“Forecast accuracy increases as extensive data is analyzed intensively.”
A recent survey with treasury teams from leading Fortune 1000 companies revealed that the main reasons for inaccurate cash forecasts included unusual spikes in A/P, uncontrollable timing of A/R, price volatility and market dynamics. This means that treasury teams could produce more accurate forecasts if they could process and analyze more extensive datasets across A/R, A/P, and other cash-flow categories.
But, can treasurers handle such complex datasets without wasting time on data-mining or excel modeling?
Consider receivables forecasting as an example. Invoice-level payment dates can be accurately predicted by calculating the forecast using around 30 variables (~60 for some companies) ranging from open invoice data to historic and recent customer payment behavior. But, how can your treasury team process this data, let alone determine the 30+ variables to track?
Artificial Intelligence-enabled cash forecasting models automatically generate high-accuracy reliable forecasts across all categories and timeframes, allowing treasurers to focus on strategic decision making. Join this webinar to learn how your treasury team can start adopting AI-enabled cash forecasting into their everyday practice.