Cash forecasting: faster and more accurate through treasury technology

Cash forecasting is essential. Everybody has to do it. For me as an individual, it’s simple because I have manageable income and expenses. For global companies, it gets difficult very quickly as they have many, often unpredictable cash flows.

From a cash manager right up to the CFO and CEO, everybody wants to know how much money their company has today, next week, next month, and next year. The concept is easy. But as organizations scale and complexity arises, corporations find it difficult to create their cash forecasts regularly and accurately. Often, they do not have a centralized way to collect data, lack the tools to analyze data, and cannot visually represent their data to empower decision making. That’s where a treasury management system (TMS) can help.

Technology for cash forecasting

From simple treasuries to central banks, treasury technology is used to automate the gathering, consolidation, and analysis of all elements of cash forecasting. A TMS delivers essential information to allow businesses to make informed decisions no matter what business strategy they may have.

With treasury management technology, cash managers no longer need to piece together information on a manual basis to answer simple questions from their CFO. They can provide the CFO with the reports needed to drive shareholder value.

Treasury technology helps corporations effectively forecast their cash inflows and outflows. By automating the cash forecasting process, finance teams do not have to spend time gathering cash positions manually, but instead can spend their time analyzing data to identify opportunities and correct anomalies. At the end of the day, it is decision making that drives the direction and the success of the company and makes the treasurer stand out.

Machine learning tools for cash forecasting

Machine learning is everywhere: in the ads you see, the things you buy, even what the world will look like in 10 years is being predicted using machine learning and data. Why should cash forecasting be any different? Using machine learning, cash forecasting can be totally automated.

With a TMS equipped with advanced statistical methods, treasury teams look at their cash forecasting data in many ways. They can identify patterns, look at trends, understand where a business comes from, and where it is going–all in one place, at one time.

Corporates increasingly move away from forecasting on spreadsheets to using a TMS. As technology adoption increases, they focus on creating forecasts more frequently and with more accuracy. Instead of updating their forecast monthly, more companies now update their forecast on a weekly or even daily basis.

A recent survey indicated that 82% of ION customers see that machine learning will be the biggest benefit to the forecasting process. Machine learning capabilities for cash forecasting help businesses create more timely, accurate forecasts, leveraging statistical analysis and neural nets.

Machine learning techniques depend a lot on the historical data and the trends within the historical data. The better the input data, the better the output, increasing the need for a systematic way of doing cash forecasting.

Due to the COVID-19 pandemic, a lot of companies might now think their historical data is “irrelevant” or “incorrect” and might steer away from implementing machine learning in their cash forecasting process. The good news is that industry trends and other statistics are readily available in the market and can be applied to a company’s ML-based cash forecasts. Sophisticated TMS’s combine ML-based cash forecasting capabilities with native stress testing functionality, providing treasury teams with the most accurate and informative tools possible for any market events.

Treasury teams can increase the efficiency and control of their cash forecasting process with a treasury management system. By implementing machine learning techniques, they can boost the speed and accuracy of their forecasts even further, even reducing the time taken to create a cash forecast by factors of thousands.