How Artificial Intelligence Improves Cash Forecasting

Accurate cash forecasting is critical to managing working capital effectively.

Organizations that use cash flow forecasting effectively are 1.5 times less likely to experience a liquidity crisis, per The Hackett Group.  A survey by the Aberdeen Group found that organizations that use cash flow forecasting are 2.5 times as likely to be profitable than those that do not.  

But organizations face significant challenges in forecasting their cash.

Artificial intelligence (AI)-powered cash management solutions solve these challenges.

This article explores how AI systems are improving the accuracy and efficiency of cash forecasting processes and the benefits that organizations of all sizes can achieve by using AI technology. 

What are the biggest cash forecasting challenges?

Organizations face big challenges when it comes to forecasting their cash.

• Inaccurate and incomplete data.  Sixty-three percent of organizations believe that their cash forecasting process is not accurate enough, according to the Association for Financial Professionals (AFP).  Accurately forecasting cash requires access to sales data, expense information, and market trends.  But aggregating data from various sources is hard.  It’s not uncommon for data to be fragmented, inconsistent, or incomplete.  And a lack of integration between systems can result in inconsistent, incomplete, or delayed data inputs.  

• Limited historical insights.  Fifty-seven percent of organizations say that their cash forecasting process is not integrated with other financial planning processes, according to a survey by the Aberdeen Group.  Cash managers often don’t have the visibility into historical payment and working capital data that they need to identify meaningful patterns and trends.

• Changing business dynamics.  New products or services, expansion into new markets, and changing operational processes can impact the accuracy of cash forecasting models.

• Volatility.  Market fluctuations, regulatory changes, unexpected events, and seasonality can have a big impact on cash flows.  Predicting the impact of volatility and seasonality can be difficult, especially for organizations that don’t have historical data on these scenarios.

• Customer payments.  The timing of customer payments can significantly impact cash flow.  But accurately predicting the timing of customer payments and changes in customer payment behavior can be a complex task for cash managers that don’t have access to historical data.   

• Details.  Knowing the level of detail to include in a cash flow forecast can be tricky for cash managers.  Short-term forecasts require more granularity and may be sensitive to minor fluctuations while long-term forecasts with fewer details may be subject to more uncertainty.   

• Human biases.  Many cash forecasts are built on assumptions and human judgement.  But misplaced optimism and incorrect subjective interpretations can lead to inaccuracies.

Organizations have too much riding on their cash forecasts to be held back by these challenges.

That’s why more cash managers are deploying AI-powered cash forecasting solutions.

How does artificial intelligence work?

The typical organization spends 100 hours per month on cash forecasting, per The Hackett Group.

AI-powered cash forecasting systems use sophisticated algorithms to analyze data, automate tasks, and make decisions that previously required human intelligence.  Here’s how AI works:

• Data collection.  AI-powered cash forecasting solutions collect large volumes of data from databases, systems of record, the Internet and other sources for analysis and decision-making.

• Data cleaning.  AI systems clean data before processing to remove inconsistencies and noise.

• Algorithm selection.  AI-powered systems use sophisticated algorithms such as machine learning, deep learning, and natural language processing.  AI-powered systems use different algorithms based on the task or specific type of problem, and the nature of the data.

• Training.  AIs learn from labeled or annotated data and adjusts internal parameters based on training results.  For instance, AI algorithms learn to map input data to desired output labels.

• Inference.  A trained AI solution collects information from multiple sources, applies the patterns, rules, and relationships it has learned, and produces cash forecasts.

• Continuous learning.  AI systems achieve improved performance over time by collecting and analyzing new data, adapting to changing conditions, and refining their predictions.   

Together, these capabilities improve the efficiency and effectiveness of cash forecasting processes.

How can AI improve cash forecasting?

Automatically analyzing data with AI-powered tools significantly enhances cash forecasting.

• Fewer manual tasks.  AI systems eliminate the manual, repetitive tasks involved in cash forecasting, freeing staff to focus more time on value-added activities such as data analysis. 

• Enhanced visibility.  By integrating data such as receivables transactions and expenses, AI-powered systems provide a complete view of a company’s finances for cash forecasting.

• Better accuracy.  By identifying patterns, correlations, and trends within historical cash flow information, AI-powered systems help cash managers develop more accurate forecasts.

• More timely cash flow predictions.  Seventy-two percent of organizations have experienced cash flow problems in the past year, AFP says.  AI-powered systems continuously collect and monitor information from point-of-sales solutions, financial platforms, and other sources in real-time, providing a business with up-to-date information on its cash position.   AI also learns from historical cash forecasting accuracy and refines its algorithms over time.  

• Predictive modeling.  AI systems can use machine learning and statistical modeling to analyze historical data and other variables to forecast cash flows based on different scenarios. 

• Risk assessment.  No business wants to be caught in a cash crunch.  AI-powered systems can simulate the impact of customer behavior, market conditions, economic indicators, and other factors on cash flows.  AI can even assess risks that may affect cash forecasting accuracy.

Overall, AI-powered systems empower businesses to leverage data-driven insights and advanced analytical techniques to improve the speed, accuracy, and efficiency of cash forecasting processes.

Improve your cash forecasting with AI

Businesses have a lot riding on their cash forecasts.  Inefficient and ineffective cash forecasts can make it difficult for a business to manage its financial resources.  AI-powered systems revolutionize cash forecasting by providing businesses with adaptive tools for collecting and analyzing data from multiple sources, identifying patterns, and predicting cash flows with a high degree of accuracy.  With more accurate cash forecasts, businesses can confidently make the informed financial decisions they need to ensure financial stability and growth in an increasingly competitive environment.