This article is written by Nomentia

Why are manual treasury processes expensive?

Manual treasury processes become expensive because they require recurring effort to collect balances, prepare payment files, update forecasts, check approvals, and reconcile data. Even when each task seems manageable, the combined impact can reduce efficiency, slow down decision-making, and increase operational risk.

Treasury teams are used to making imperfect systems work.

A spreadsheet here. A bank portal there. A local ERP export from one entity, a payment file from another, and a cash forecast that still depends on email updates from the business. None of these workarounds may look dramatic on their own. In many organisations, they are even seen as normal.

The problem is that “normal” can become expensive.

Manual treasury operations rarely create one large, visible cost line. Instead, they create a pattern of hidden costs: time spent collecting data, delays in decision-making, duplicated effort, payment exceptions, outdated forecasts, missed visibility, and control gaps that only become urgent when something goes wrong.

That is why treasury automation ROI should not only be discussed as a technology question. It is also an operating model question. How much time does treasury spend managing the process instead of managing cash, liquidity, payments, and risk?

Why manual treasury work is difficult to measure

The cost of manual work is often underestimated because it is distributed across people, entities, systems, and routines.

A treasury analyst may spend hours preparing a daily cash position. A regional finance team may manually upload payment files. Another person may validate bank data, check approvals, update forecasts, or investigate why one bank statement does not match the expected format.

Each task may be manageable. Combined, they create a significant operational burden.

This is also why many teams struggle to build a cash forecasting business case. The value of better forecasting is not limited to “faster reporting”. It is the value of better decisions: knowing earlier where liquidity is needed, reducing dependency on outdated data, improving confidence in funding decisions, and giving leadership a clearer view of what may happen next.

External research points in the same direction. PwC’s 2025 Global Treasury Survey notes that treasury teams are under pressure to improve cash visibility, cost efficiency, and risk management, while leading organisations increasingly adopt real-time liquidity tools, AI-enhanced forecasting, and centralised payment models. HSBC also highlights that cash flow forecasting has remained a key treasury priority, reflecting the need for precise and timely forecasts in a volatile environment.

In other words, manual treasury processes are not only inefficient. They can slow down the organisation’s ability to respond.

The cost of fragmented cash visibility

Cash visibility is one of the clearest examples of hidden treasury cost.

When balances are collected manually across banks, accounts, currencies, and entities, treasury may technically have the data, but not necessarily in time to act on it. The team may know yesterday’s position, but not today’s. It may have a consolidated view, but only after several people have updated files, checked bank portals, and reconciled different formats.

That delay matters.

Without timely visibility, companies may keep too much cash idle in one place while borrowing elsewhere. They may struggle to identify trapped cash. They may make liquidity decisions based on incomplete information. They may also spend valuable time explaining numbers instead of improving them.

Nomentia positions its Smart Treasury Suite around visibility, control, and predictability across payments, cash, liquidity, and risk, integrating with ERPs, banks, and other systems. For companies operating across multiple banks and entities, that integration layer is not just technical infrastructure. It is the foundation for turning fragmented data into usable treasury insight.

The cost of manual payments

Payments are another area where manual processes can appear cheaper than they really are.

At first glance, uploading files through bank portals or managing payments across local workflows may seem acceptable. The team knows the process. The banks are connected somehow. Payments are executed. Work continues.

But payment operations carry a high cost when they depend on scattered portals, inconsistent approvals, manual file handling, and local exceptions.

The hidden costs include time spent preparing and checking payment files, resolving format issues, validating approvals, tracking payment statuses, and answering questions from subsidiaries, AP teams, banks, and auditors. More importantly, weak payment control can increase exposure to duplicate payments, missed cut-offs, fraud attempts, and compliance issues.

This is where payment automation benefits become easier to explain. Automation is not only about faster payment execution. It is about standardising the process, improving traceability, reducing manual intervention, and making payment control easier to prove.

The cost of unreliable forecasting

Forecasting is often where manual treasury processes become most visible to leadership.

