing it
- Technical evaluators who want to assess the APIs from public documentation first: no developer portal is published and the help centre sits behind authentication
How to use Nomentia Cash Flow Forecasting
A typical end-to-end flow, from setup to results.
- Request access through the contact form: there is no pricing page and no online sign-up, so the entry point is the Book a demo request
- Agree the scope and subscription with the vendor, then contract on the General Terms of Agreement and, where personal data is processed, the Data Processing Agreement
- Connect the ERP systems through REST APIs or secure file transfer, using standard connectors and configuration-driven mappings
- Connect the banks and bring in the treasury instruments already managed in Nomentia, so operational and financial flows land in the same forecast
- Set up subsidiary collection with controlled templates, validation rules and submission deadlines
- Configure the forecasting models: choose the source transactions, model, scope and horizon for each use case, or let Auto-select apply the best-performing model
- Let the AI build a reference forecast from historical bank transactions, ERP actuals and past forecasts
- Read the reports comparing manual forecasts, the AI reference forecast and actual transactions
- Freeze forecast versions and run plan-versus-plan and plan-versus-actual analysis to track accuracy over time
- Where the separate Nomentia AI assistant is in use, query the data in natural language inside the application within the logged-in user's own permissions; day-to-day help runs through email, phone from 08:00 to 16:00 (UTC+01:00) and the authenticated help centre
Pros & Cons
Pros
- The AI forecast is positioned as an objective counterpoint to human forecasts rather than a replacement, which keeps subsidiary and treasury judgement in the loop
- Models are isolated per customer: the vendor states they are trained on your history and are not shared across customers
- Forecast accuracy becomes measurable inside the tool through frozen versions and plan-versus-actual comparison; the client KARL MAYER reports a three percent accuracy gain on a complex subsidiary thanks to predictive analytics
- Several ERP systems can run in parallel, with standard connectors and configuration-driven mappings instead of bespoke development in most cases
- Published security certifications: ISO/IEC 27001:2022, ISAE 3402, the SWIFT Customer Security Programme and FSQS-NL
- Unusually complete public contractual documentation: general terms, DPA, technical and organisational measures, a GDPR compliance note and a named subprocessor list, all downloadable
- European hosting on Microsoft Azure, with a primary data centre in the Netherlands and a secondary one in Ireland
Cons
- No public pricing at all: no pricing page, no tiers, not even an order of magnitude, only an invitation to request a custom demo and pricing
- No free trial and no free plan are announced anywhere on the site
- No public API documentation, although REST APIs are explicitly sold, and the help centre sits behind authentication, so little can be assessed before contracting
- No statement anywhere about the languages of the product interface
- Best AI accuracy is said to require around three years of consistent history, which limits the value for young entities
- Enterprise-only entry: no self-service sign-up, so any evaluation runs through a sales cycle
- The company history timeline on the About page exists only as an image, unreadable by screen readers and by search engines, and the single year it displays refers to the Analyste and OpusCapita lineage rather than to Nomentia Oy itself
Pricing & Plans
No price is published. Nomentia operates a contact-sales model: the site carries no pricing page, no rate card and no published amount, and the contact page offers a custom demo and pricing. Neither a free plan nor a free trial is announced, so there is no lowest price point to report in any currency. The only pricing object on the product page is a structured-data offer whose price field holds the literal text Contact for pricing, which is not an amount. The commercial model described in the general terms is a negotiated enterprise subscription, with a subscription fee and a subscription period, but no figure is disclosed. A quotation must therefore be requested from the vendor.
Data, GDPR & hosting
A consolidated view of how Nomentia Cash Flow Forecasting handles your data.
GDPR overview
GDPR implementation is concrete and documented. Privacy Notice version 2.1, updated 30 May 2026, names Nomentia Oy (registration number 2855557-7, Linnoitustie 6 C, 02600 Espoo, Finland) as controller for website and marketing data and as processor for data loaded into the SaaS. It commits explicitly to observing the General Data Protection Regulation (2016/679) and applicable national law. A data protection officer is reachable at privacy@nomentia.com and +358 10 419 5200. Listed rights: access, withdrawal of consent, rectification, objection, restriction, portability and erasure. Transfers outside the EEA rely on standard contractual clauses, and the supervisory authority named is the Office of the Data Protection Ombudsman in Helsinki. A Data Processing Agreement is downloadable in English and Finnish, alongside a GDPR compliance note, technical and organisational measures and a named subprocessor list.
Who owns the data?
Under the General Terms of Agreement dated 23 August 2024, the customer retains all rights to its Customer Data, defined as any data loaded or entered into the service or retrieved from the customer's bank. Nomentia holds only a limited right to use that data in operating the service features for the customer's benefit. All rights to the service itself remain with the supplier's group, so the platform, models and software never pass to the customer with the data. Where Nomentia acts as a processor on the customer's behalf, its obligations are governed by the separate Data Processing Agreement, which also frames what its named subprocessors may do.
Reuse rights
Because the customer keeps all rights to its Customer Data, it can export, reuse and share that data inside or outside the service without asking Nomentia for permission, and the forecasts, versions and reports built from it stay with the customer. Nomentia's own reuse is narrower and stated in the general terms: it may use data included in customer material, and data arising out of handling that material, for testing, development and improvement of the service, provided the data is anonymised and processed under applicable data protection law. On the forecasting module itself, the vendor states that data is used to build forecasts for your organisation only, and that models are trained on your history and are not shared across customers. The separate Nomentia AI assistant is described differently: customer data is not used for model training or reuse there, and the underlying language model is stateless. These are two distinct subsystems and the site does not reconcile the two wordings. No opt-out from model training is documented; what the user does control is which source transactions, models, scopes and horizons feed each forecast.
