5 Metrics to Compare Excel Vs AI Cash Forecasting: Expectations Vs Reality

AI vs Excel: The most debated cash forecasting topic

Excel has been the most widely used cash forecasting tool for a long time, but it isn’t foolproof. It holds certain limitations such as:

• Completely manual and consumes a lot of time
• Error-prone
• Difficulty in gathering the right datasets and consolidating them
• Frequently requires human adjustments and inputs
• Inability to  compare variance

Due to the limitations, forecasts generated are inaccurate and unreliable. This leads to poor borrowing and investing decisions. AI can make a significant impact here.

Impact of Artificial Intelligence in Forecasting Cash

How AI Reforms Cash Forecasting

Artificial intelligence makes giant strides in improving the efficacy and agility of the forecasting process. Here’s what AI does:

• Automates manual and repetitive tasks such as gathering data from various sources
• Applies the best-fit algorithm to build accurate forecasts
• Compares forecasts to actuals data over different time horizons
• Adjusts forecasting models with time

According to the 2020 Treasury Perspectives Survey and the 2018 Rapid Research Technology Use Survey, AI has been acknowledged as a technology that can have a great impact on treasury automation.

Common roadblocks to adopting AI in cash forecasting

Despite the ease of implementing AI and the benefits it offers, vendors are still on the fence about adopting it. The most common roadblocks to AI are:

• Fear of losing jobs to AI
• Limited technical skill sets
• Limited knowledge of what happens under the hood

This is a pictorial representation of the roadblocks to AI adoption:

How to Address the Fear?

Even though Artificial Intelligence will automate most of the forecasting processes such as data gathering, modeling, and variance analysis, it still won’t replace human decision-making. In fact, it will be an enabler to the strategic growth of the treasury by supporting confident decision-making.

AI frees up analyst bandwidth to more strategic tasks such as risk management and aligns the treasury team to the business goals of the company.

5 Areas where AI Outperforms Excel

1. Variables:

Excel only allows a few variables(up to 4) that can be added to the forecast Whereas, AI allows up to 60 variables and helps in achieving a higher degree of accuracy.

2. Accuracy:

Excel supports static algorithms such as regression, averaging, heuristics in forecasting which fails to forecast complex categories such as A/R and A/P accurately. But, AI supports specialized algorithms for each category to boost accuracy. For eg. using a random forest classifier for forecast A/R vs using heuristics for payroll.

3. Variance:

Due to the major effort involved, companies perform variance analysis over limited time periods. Thus, forecasts that are generated have high variance. AI, on the contrary, helps in performing variance analysis over multiple durations, with increased frequencies to compare:

• Forecast vs Actual
• Forecast vs Forecast

4. Frequency:

Due to economic volatility, companies nowadays want to perform forecasts with higher more frequency than before. With spreadsheet-based forecasting, the reports generated are not up-to-date, hence inaccurate. This is how the manual forecasting process looks like:

The reports are outdated by the time they are sent out to the CFOs since it takes plenty of time to generate the reports. However, Artificial Intelligence provides real-time forecasting to reflect the most up-to-date numbers.

5. Potential ROI:

AI guarantees higher ROI and cost savings due to the following reasons:

• Lower interest expense with advanced borrowing
• Higher investment returns  with accurate long-term forecasts
• FTE time savings with automation

Cash forecasting has far-reaching implications since it drives liquidity and financial planning. AI is revolutionizing cash flow forecasting, resulting in high productivity among treasury and generating increased savings.