The CFO does not necessarily see how many files were collected, how many emails were sent, or how many adjustments treasury made before the forecast was ready. But the CFO does see when the forecast is late, when confidence is low, or when the numbers change without a clear explanation.

A manual cash forecast can still be useful. Many experienced treasury teams are excellent at working around incomplete data. But as the business grows, expands into new markets, adds banks, or inherits systems through acquisitions, the limits become harder to ignore.

Forecasting depends on data quality, timing, ownership, and repeatability. If treasury spends too much time gathering inputs, it has less time to analyse drivers, challenge assumptions, and model scenarios. A forecast that takes days to prepare may already be outdated when it reaches decision-makers.

This is why the business case for treasury automation should include both time savings and decision quality. Faster data collection is valuable. But the larger value often comes from giving treasury more time to interpret what the numbers mean.

The cost of controls that rely on people remembering the process

Manual controls are often built around expertise. The team knows which approvals are needed, which files need checking, which bank deadlines matter, and which exceptions require escalation.

That works until complexity increases.

As more entities, banks, users, and payment types are added, control becomes harder to manage consistently. Processes may differ across countries. Approval rules sit outside the system. Audit trails may require manual reconstruction. Exceptions depend on individual knowledge rather than embedded workflows.

In a stable environment, this may go unnoticed. During growth, restructuring, audit, staff changes, or periods of financial pressure, it becomes a risk.

The Nomentia Treasury Trends Report 2026 describes treasury teams facing pressure to deliver real-time insights, stronger controls, and more strategic input, often while dealing with fragmented systems and limited IT support. The report is based on 384 treasury and finance leaders across the Nordics, DACH, Benelux, and the UK.

That is the reality many treasury teams recognise: expectations are rising faster than operational capacity.

How to think about treasury automation ROI

A strong treasury automation ROI discussion should not begin with software features. It should begin with operational impact.

• Where is treasury losing time today?
• Which manual tasks are repeated every day, week, or month?
• Where do payment processes create avoidable risk?
• How much effort goes into collecting and validating data?
• Which decisions are delayed because cash visibility or forecasts are not ready?

From there, TMS cost savings become easier to frame. The value may come from fewer manual hours, lower operational risk, more efficient payment execution, improved cash visibility, reduced dependency on spreadsheets, or stronger audit readiness.

The most useful business case is not a generic promise that automation saves money. It is a structured estimate of where the organisation currently loses time and where better treasury processes could create measurable improvement.

Also Read

• How to improve cash flow forecast accuracy with AI?
• Top 8 treasury management solutions
• Insights from the Nomentia Treasury Summit 2024: Navigating the dynamics of modern treasury management
• Starting a new job in Treasury: Best practices and expert advice
• How does physical cash pooling & target balancing work with a TMS?
• Implementing a Global Enterprise-scale Payment Hub: The Challenges and Business Impacts
• Treasury Technology Trends in 2024: How APIs, AI, and RPA Change the Treasury Landscape?
• A deep dive: Simplifying guarantee management for treasury & finance

Join our Treasury Community

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 Nomentia

Your cash flow forecast is lying to you. Not on purpose, but it’s wrong—probably by a lot. Spreadsheets lull you into a false sense of control, but the numbers lie. They miss shifts in spending, overlook delayed payments, and crumble the moment reality deviates from last month’s assumptions. By the time the cracks show, you’re already scrambling—plugging holes, chasing down cash, and making desperate decisions.

The experts:

Why “close enough” isn’t always good enough in cash flow forecasting

A cash flow forecast that’s even slightly off can send your business into a tailspin. As Hubert Rappold puts it: “Small deviations in cash flow forecasts can lead to big financial risks.” Underestimate expenses, and you’re suddenly short on cash when payroll hits. Overestimate revenue, and you’re making spending decisions based on money that isn’t actually there. “Basing your decision on a forecast that is substantially off; you might end up making decisions based on inaccurate data—like borrowing unnecessarily or mismanaging liquidity.” The further your forecast drifts from reality, the riskier every financial move becomes. And in a world where margins are tight, customers pay late and surprises lurk around every corner; imprecise forecasting isn’t just an inconvenience but a liability.