Data retention & training
Hosting summary
The named subprocessor list states that the Nomentia Cash and Treasury Management and Trezone solutions are hosted and running on the public Microsoft Azure cloud, contracted through Microsoft Ireland Operations Limited in Dublin. The primary data centre is in the Netherlands and the secondary data centre is in Ireland, both inside the EU and the EEA. Elisa Oyj, in Helsinki, supplies data centre and managed IT services for the Nomentia Cash Management solution, with processing located in the EU and EEA, and NetNordic Finland Oy, in Turku, operates the 24/7/365 security operations centre that monitors the infrastructure. The Privacy Notice states that Nomentia aims, where possible, to process personal data within the EU and EEA region. The technical and organisational measures describe professional data centres with physical access control, alarms and video surveillance, encrypted backups with copies moved to a remote site for disaster recovery, and segregation, with personal data processed in dedicated systems not shared with other services or entities. Some subprocessors nonetheless operate outside the EEA under adequacy decisions, standard contractual clauses or the Data Privacy Framework.
Things to keep in mind
Risks and trade-offs to weigh before adopting Nomentia Cash Flow Forecasting.
- An AI reference forecast is persuasive precisely because it looks neutral. The vendor positions it as a counterpoint to human judgement, not a substitute, and treating it as the truth would quietly erode the analytical work of the subsidiaries and treasurers who feed it
- Pricing never appears in public, so no comparison with alternatives is possible without entering a sales process, and no external reference exists against which to check a quote
- The wording on model training differs between modules: the forecasting module trains models on your history without sharing them across customers, while the Nomentia AI assistant states that customer data is not used for training at all. Two subsystems, two statements, worth clarifying contractually for your own use case
- The general terms allow the vendor to use anonymised data drawn from customer material for testing, development and improvement of the service, and no opt-out from model training is documented anywhere
- After termination, the vendor may destroy customer data three months later, and return of the data is offered against reasonable compensation, so the exit should be planned before signing
- Subprocessors can change: notice is given with a right to object, but silence past sixty days counts as acceptance, and some subprocessors process data outside the EEA, in the United Kingdom, Canada and the United States, under adequacy decisions, standard contractual clauses or the Data Privacy Framework
- The help centre and the product documentation sit behind authentication, so nothing can be verified independently before contracting; note too that the displayed support address, support@nomentia.com, differs from the address behind the link, helpdesk@nomentia.com, on three pages and in two languages
Setup & Integrations
Technical difficulty
Moderate, and more an organisational effort than a technical one. The service is cloud-native SaaS, so nothing is installed locally. On the ERP side, initial connectivity and configuration are reported to often take a few hours, with full rollout commonly within one business day depending on scope; standard connectors and configuration-driven mappings limit bespoke development. Exchanges run over REST APIs or secure file transfer in CSV, XML or ISO 20022. The real work is organisational: subsidiary templates, validation rules and deadlines, plus roughly three years of consistent history for the AI. Named implementation partners suggest projects are often assisted.
Deployment
Integrations
Behind Nomentia Cash Flow Forecasting
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Alternatives
Tools that compete with or complement Nomentia Cash Flow Forecasting.
Frequently asked questions
How does Nomentia Cash Flow Forecasting build a forecast?
How does the AI generate a reference forecast?
Does the AI replace forecasts from subsidiaries or from the treasury team?
Is our data used to train models for other customers?
Can a forecast be frozen and its accuracy tracked?
Which ERP systems can be integrated?
Does the module handle several currencies and organisational levels?
How much does it cost?
Where is the data hosted?
Is a Data Processing Agreement available?
Should you pick Nomentia Cash Flow Forecasting?
Nomentia Cash Flow Forecasting is a mature module from a European vendor of real scale: Nomentia Oy serves more than 1,400 customers across Europe from Espoo, Finland, with over 250 employees and seven offices. The forecasting proposition is coherent. Rolling forecasts are assembled from ERP, bank, subsidiary and treasury data in one place, and the AI contribution is framed carefully, as a reference forecast built on the customer's own history that sits alongside human input rather than displacing it, with models the vendor says are not shared across customers. The supporting documentation is a genuine strength and unusually complete for this market. General terms, a data processing agreement, technical and organisational security measures, a GDPR compliance note and a named subprocessor list are all public and downloadable, and the security page publishes ISO/IEC 27001:2022, ISAE 3402, the SWIFT Customer Security Programme and FSQS-NL. Hosting is documented and European: the public Microsoft Azure cloud, with a primary data centre in the Netherlands and a secondary one in Ireland. The blind spots are commercial rather than technical. No price is published in any form. No API documentation is publicly accessible even though REST APIs are sold, and the help centre requires authentication, so a prospective buyer cannot assess the product in depth before entering a sales conversation. No interface language is declared. Around three years of consistent history is recommended for the AI to perform well, which favours mature groups over young entities. For a group treasury already running several ERP systems and collecting forecasts from subsidiaries, this is a serious candidate, and the published security and contractual material makes due diligence unusually straightforward. For anyone who needs to compare prices or test the product before talking to sales, it is not.
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