New tools and techniques, including AI and ML, are helping treasurers optimize cash flow and give them a greater role in strategic business decision-making.
Not long ago, corporate treasurer—the highest position in any company’s green corps—was about the last position most observers would label as strategic. While the job has always had a strong risk management component, the basic task was simple: ensure the company has cash available where and when it is needed.
Not anymore. Today, the corporate treasury team plays a critical role in helping companies navigate a business environment full of economic uncertainty, geopolitical risks, regulatory changes, trade tensions and supply chain disruptions. And while the latest tools in this field – artificial intelligence (AI) and machine learning (ML) – promise to make tasks like liquidity forecasting, cash management and risk management easier, they bring their own complications and even limit the treasury team . more closely in management’s strategic planning.
This means corporate treasurers work closely with other business units and use data and analytics to provide crucial insights into financial and risk issues and improve cash flow. Treasury must be able to respond quickly to new scenarios while optimizing liquidity in both the short and long term to safeguard the company’s financial health.
“Things are changing on a daily basis, which is very different from three or four years ago,” said Herve Carrere, chief product officer Treasury and Capital Markets at Finastra. “You have the ongoing wars, the conflict with China, the high inflation, and… [high] interest rates.”
Faced with these challenges, companies need better forecasting and more efficient and regular analysis for scenario planning. “Treasurers must optimize as much as possible and be more flexible,” says Carrere. “They need efficient tools to manage cash flows, both cash-in and cash-out, and to predict the impact of something specific to their treasury needs.”
Cash flow forecasting is a top priority for treasurers, says Niki van Zanten, a former corporate treasurer and now a consultant at TreasurUp, a Netherlands-based fintech that serves banks. “It’s an activity, but what’s really important are the consequences of that activity,” he notes. “So that could mean making cash flow forecasts to make sure that you have enough liquidity in the very short term to pay all your salaries and invoices and make sure everything is clear. But you may also want to be sure that you have a permanent deal in six months’ time, for example.”
Data-driven forecasting
Liquidity forecasting, which uses more data sets to make cash flow forecasting more useful as a strategic tool, is one area where AI and ML can help, but they also create potential problems of their own.
“Many software vendors are starting with ML models that accelerate the calculation of selected proven models,” says Victoria Blake, Chief Product Officer at GTreasury, a US-based treasury and risk management software provider. “These models can be useful as a point of comparison for scenario planning and aid decision-making when it comes to treasury applications such as predicting future liquidity needs.”
AI, on the other hand, “requires substantially larger amounts of data to provide reasonably predictive model results for these treasury use cases,” says Blake. “Furthermore, the burden of AI effectiveness depends entirely on the engineering of the underlying model. This means that if the AI is a ‘black box’ in any form, it can be difficult to understand and act on the pattern factors that the AI predicts. So it is important that treasury teams first have a deep understanding of these models before using them, to avoid possible false signals and predictors.”
Black box AI systems are not practical for the treasury function, Van Zanten agrees.
“They need to see very clearly what data sources they have,” he says, “and they like to use data sources they already know. Forecasting for most businesses means doing the best they can with the least amount of effort, which means banks need to provide all the information they have on hand in a format the business can use.”
That said, AI and ML systems address corporate treasurers’ ongoing need for better ways to extract meaning from the numbers.
“We’ve seen how migrating to the right treasury data analytics strategy can absolutely transform the way treasury teams interpret and use their financial information – and deliver better business results across the enterprise suite,” Blake notes. “By using advanced analytical tools, treasury teams can discover much deeper insights from their ever-increasing amounts of financial data.”
These insights can include identifying key trends, patterns and anomalies that might otherwise go unnoticed, providing a clear picture of the company’s financial health.
“Real-time data processing enables a more flexible response to market changes and internal financial shifts,” says Blake. “Predictive analytics can predict future financial scenarios with greater accuracy, aiding risk management and strategic planning. Automation in this data analysis process also gives treasury teams the freedom to focus on interpreting results and developing strategic recommendations.”
Financial institutions are busy creating customer offers that leverage advanced data analytics. Mike Cummins, head of treasury solutions at Providence, RI-based Citizens Bank, says their focus is on providing customers with connectivity options and solutions that help them with liquidity management and fraud prevention.
“Within the domain of treasury management, data analytics are important for several reasons, especially for strategic and informative business decisions, cash flow forecasting and DPO analysis [days payable outstanding] and DSO [days sales outstanding],” notes Cummins. “Customers benefit by optimizing their working capital and minimizing costs.”
From API to SaaS
While large companies with multiple banking partners have a treasury management system (TMS) or a forecasting engine that makes multiple cash flow forecasts, a medium-sized company with only one main bank and perhaps a few others and a small finance department does not have the resources to run a own bank to set up their own full-fledged TMS, so they get it from their main banking partner.
This is a gap that their main banking partner may want to fill. “It will be a good place for banks to provide this,” says Van Zanten. “For medium-sized businesses earning between £30m and £300m a year, there are many benefits to starting to make good cash flow forecasts and professionalising financial processes. These companies have multiple accounts, multiple currencies, perhaps multiple banks and many data sources, but they typically lack the tools and knowledge to create comprehensive, consolidated forecasts.”
Migrating to the right treasury data analytics strategy can change the way treasury teams interpret and use their financial information.
Application Programming Interfaces (APIs) are transforming cash management for corporate treasurers by enabling real-time data exchange and automation. Finastra’s API Marketplace allows banks to provide both extensibility and interoperability to corporate customers by enabling collaboration between banks, fintechs, software providers and other market participants, Carrere says. FusionFabric.cloud, the collaborative SaaS (software as a service) platform, offers an a la carte menu of treasury services that banks can offer their corporate customers.
“APIs simplify connectivity to the rest of the ecosystem participants, depending on what you need, whether it’s payment connectivity, reconciliation, collateral management, etc.,” says Carrere. “They also provide additional revenue for banks, which can offer value-added services to their end customers based on big data models that they can test, validate and execute without having to undertake a costly project.”
Like APIs, which first emerged in the 1940s but are now ubiquitous, virtual accounts have been around for decades but are now evolving from simple digital subaccounts to sophisticated financial tools that provide enhanced functionality, expanded use cases, enhanced security and valuable provide insights. . These innovations enable treasury teams to optimize cash management, reduce costs and drive business growth.
“Businesses with a large number of physical bank accounts may face challenges around cash visibility and control. Valuable liquidity can often be in the wrong place at the wrong time,” said Tom Wood, Head of Global Payments Solutions, Commercial Banking, at HSBC UK. “By assigning each business unit and currency a unique virtual account number, our Virtual Account Management solution can help companies rejuvenate their cash management. Virtual accounts also support natural cash concentration, reduce dependence on physical accounts and can accelerate the onboarding process of new entities.”
Driving business growth in a tough economic climate is a challenge, but with tools like virtual accounts and APIs and new process models like SaaS, treasurers can access, aggregate and analyze real-time data from treasury systems and other sources, providing instant insight in their cash. and valuable insights that enable them to make more informed, data-driven decisions.
The post The treasury function becomes strategic first appeared on Global Finance Magazine.