What is cash flow forecasting, really?

At its core, cash flow forecasting is just this: predicting how much money will move in and out of your business over a given period. It’s not about spreadsheets or fancy formulas but knowing, with as much certainty as possible, whether you’ll have enough cash to cover what’s coming.

Why traditional forecasting falls apart? 

Most businesses, big and small, still rely on outdated tools and methods that weren’t built for today’s financial landscape. Here’s why they fail:

• Excel is static – Spreadsheets don’t update themselves. Every forecast relies on manual inputs, meaning errors, omissions, and outdated data pile up fast.
• Assumptions age poorly – Traditional models rely too much on past data, ignoring real-time shifts like late payments, economic changes, or unexpected expenses.
• It’s a time sink – Forecasting manually eats up hours (or days), and by the time you’re done, the numbers may already be obsolete.
• Human error is inevitable – Even the best finance teams make mistakes. One wrong formula or missing invoice can throw everything off.
• No real-time adjustments – A single unexpected expense or delayed payment can make a forecast useless, but Excel won’t flag the problem until it’s too late.
• Data lives in silos – Bank accounts, invoices, and ERPs all hold key pieces of the puzzle, but pulling them together manually is slow, painful, and prone to mistakes.
• Key person dependency – Many companies rely on one finance expert who “knows the spreadsheet.” If they leave, get sick, or make a mistake, the entire system can fall apart.

Let’s be clear—treasurers and finance managers are some of the most skilled problem-solvers in any business. They know how to fine-tune their forecasts, clean up messy data, and make Excel do what they need. But time is limited, and expectations keep rising. The demand for instant, up-to-date cash visibility means they can only do so much, no matter how skilled they are.

“Excel-based forecasting worked perfectly fine when business environments were more predictable,” explains Johannes Pöschl. “But today, cash flows are influenced by a web of factors—seasonality, economic shifts, even supplier behavior. Static spreadsheets just can’t keep up with that complexity.”

And here’s the real danger: many forecasts depend entirely on the person who built them. If that expert is unavailable—whether they leave, take a vacation, or simply get swamped—no one else knows exactly how their formulas and models work. That’s a terrifying prospect for any company relying on accurate cash flow predictions.

This is where AI-driven automation changes the game. Instead of a fragile, human-dependent system, businesses get a dynamic, always-updating forecast that adjusts in real time. It doesn’t replace the finance team—it gives them superpowers. Let’s take a look at:

How AI enhances cash forecasting accuracy?

For many, forecasting cash flow, is a reactive scramble. No wonder, when traditional forecasting relies on static models and best guesses. Implementing AI into your forecasting you can go beyond static formulas and outdated assumptions. Not just automate your forecasting, but make it smarter, spot hidden patterns and continuously refines projections.

“AI forecasting can lead to more objective forecasts, leaving behind the impact of regional optimism biases in forecasting,” says Johannes. “They can also incorporate resource prices and estimate their effects on supplier prices that traditional models or treasurers might miss.”

As Hubert adds: “AI can automatically classify transactions from bank statements, showing finance teams exactly where cash flow discrepancies are coming from—late customer payments, unexpected supplier costs, or seasonal trends. That kind of insight is invaluable.”

Here’s how it stacks up against traditional methods:

