Why Treasury Systems Matter More as Companies Expand
Managing money in a growing business isn’t simple anymore. As companies expand across countries and currencies, their financial operations become increasingly complex. More accounts, more systems, more data, and often, the same small team trying to keep up.
Many treasuries still rely on spreadsheets and manual checks, which were effective when operations were smaller, but now slow everything down.
Decisions take longer, errors creep in, and leaders lose clear sight of where their money really sits. That’s why more businesses are turning to smarter, automated solutions that bring control, speed, and clarity back to their finances.
Modern treasury systems enable real-time visibility into cash, allowing for faster action and more confident planning, rather than reacting.
One of the people leading this shift is Daniel Kalish, Co-Founder and CEO of Nylos. With a background in finance and technology, he has spent years helping companies bridge the growing gap between data and decision-making.
At Nylos, he’s building AI-native treasury systems that automatically clean, organize, and analyze financial data, while keeping people in charge of every move. His goal is simple: remove the manual noise so treasurers can focus on strategy, not spreadsheets.
In this article, we’ll look at Daniel’s insights on how AI is reshaping treasury systems, why clean data matters most, and how finance teams can adopt AI safely to boost visibility, improve control, and work smarter, not harder.
Why Complexity Outruns Growth and When to Use AI Treasury Systems
When a company doubles in size, its treasury rarely keeps pace. New bank accounts emerge, currencies proliferate, and payments extend across borders. Every new region brings its own rules and timing. Soon, what felt manageable turns into a maze.
The real issue is that the treasury team doesn’t grow at the same rate. The same few people now handle a significantly larger number of transactions, systems, and reports. Mistakes rise, pressure builds, and control slips away.
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Organic Growth vs. Acquisitions
Organic growth happens slowly, so teams can spot problems coming. It’s still tough, but there’s time to adjust. Acquisitions, though, are like plugging in a second company overnight.
Suddenly, there are more banks, vendors, and treasury tools than anyone can keep track of. Merging all that without chaos takes time and structure.
When Treasury Systems Start to Break Down
Early warning signs show when things begin to slip.
- Lack of cash visibility – No one knows exactly where the company’s money is or how much it holds.
- Too much manual work – The team spends days chasing spreadsheets instead of improving forecasts.
- Slow reporting – When management waits a week for updates, decisions start to fall behind.
These gaps affect more than the treasury. Payroll runs late, collections slow down, and confidence drops across departments.
The Real Cost of Poor Cash Visibility
When a company can’t see its cash, it can’t steer its finances. Real-time visibility enables teams to act quickly, delay payments, collect funds more efficiently, or shift funds as needed.
The treasury isn’t just about keeping records. It’s about helping the business grow with control and foresight.
Tracking key numbers, such as cash buffer, DSO, DPO, and FX exposure, provides clarity. When those numbers stay visible and reliable, the treasury becomes not just efficient, but essential.
What’s the Real Difference Between AI-Enabled and AI-Native Treasury Systems?
Most treasury tools claim to use AI, but not all of them truly do. Many older systems were built years ago, then migrated online and enhanced with new features, such as chat interfaces.
They appear modern, but the data inside still operates using outdated logic. The system records what happens but doesn’t really understand it.
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How AI-Native Systems Actually Work
An AI-native treasury system works differently. It’s designed to learn from every transaction and improve over time.
Each part of the system, whether it’s classifying data, forecasting, or analyzing cash, feeds information back into itself. The next time a similar situation appears, it will already know what to do.
The main difference is clear.
- AI-enabled systems only record and show information.
- AI-native systems interpret the data, identify trends, and suggest the next actions to take.
That’s why AI-native platforms are referred to as systems of action rather than systems of record. They don’t stop at showing numbers; they help you decide what to do with them.
How Intelligent Agents Work Together
AI-native systems use several smart agents that work like a small team. One cleans and structures data. Another tracks patterns and finds insights. A third forecasts cash flow and liquidity. They all communicate with each other in real-time, creating a seamless flow instead of separate, manual steps.
Why Clean Data Is the Real Foundation
Even the best AI can’t work without clean data. That’s why treasury systems must remain connected to banks, ERPs, and accounting tools to ensure data accuracy and up-to-date information.
When the data is structured and clear, the system gives better insights and reasoning. AI doesn’t replace people, it supports them. It helps treasurers act faster and make smarter, more confident decisions.
How AI Treasury Systems Improve Decisions And Liquidity Risk Control
AI in the treasury strengthens decision-making without removing human control. Treasurers still make the key calls, and AI clears the grunt work.
It sorts data, matches transactions, and generates reports, allowing teams to focus on results. That shift saves time and reduces errors, which boosts confidence across the finance team.
