Several automated cash forecasting software are now at treasury’s disposal which can be used to monitor and improve cash flows. However, there are a lot of buzzwords around cash forecasting automation that might lead to confusion during adoption. The myths associated with automation can be debunked by learning how automated cash forecasting works in reality.
Step 1. Input Data: Cash forecasting automation software needs to be incorporated with adequate, relevant, and good quality data for training the models and testing the results.
Step 2. Processing: The processing relies on the type of data fed into the system. The choices of algorithms and models are dependent on:
Step 3. Output data: GIGO-The quality of the output generated depends on the quality of input data incorporated into the models. Automated cash forecasting software generates accurate and reliable forecasts. As a result, the predictions and recommendations are consistent and readily usable, and the insights are useful for making data-driven and confident decisions.
The benefits reaped from using automated cash forecasting software are:
Companies that operate in various parts of the world have multiple banks and ERPs, thus they have limited granular visibility into the cash flows. The lack of visibility hinders variance analysis, hence affecting decision-making.
Automated cash forecasting provides a single source of truth by gathering data automatically straight from sources such as TMS, ERPs, banks, and FP&A systems. Thus, it increases granular visibility into the business cash flows.
The software generates real-time and good-quality reports with detailed insights and drill-down capability. Since the turnaround time is reduced, the CFOs can instantly gather reports on cash flows, available balances in banks, and funding requirements. The reports are also accurate enough to be sent out to external stakeholders and build credibility with the board and investors.
Companies that focus on tightly managing cash to stay afloat during volatile times need to prioritize funding for business units and execute cash pooling on a weekly or daily basis. This gives them an opportunity to draw from their revolvers at lower interest rates. Cash forecasting automation allows cash deficit companies to forecast weekly or daily to make proactive and confident borrowing decisions.
As automation handles manual and time-consuming tasks, it reduces the administrative burden on the treasury department. As a result, the treasury can focus on high-value activities such as cash management, risk management, and strategic decision-making.
Automated cash forecasting software improves the accuracy of the forecasts through machine learning by comparing past and recent results, identifying the errors, and making continuous improvements. Real-time data visibility and accuracy in forecasting cash flows help treasurers proactively identify and mitigate risks before they amount to losses for the organization.
Automated cash forecasting is more accurate than manual cash forecasting due to the following reasons:
An automated cash forecasting solution learns from data and improves with time. Spreadsheet limits the use of multiple variables, so certain nuances can’t be tracked through the manual approach. On the contrary, AI performs a historical analysis and a regression analysis to understand the historical patterns associated with A/R and A/P and predict customer-specific payment dates by supporting multiple customer and invoice-level variables.
Different models are used for different cash flow categories based on the complexity and uncertainty of a cash flow category. For example, forecasting A/R needs to be forecasted using AI models. In contrast, payroll and CAPEX forecasts are performed using heuristic models.
AI enables incorporating external factors to capture trends such as raw material price fluctuations for generating an accurate sales forecast. The time series algorithm prioritizes recent trends over historic ones and incorporates seasonality into cash flow forecasts to boost accuracy.
AI enables performing variance analysis across various cash flows and for various time horizons. The variance is reduced through the ‘closed-loop feedback system.’ The closed-loop feedback system facilitates AI systems to learn what they did correctly or incorrectly, providing them with data to adjust the forecasts accordingly.
Read more on how AI-enabled cash forecasts perform better than spreadsheet-driven forecasts.
HighRadius’ cash forecasting software captures data from multiple data sources automatically to provide easy data access and provides real-time insights into the cash flows. Moreover, it captures external data, ‘what-if’ scenarios, and customer-specific payment trends and behavior using Artificial Intelligence to increase the accuracy of the cash forecasts.
When AI models are used for complex cash flow categories such as A/R and A/P, it builds forecast accuracy and allows CFOs to make confident decisions towards debts and investments instead of relying on intuitions.
The automated cash forecasting solution at HighRadius supports performing variance analysis over multiple durations across multiple regions, entities, and cash category levels. Additionally, it supports functionality to drill down into variance drivers for exercising better control over cash flows.
Talk to an expert today to gather more insights into what HighRadius’ cash flow forecasting software offers for treasury and finance.
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.