Traditional forecasting methods	Challenges for forecast accuracy	AI in forecasting: Key techniques for accuracy improvement
Manual data entry & spreadsheets	Prone to human error, delays, and data inconsistencies	Automated connectivity & forecast reconciliation: integrating real-time bank & ERP data to eliminate errors and update forecasts dynamically.
Rule-based forecasting (fixed models)	Rigid assumptions fail to capture real-world volatility	Machine learning & pattern recognition: AI-powered forecasting learns from past errors and adapts dynamically to new trends.
Historical trend extrapolation	Fails to account for sudden economic shifts, external shocks	Multi-variable analysis: AI-driven forecasting incorporates economic indicators, market trends, and business-specific variables.
Limited scenario planning	Forecasts become unreliable in times of uncertainty	Risk simulations & stress tests: AI forecasting can run multiple scenarios to assess financial resilience under various conditions.
Static payment terms-based Cash flow predictions	Overlooks customer-specific behavior, which leads to inaccurate receivables forecasts	Dynamic payment behavior predictions: AI forecasts can analyze past payment trends to predict late payments with higher accuracy.
Isolated departmental forecasting	Fragmented cash flow data across finance, treasury, and operations	Automated connectivity: Forecasts integrate multiple data sources for a holistic, real-time view of liquidity.
Lack of external market consideration	Ignores macroeconomic trends, FX rates, inflation, and geopolitical risks	Sentiment & market trend analysis: AI-supported forecasts process can incorporate market sentiment indices, GDP forecasts, interest rates and other data affecting the business environment to refine forecasts.
Reactive forecast adjustments	Adjustments are made after discrepancies occur, not proactively	Self-learning algorithms:  continuous refinement of forecasts based on real-time variance analysis.
Delayed cash flow reconciliation	Forecasts deviate from reality due to mismatches in receivables/payables data.	Automated invoice matching & forecast reconciliation: reconciling forecasts against actual bank transactions in real-time.

AI in cash forecasting: Use case examples

“Take something as simple as public holidays,” says Johannes. “They affect cash flows differently depending on the industry and country, and AI can model these effects automatically. Over time, the system refines itself, making forecasts even more accurate.”

Hubert gives another example: “AI can analyze past customer payment behaviors to refine expected due dates. But even simple logic—like applying Days Sales Outstanding (DSO) metrics—can significantly improve accuracy, especially for short-term forecasts.”

Let’s consider:

• Pattern recognition to catch supplier payment delays: An industrial equipment manufacturer kept running into unexpected Q4 cash shortfalls. The culprit? Subsidiaries in Asia were consistently paying suppliers 15–20 days late, but traditional models failed to flag the pattern. The result: a €10M gap, covered by borrowing at 5% interest—wasting €125K per quarter. AI-powered forecasting caught the recurring delays, allowing the treasury to adjust projections and secure credit lines early, saving €500K a year.
• Predicting late payments to stop cash flow gaps: A software company with €50M in receivables struggled with late payments from enterprise clients in North America and Asia. Customers paid an average of 12 days late, forcing treasury to rely on credit lines at 4% interest—burning €65K every month. Using AI to analyze payment behaviors, allowed the treasury to predict which clients would delay, and helped them follow up proactively. Cutting late payments by half saved €390K per year in financing costs.
• Market sentiment analysis to see a demand drop before it happens: An automotive parts supplier was blindsided by a slowdown in US and UK car manufacturing. Depending on traditional forecasting would have allowed them to miss the warning signs, leaving the company stuck with €30M in excess inventory—costing €3M per year in storage. Perhaps, the right person at the right place at the right time would have caught the demand drop and acted accordingly, but they weren’t available. AI assistance, however, had allowed the treasury to detect a downturn in auto sales three months in advance. Because the treasury acted early, they were able to reduce inventory buildup and avoid €1.4M in storage and emergency financing costs.

The Treasurer’s dilemma: Drowning in Spreadsheets, starved for time

Every morning, the Treasurer of a globally operating business opened the same monster Excel file—a tangled web of formulas, manual inputs, and linked sheets that somehow held the key to the company’s cash flow. Keeping it updated was a full-time job. Data trickled in from subsidiaries across time zones, bank accounts were scattered across multiple institutions, and assumptions had to be constantly tweaked. Forecasting was supposed to provide clarity, but instead, it felt like a high-stakes guessing game.

The demands from leadership kept growing: More accuracy. More real-time visibility. More risk mitigation. But with what? The Treasurer had already pushed Excel to its limits, building an intricate system that only they truly understood. When the CFO needed answers, they delivered—but not without late nights, countless emails chasing missing numbers, and a nagging fear that one small mistake could throw everything off.