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Smarter Cash and Liquidity Management
A major advancement in modern treasury tools is the liquidity optimization agent. It tracks accounts, balances, and policies all day. The agent checks:
- Balance thresholds and cash buffers
- Counterparty exposure and liquidity limits
- Policy rules for how and where cash should move
When an issue or opportunity arises, the system flags it with relevant context. It might suggest moving idle funds into higher-yield accounts. It might propose delaying a payment to ease short-term pressure. Instead of reacting late, teams act early with clear options.
Faster Implementation and Seamless Connectivity
Traditional treasury systems take months to integrate with banks and ERPs. AI-native platforms change that. They connect through secure user access and start pulling data within days. You get real-time views faster, and you start improving forecasts sooner. That means a quicker path from setup to value.
Key Advantages of AI-Native Treasury Systems
AI brings flexibility that legacy tools can’t match. Treasurers can:
- Re-tag and organize data anytime without technical help
- Adjust structures and reporting instantly
- Manage related functions like cash accounting and collections in one place
Keeping Treasury Safe and Informed
The treasury is risk-averse by design, and AI aligns with that mindset. It reduces uncertainty through constant checks, clean data, and transparent logic.
People stay in charge, while the system supplies timely signals and reasoning. Decisions get faster and sharper, and blind spots shrink. Ultimately, you can better protect liquidity and support growth with steady control.
How To Adopt AI Treasury Systems Safely and Prove Real ROI
The Treasury’s goal has always been clear: protect cash and reduce risk. When AI enters that space, it should make things safer, not uncertain. The right tools don’t replace people; they help them work faster and with more confidence.
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Adopting AI with Caution and Control
The best way to introduce AI in the treasury is to do so step by step. Teams should run it alongside their current setup, like Excel, until the numbers match for several weeks. This builds trust in the system before full adoption.
Treasurers still stay in charge. They review every recommendation, validate insights, and decide what to act on.
A reliable AI tool must clearly explain each suggestion, indicate the source of the data, and outline the calculation process used to derive the result. That level of visibility makes the system dependable, not risky.
Where the Real ROI Comes From
AI delivers results fast once it’s properly set up. The return on investment usually appears in three key areas:
- Productivity Gains: Within the first month, treasury teams connect their banks and ERPs. Manual tagging and data chasing disappear. Instead of spending hours collecting data, teams use that time to improve performance.
- Better Control: Automated updates enable teams to refresh reports multiple times a day, rather than waiting a week. This constant visibility improves accuracy and prevents errors before they happen.
- Higher Cash Value: AI identifies idle or trapped cash, reduces borrowing, and optimizes FX or fee management. Even small adjustments can lead to significant savings and a stronger cash position.
Turning Treasury into a Strategic Force
AI doesn’t just improve operations; it strengthens collaboration. When the treasury shares accurate, AI-driven forecasts with accounting, collections, and payments teams, decisions align faster.
The result is improved liquidity, smoother cash flow, and a treasury team that is seen as a key strategic partner across the business.
Conclusion
Modern treasury systems aren’t just tools for reporting anymore. They’re becoming intelligent partners that help businesses manage cash, control risk, and make faster, more informed decisions.
As companies grow, so does complexity, and that’s where AI makes a real difference. It automates repetitive work, keeps data clean, and gives treasurers the time and insight to focus on strategy instead of managing spreadsheets.
AI-native treasury systems work smarter because they’re built to learn from every transaction. They don’t just store information; they understand it, analyze it, and suggest the next course of action.
Still, people stay in control. Treasurers review every recommendation, confirm the logic, and act with confidence. It’s a combination of human judgment and machine precision.
The real strength of these systems lies in striking a balance between speed and safety. They connect to banks and ERPs more quickly, enhance forecasting accuracy, and safeguard liquidity with fewer blind spots.
With clean data and transparent reasoning, decisions become faster and safer. Adopting AI isn’t about replacing the treasury team. It’s about giving them better tools to act with clarity and purpose.
When that happens, treasury stops being a back-office function and becomes a driving force behind growth. That’s the true value of modern treasury systems, turning complexity into control and insight into action.
FAQs
What are Treasury Systems used for in a business?
Treasury systems enable companies to effectively manage their cash, payments, and financial risks. They show where the money is, how it’s moving, and help leaders make quick, informed financial decisions.
Why are modern Treasury Systems replacing Excel-based setups?
Excel works for small teams but fails as companies grow. Treasury systems automate repetitive tasks, reduce errors, and provide real-time updates that spreadsheets can’t match.
How do Treasury Systems support global businesses?
They centralize data from multiple countries, currencies, and banks. This helps teams view everything in one place and act fast without juggling separate systems.
Can Treasury Systems integrate with existing accounting tools?
Yes, most connect directly with ERPs, banks, and payment tools. This ensures that all financial data remains accurate and is updated automatically.
What’s the biggest challenge when adopting new Treasury Systems?
The main challenge is data quality. If information isn’t clean or structured, even advanced systems give poor insights.
