An accurate cash flow forecast helps companies predict future cash flows, avoid crippling cash shortages, and earn returns on cash surpluses in the most efficient manner possible.
Companies can be classified into two types based on their cash position:
During Covid-19, based on cash position and financial situation, the drivers influencing the purpose of cash forecasting varies as per the following:
There are two methods of cash flow forecasting:
An indirect cash forecast is driven from various projected income statements and balance sheets, generally done as part of the planning and budgeting processes.
Direct cash forecasting or short-term forecasting is a method of forecasting cash flows and balances that are used for short-term liquidity management purposes. It’s also called the receipts and disbursements method.
Spreadsheets have been the most widely used for cash forecasting for a long time. They hold certain limitations such as:
Due to the limitations, forecasts generated are inaccurate and unreliable. This leads to poor borrowing and investing decisions.
Poor cash forecasting methods include everything from using ineffective tools to focusing on the wrong factors. Many companies still rely on manual or semi-automated forecasting tools, such as spreadsheets, and these are far from optimal.
Some major impacts of inaccurate forecasts are:
The three most promising technologies to improve forecast accuracy are:
RPAs are robots that are programmed to run a certain set of tasks with little to no human intervention. This would enable treasury teams to free up a lot of time previously used in repetitive tasks like data gathering and consolidating and focus more on higher-value duties like cash forecasting.
Artificial Intelligence utilizes self-learning algorithms to identify patterns and changes in them and guides treasurers on what to do. It can track anomalies in transactions and stop them or find shifting behaviors in operations and suggest better alternatives.
The machine learning algorithms ultimately impact what the generated forecast looks like. Better quality of the input data used for training produces better output (GIGO).
Using machine learning techniques, treasury teams can get monetary gains, prepare better, plan, and validate data. Also, with these tools, they can be relieved from performing mundane, tedious tasks, allowing them to be a more strategic player and operate in new and more effective ways.
Artificial Intelligence is the best-fit technology since generates significantly accurate forecasts due to its ability to forecast complex categories such as A/R and A/P with a high degree of accuracy.
Staying on top of market movements or uncertainty with agile forecasting
Improved liquidity with faster cash conversion cycle
Improved capital allocation and risk management for the CFO’s office
Making strategic decisions related to business expansions and M&A
The treasurer is able to make confident decisions based on accurate and real-time forecasts, which enhances the credibility of the treasurer in the CFO’s office.
The three primary accuracy driven ROI factors are:
Increased accuracy leads to better debt/investment decisions and less cash on hand.
1. Determine the difference in interest costs that would result from making better judgments (more LIBOR loans, fewer prime loans).
2. Borrowing limits are reduced, and interest rates are improved.
Automation leads to reduced time spent creating, updating, and consolidating forecasts and variances.
1. Calculate the cost of time wasted on tasks that could be automated.
2. Determine the incremental value of other jobs that can be completed as a result of the new time savings.
Greater confidence and credibility with consistent and highly accurate forecasts.
The HighRadius™ Treasury Management Applications consist of AI-powered Cash Forecasting Cloud and Cash Management Cloud designed to support treasury teams from companies of all sizes and industries. Delivered as SaaS, our solutions seamlessly integrate with multiple systems including ERPs, TMS, accounting systems, and banks using sFTP or API. They help treasuries around the world achieve end-to-end automation in their forecasting and cash management processes to deliver accurate and insightful results with lesser manual effort.