Then came the talk about AI-powered forecasting.

It sounded promising—automation, real-time data analysis, better predictions. But there was also an unspoken worry: What if this replaces me? What if all my expertise, my hard-earned knowledge, gets sidelined by software?

And yet, the bigger fear wasn’t AI. It was this. This endless cycle of manual work, desperate fixes, and hoping that when leadership asked for insights, the numbers weren’t off—because if they were, it would be their name on the line. Worse still, if they ever stepped away, who else would even know how to keep this monster running?

That’s when the real question hit: What’s the bigger risk—adopting AI or continuing like this? Spending hours babysitting spreadsheets?

The reality hit. So they ran the numbers. Even a small boost in forecast accuracy would cut emergency borrowing and save more than enough to justify the investment. The business case was clear. It was time to kill the spreadsheet before the spreadsheet killed them.

“A lot of treasurers worry that AI will replace them,” Johannes notes. “But in reality, AI is just a tool—it provides forecasts, but treasurers still bring the expertise to validate and interpret them. The most successful teams use AI to eliminate tedious manual work, freeing themselves to focus on strategy.”

Hubert agrees: “If you set up AI-driven forecasting right, you don’t just improve accuracy—you make life easier. Treasurers get instant feedback, can compare past forecasts to actuals, and refine their approach over time. The goal isn’t to replace them; it’s to give them better tools.”

Conclusion: Forecast or guess?

You wouldn’t steer a company based on gut feelings alone—so why accept guesswork in cash flow forecasting? AI isn’t a magic fix, but it’s the difference between informed decisions and financial blind spots. The real risk isn’t AI—it’s sticking to spreadsheets while the world moves forward.

Also Read

• The hidden cost of manual treasury operations
• Top 8 treasury management solutions
• Insights from the Nomentia Treasury Summit 2024: Navigating the dynamics of modern treasury management
• Starting a new job in Treasury: Best practices and expert advice
• How does physical cash pooling & target balancing work with a TMS?
• Implementing a Global Enterprise-scale Payment Hub: The Challenges and Business Impacts
• Treasury Technology Trends in 2024: How APIs, AI, and RPA Change the Treasury Landscape?
• A deep dive: Simplifying guarantee management for treasury & finance

Join our Treasury Community

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 Nomentia

What should companies consider when selecting a treasury management solution?

Evaluate how well the solution integrates with your ERP and banking systems, supports real-time liquidity visibility, and automates forecasting and payments. Modern platforms should offer API connectivity, strong compliance controls, and scalable modules that adapt to the company’s growth and complexity.

Treasury teams are under fire. Cash is expensive, FX volatility won’t quit, banks are charging more for less, and regulators keep moving the goalposts. Meanwhile, without dedicated treasury management software, outdated systems and spreadsheet chaos make it harder than ever to see where the money actually is—let alone manage it effectively.  

The result? Missed opportunities, unexpected risks, and wasted time on manual work that should have been automated years ago. Treasurers need real-time visibility, seamless payments, smarter forecasting, and ironclad compliance—but with so many options on the market, choosing the right system is a minefield.  

Should you go all in on a full Treasury Management System (TMS) to centralize everything, or is it smarter to build a custom tech stack with best-in-class treasury management solutions for payments, forecasting, and risk management?  

Let’s take a look at which approach makes the most sense for your business. But first: 

What is a treasury management solution?  

A treasury management solution is a software solution that helps organizations automate, manage, and optimize their financial operations, including cash management, liquidity forecasting, risk management, payments, and compliance. It integrates with banking systems and ERPs and helps companies keep track of their cash, pay bills on time, move money where it’s needed, and avoid financial risks—all in one place, without the headaches of manual tracking. 

