Cash forecasting

How Corporate Treasurers Approach Medium & Long-Term Cash Forecasting

Report date: 
2 Jun 2026

Commentary

There are few subjects on which all treasurers agree. Cash forecasting is one: everyone agrees it is difficult, painful, and rarely accurate. And that is just the “easy” part, forecasting the short term, i.e., up to three months. 

What happens when you reach out into the distant future – the medium and long term cash forecast? Surely, this is vital, if nothing else, so a company can plan its dividends and debt raising or repayment in advance? But it quickly becomes difficult, as techniques start to diverge. The best short term forecast is done looking at actual cash, and mapping out the expected receipts and disbursements. Beyond three months, this generally doesn’t work, as actual payments and receipts become less certain. People start to look at the strategic plan and try to work out the likely cash impacts – most treasurers view this as being less operationally relevant. Also, some people take input from the operating units and consolidate it, while others take a “tops down” approach.

In fact, the call started with a healthy discussion: why do a longer term cash forecast at all? 

  • For several peers, cash and funding was not a real issue. In this case, a good cash forecast may enable, say, $150,000 of saved interest expense by eliminating buffers and avoiding unnecessary borrowing. But, if it costs more than $150,000 to produce this good forecast, what is the benefit?
  • Other peers had really tight cash situations, were trying hard to maintain a favourable credit rating, or needed to meet the cash targets of private equity owners. In these cases, a good cash forecast was an operational necessity, and cash generation was often a significant KPI.
  • In all cases, the view of management was an essential consideration. Without full senior management support, a good process is more or less impossible, since it requires a lot of work and cooperation by different functions.
  • Group structure is a big factor. Where funding is done locally, a group cash forecast is not necessarily useful: in this case, what matters most to the group is managing local debt levels and the amount of cash being remitted to HQ. Local entities are usually motivated to do a good forecast.

So, how do peers handle this thorny issue? - Please Register / Log In to read the rest of this commentary

 

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Plans & Experiences with AI in Cash Forecasting

Report date: 
17 Sep 2024

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Corporate Treasury Payment Service Provider Relationship Management

Report date: 
24 Oct 2023

Commentary

“May you live in interesting times” goes the old Chinese curse. Whether we are cursed or not, we are certainly living in interesting times.

This call focused on one area of the information revolution – Payment Service Providers

(PSPs), but it was an illuminating insight into the challenges treasurers face. The multitude of payment methodologies and PSPs are forcing treasurers to deal with many different approaches, companies and formats. Today digital sales are mostly for B2C transactions, but this is spreading to B2B as business models evolve.

As treasuries move to APIs, bots and other less structured forms of communication, everyone will face the issues discussed in this report (the full 18 page report is available to premium subscribers - enquire here for details).

The biggest issues participants raised are:

  • Ownership. Treasury clearly owns the relationship with traditional banks. But many treasurers find that marketing or other functions (notably IT) sign up the company for a PSP relationship, and then leave it for treasury to resolve the issues. Participants are beginning to lay down rules for approving new relationships, usually involving marketing and IT.
  • Management system. One participant has a rigourous process which involves marketing, IT and treasury to make sure all aspects are covered.
  • Local vs global. Some PSPs are global, while others are regional, or purely local. The purely local ones are usually left to local or regional teams to manage, while global ones are typically managed from HQ. In some cases, only local options are available: this is a challenge for centralised treasuries.
  • Global PSPs. The main providers mentioned were PayPal, Ayden and WorldPay. No-one finds they can
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AI & Robotics in Corporate Treasury

Report date: 
9 May 2023

Commentary

This call was organised in the midst of media hype about AI (Artificial Intelligence), with several banks having banned the use of ChatGPT, and highly convincing fake videos being created and going viral. The first question was whether our members share the banks’ concern over the danger of tools such as ChatGPT running out of control and executing highly credible frauds. The answer was “No” - in the sense that it was not on anyone’s radar screen.

The second question was about the adoption of robots to automate treasury processes: these typically execute pre-defined processes, with no decision-making function. There are high levels of interest in this, and increasing levels of adoption. 

AI is of interest for areas such as forecasting, where an increasing number of applications are available which look at historical data and use it to predict future patterns. However, only one participant is currently using it for cash forecasting. But:

  • Banks are increasingly using AI to screen transactions, and highlight unusual ones. This is good – but one participant saw valid, but unusual, transactions fail to execute on time as a result.  
  • AI’s ability to handle large data lakes or oceans inside companies is a positive - but it is hard to be sure all the relevant data has been included. 
  • One participant is concerned that the questions being asked on ChatGPT could potentially be tracked, leading to confidentiality breaches.
  • The same participant is also concerned that the inability to track and verify the source of data in this tool could lead to unintentional copyright infringements. Usage rules are being put in place to manage these risks.

On the other hand, most participants are actively using robots for various tasks:

  • Allocation of
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