The Role of AI in Predicting A/R & A/P for Accurate Cash Forecasting

Cash is often regarded as the lifeblood of an organization as it enables the proper functioning of a company. However, when it comes to forecasting cash, most companies are lagging behind due to their inability to predict A/R and A/P accurately.

What Are the Top Challenges in Cash Forecasting?

Cash forecasting is a complex problem and trying to estimate what will happen on the A/R side of the equation is much more complicated than on the A/P side.
Both have a component of unpredictability, but

• With A/P, you know what is due and when you plan to pay that amount
• With A/R, you know when payments are due from your customers, but you usually cannot
  reliably predict if they will pay on time, early,late or not at all.

Why Is Accounts Receivable Difficult to Forecast?

Accounts receivable forecasting is particularly challenging as it is entirely in the client company’s hands. While payment terms are agreed upon, customers might not always adhere to them, adding an element of unpredictability to the process.

Further challenges that make forecasting A/R difficult include:

• Sheer volume of invoices
• Range of systems creating data variability
• Number of entities involved

Factors Causing Unpredictability in A/R

Why Is Accounts Payable Difficult to Forecast?

In the case of A/P, the forecast is accurate in the short-term, up to the next 2 to 4 weeks.However, it is in the longer run that the accuracy takes a hit because of uncertainties revolving around payments.

Challenges when forecasting A/P are:

• Difficult to predict payments for which invoices haven’t arrived yet from suppliers
• Increased variability during seasonal rebate programs
• Volatility in payment dates and timings during CAPEX projects

Factors Causing Unpredictability in A/P

Benefits of Using Artificial Intelligence for Cash Forecasting

Transformation for Digital Treasury Starts with the Following Steps

• CONSIDER AUTOMATION

  AI, when combined with TMS systems, Bank Systems and
  ERP systems can substantially improve the quality of the forecasts produced.

• SEE THE BIG PICTURE

  Automate part or all of the process to reduce the risk of
  human error, thereby improving confidence in the forecast.

• ANALYZE THE DATA

  Observe data from a high-level view across different
  categories and regions.

• MAKE STRATEGIC DECISIONS

  Move from data entry and model creation to being strategic
  contributors in the CFO’s office.