Benefits of treasury management software solution  

1. Improved cash flow optimization
   • Ensures businesses always have enough cash to cover daily expenses while minimizing idle funds. 
   • Helps forecast future cash needs to prevent liquidity shortages or excess reserves. 
2. Stronger working capital management
   • Enhances accounts receivable (AR) and accounts payable (AP) processes for timely collections and payments. 
   • Optimizes inventory levels to avoid overstocking or shortages, maintaining financial balance. 
3. Better financial decision-making
   • Provides real-time financial data for more informed budgeting, investment, and cost-cutting decisions. 
   • Reduces financial risks by offering insights into market trends and company performance. 
4. Efficient bank relationship management
   • Centralizes management of multiple bank accounts for better visibility and control. 
   • Monitors fees and transaction costs to negotiate better banking terms. Strengthens security by managing access to company funds. 
5. Seamless payments & reconciliation
   • Automates payment processes to reduce errors and delays. 
   • Matches incoming payments with invoices to improve accuracy and financial reporting. 
6. Optimized Interest rate & credit facility management
   • Tracks borrowing costs to minimize interest expenses. 
   • Ensures credit lines are used efficiently, preventing unnecessary debt accumulation. 
7. Enhanced compliance & document management
   • Stores treasury-related contracts, agreements, and compliance records in one secure location. 
   • Helps businesses stay compliant with financial regulations, reducing legal risks. 
8. Integration with ERP & accounting systems
   • Syncs financial data across platforms to maintain accurate and up-to-date records. 
   • Reduces manual data entry, saving time and minimizing errors. 

Key features of treasury management solution  

Feature category	Description
FX & interest rate risk management	Automated FX exposure tracking across subsidiaries    Multi-currency cash visibility in real-time    Hedging and risk analytics with scenario analysis    Scenario analysis to assess interest rate impacts    Covenant compliance monitoring for financial ratios
Liquidity & cash management	Real-time cash positioning across global accounts    Cash pooling and sweeping for optimized liquidity    AI-driven forecasting for improved accuracy    Centralized treasury management for in-house banking
Cash flow forecasting & planning	AI and machine learning for enhanced forecasting accuracy    Scenario planning and stress testing    Automated data integration from ERPs, banks, and financial platforms    Analytics-driven cash flow lending assessments
Bank connectivity & payments	Multi-bank connectivity via APIs and SWIFT    Automated bank fee analysis and reporting    Centralized payments with fraud detection tools    Secure payments and bank reconciliation
Debt & investment management	Debt and investment tracking with real-time updates    Loan portfolio management and refinancing insights    Support for alternative funding option management
Regulatory compliance & audit controls	Automated compliance monitoring (AML, KYC, tax)    Audit trails and regulatory reporting    Intercompany loan tracking for transfer pricing compliance    Transfer pricing and tax reporting for compliance
Intercompany financing & netting	Automated intercompany netting to reduce costs    Centralized treasury management for internal banking operations    – Intercompany forecast reconciliation
Technology, cybersecurity & integration	Cloud-based access with mobile support    Seamless integration with ERP, accounting, and payment systems    Advanced cybersecurity and fraud detection tools

Top 8 treasury management solutions

• Nomentia: Nomentia is a modular, cloud-based TMS designed for mid-sized and large enterprises. It specializes in cash and liquidity management, payments, bank connectivity, and fraud prevention. 
• Kyriba: Kyriba is a global cloud-based TMS focused on cash management, liquidity planning, risk management, and payments automation. It is widely used by global enterprises. 
• TIS: TIS is a specialized cloud-based treasury and payments solution focused on global bank connectivity, payment automation, and compliance. 
• Gtreasury: GTreasury is a comprehensive TMS with strong capabilities in cash, risk, payments, and accounting. It caters to businesses looking for an all-in-one treasury solution. 
• SAP: SAP Treasury is a fully integrated TMS within SAP ERP, offering advanced treasury functions, risk management, and financial analytics. 
• ION Group: ION Group offers enterprise-grade treasury solutions with a focus on automation, analytics, and risk management for complex treasury operations. 
• Serrala: Serrala is a finance and treasury automation platform offering solutions for cash management, payments, and risk control. 
• Treasury Systems: Treasury Systems is a Nordic-focused TMS providing cash, risk, and payments management for mid-sized and large businesses. 

Top treasury management systems & software: Key features, strengths, considerations, best for

Nomentia 

Nomentia is a flexible and modular cloud-based Treasury Management System designed for mid-sized and large enterprises looking for centralized cash management and payment automation. Unlike some all-in-one TMS solutions, Nomentia offers modular functionality, allowing companies to select and implement only the features they need. The system focuses on bank connectivity, liquidity forecasting, cash flow visibility, and fraud prevention. With strong integration capabilities, Nomentia easily connects to multiple ERP systems, banks, and financial platforms. 

Key features	Strengths	Considerations	Best for
Multi-bank connectivity for global cash visibility Automated cash flow forecasting and liquidity management Centralized payment processing with fraud prevention FX risk management and in-house banking tools ERP and financial system integration	Highly modular, so companies only pay for what they need  Strong cash visibility & bank connectivity features  Quick implementation compared to some enterprise solution	Limited risk management capabilities for advanced FX and derivatives  Requires multiple modules to cover all treasury functions	Mid-market and large multinational companies  Businesses needing a modular approach to treasury management  Companies focusing on cash visibility and payments automation

Kyriba 

Kyriba is one of the most comprehensive cloud-based TMS platforms, offering a broad set of treasury, risk, and liquidity management solutions for large multinational corporations. The system is known for its strong forecasting features, real-time cash visibility, and integrated risk management tools. Kyriba also provides robust payments processing, fraud prevention, and regulatory compliance features, making it ideal for businesses needing deep automation and global treasury centralization.

Key features	Strengths	Considerations	Best for
Liquidity and working capital management with automated cash pooling  Centralized payments hub with fraud detection and regulatory compliance  FX and interest rate risk management with hedging tools  APIs for seamless ERP and banking integration	Comprehensive treasury functionality in a single platform  Advanced analytics for forecasting and risk  Global support for multi-currency, multi-entity operations	Can be complex and costly for smaller businesses  Longer implementation time due to extensive features	Large multinational enterprises with complex treasury needs  Organizations looking for AI-driven forecasting and automation  Companies needing advanced FX and liquidity management

TIS 

TIS (Treasury Intelligence Solutions) is a specialized cloud-based treasury and payments solution focusing on bank connectivity, centralized payment processing, and compliance monitoring. Unlike full-scale TMS platforms, TIS is designed to enhance payment workflows, fraud detection, and cash visibility without replacing core financial systems like ERPs. This makes it a strong choice for businesses with high payment volumes across multiple banks that need better automation and security. 

Key features	Strengths	Considerations	Best for
Centralized payment processing with multi-bank connectivity  Real-time cash visibility across global banking partners  Fraud detection and compliance tools for payments  API-based integration with ERPs and financial platforms	Robust payment hub for large-scale transactions  Strong security and fraud prevention features  Quick to deploy with minimal disruption to existing systems	Limited financial risk management and hedging tools  Not a full-fledged TMS—focused mainly on payments and bank connectivity es	Companies with high transaction volumes and multiple banking partners  Businesses prioritizing secure, compliant payments  Organizations looking for a payment-focused solution rather than full a TMS

GTreasury 

GTreasury is an all-in-one TMS providing strong cash management, risk mitigation, and financial automation. It is widely used by mid-sized and large enterprises that need better cash visibility, centralized payments, and FX risk management. GTreasury combines automated cash positioning, forecasting, and hedge accounting, making it a versatile choice for companies looking to reduce manual treasury work. 

Key features	Strengths	Considerations	Best for
Real-time cash positioning and forecasting  Automated payments and bank integration  FX and interest rate risk management  Hedge accounting and financial compliance reporting	Well-balanced between cash, payments, and risk management  User-friendly interface with customizable dashboards  Good compliance and hedge accounting tools	Implementation can take time depending on company needs  Customization requires additional configuration	Mid-sized and large multinational companies  Businesses managing FX exposure and liquidity risk  Organizations seeking end-to-end treasury automation

SAP 

SAP Treasury is a fully integrated TMS within the SAP ERP ecosystem, designed for large enterprises that require advanced treasury, risk, and liquidity management. It is best for companies already using SAP ERP, as it seamlessly connects with financial modules and provides real-time cash, risk, and payments tracking. 

Key features	Strengths	Considerations	Best for
Real-time liquidity and risk monitoring  FX risk and hedge management  Automated payments and bank communication  Full ERP integration with SAP finance and accounting	Deep integration with SAP financial modules  Strong compliance, risk management, and audit capabilities  Highly scalable for global enterprises	Best suited for SAP users—integration with non-SAP systems can be difficult  High implementation costs and complexity	Large enterprises using SAP ERP  Companies needing deep financial integration and regulatory compliance  Businesses with complex treasury and risk management requirements

ION Group 

ION Group provides enterprise-level TMS solutions tailored for complex financial operations. It is widely used by large multinational corporations, financial institutions, and trading firms for automated treasury workflows, risk hedging, and advanced trading analytics. 

Key features	Strengths	Considerations	Best for
Cash and liquidity management  Enterprise-wide risk management and hedging  High-frequency trading and derivatives management  AI-driven decision support and analytics	Highly scalable for global enterprises  Best-in-class derivatives and FX risk management  Deep automation and analytics	Very complex and costly—best for large institutions  Requires dedicated treasury and finance teams	Global enterprises and financial institutions  Companies with complex derivatives and FX hedging needs  Organizations needing deep analytics and automation

Serrala

Serrala offers a modular, cloud-based treasury and financial automation platform, focusing on payments, cash visibility, and risk management. It’s widely used by mid-sized and large enterprises that want to automate global payments, gain real-time cash insights, and ensure regulatory compliance. Serrala integrates well with SAP and other ERPs, making it a strong choice for companies looking for embedded treasury automation. 

Key features	Strengths	Considerations	Best for
Global cash visibility and forecasting  Automated payments and fraud detection  Bank connectivity and reconciliation tools  FX and liquidity risk management  Seamless ERP (especially SAP) integration	Strong payment automation and fraud prevention  Deep integration with SAP for treasury and finance  Modular approach, so companies can scale features as needed	Best suited for SAP users—integration with non-SAP ERPs may require customization  Not as feature-rich in financial risk management compared to enterprise-focused TMS	Companies looking for a treasury solution embedded within SAP  Organizations focused on payments automation and fraud prevention  Mid-sized to large enterprises needing scalable treasury modules

Treasury systems

Treasury Systems is a Nordic-based TMS designed for mid-market and large corporations looking for a user-friendly, cloud-based treasury platform. It covers the core treasury functions, including cash management, FX risk, payments, and liquidity forecasting, with a focus on automation and streamlined workflows. 

Key features	Strengths	Considerations	Best for
Cash and liquidity management  FX and interest rate risk management  Automated payments and reconciliation  Bank connectivity and in-house banking  Regulatory compliance tools	Straightforward and easy-to-use interface  Good automation capabilities for mid-sized firms  Strong FX and risk management tools	Less recognized globally compared to Kyriba or SAP Treasury  May not scale as well for very large, multinational corporations	Mid-market companies with multi-currency treasury needs  Businesses looking for a simple, effective TMS with strong automation  Companies managing FX risk and liquidity across regions

The best treasury management solution for you?  

Treasury teams in don’t have the luxury of trial and error. Missed FX hedges, slow payments, poor cash visibility—these things add up fast. Cash is tight, risks are high, and the wrong system can slow you down instead of making life easier. Whether you go for a full TMS or build your own stack with best-in-class tools, the goal is the same: centralize, automate, and get real-time control over your cash.  

The real question isn’t whether you need a treasury management solution. It’s how much longer you can afford to go without the right one.  

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