Spreadsheets vs AI: Why AI Wins in Cash Forecasting 

The impact of spreadsheet-driven cash forecasts

The forecasts generated through spreadsheets are inaccurate and unreliable which leads to the following negative impacts:

• Increased cash buffers: When forecasts are inaccurate, companies increase their cash buffers due to low confidence and improper decision-making.
• Higher borrowing costs: Since the reports are dead-on-arrival and based on assumptions, firms overborrow due to financial distress since they aren’t well prepared for macro-level fluctuations.
• Penalties: Due to improper management of liquidity, and extremely delayed payables, firms are charged with penalties or repercussions like damaged relationships with external partners.
• Delayed investments: Due to high cash buffers, firms postpone investments that can be fruitful for their growth.

These effects impact the treasury on a global level:

Spreadsheets are still by far the most used technology to generate a cash flow forecast. But, as companies strive to achieve better accuracy in forecasts, the need for Artificial Intelligence has escalated.

Advantages of cash forecasting with AI

AI overcomes most of the challenges from forecasting cash using spreadsheets such as:

• Automates data gathering and integrates from multiple sources such as bank portals, TMS, ERPs, FP&A systems, etc.
• Applies the best-fit algorithm to build highly accurate forecasts and doesn’t need much human intervention.
• Tracks variance by comparing forecasts to actuals data over different time horizons.
• Lowers the variance by a significant degree by using Machine Learning to tweak the models.

The impact of AI-powered cash forecasts

Accurate cash flow forecasts built with the help of AI leads to the better financial health of a firm with:

• Reduced forecast turnaround times: Real-time forecasts help businesses manage macroeconomic fluctuations by taking timely decisions.
• Effective cash and risk management: Optimize the cash conversion cycle by unlocking trapped working capital.
• Reduced idle cash: This enables firms to invest surplus cash and generate interest gains.
• Increased strategic decisions: Highly accurate forecasts support the CFO’s office in making confident decisions on M&A, business expansions, repatriation, etc. This builds credibility for treasury.

Effect on global treasury with enhanced forecast accuracy

Despite the numerous benefits that AI offers, the jury is still out on if AI is better than spreadsheets. This debate can be settled by evaluating AI with Spreadsheets against some metrics.

Key metrics to compare AI vs Excel

 

1. Visibility:

While using spreadsheets, treasury analysts need to gather data from several data sources like bank portals, TMS, ERPs, etc, and consolidate them into one spreadsheet. This process is quite time-consuming and labor-intensive and hinders visibility. But, AI readily integrates with multiple systems and builds bottom-up forecasts that provide granular visibility.

2. Accuracy:

Spreadsheet increases the scope of human errors and limits adding multiple variables to forecast for complex cash flow categories like A/R and A/P. On the contrary, AI supports up to 60 variables, which improves accuracy in cash forecasting.

3. Modeling:

Spreadsheet limits the usage of only a few formulas, so forecasting has to be relied on by a technically well-versed person. Whereas, AI supports the use of multiple algorithms and selects the best fit curve to continuously increase the level of accuracy.

4. Variance Analysis:

Due to the major effort involved and greater time spent in the manual process, companies perform variance analysis over limited time periods. AI, on the other hand, helps in drilling down to the variance drivers and reducing them with the help of machine learning that evolves forecasts with time and data. AI helps in performing variance analysis over multiple durations, with increased frequencies to compare:

• Forecast vs Actual
• Forecast vs Forecast

5. Frequency: 

Organizations demand greater forecast frequency to improve their financial performance and prevent bankruptcy. Due to the time constraints with manual-based forecasting, it is not viable to create high-frequency forecasts. Furthermore, the Excel-based forecasting reports are outdated by the time they reach the C-Suites due to high turn-around time. On the contrary, AI-based forecasts get updated in real-time to present the most up-to-date figures.

6. Potential ROI:

AI provides greater ROI in short term as well as long term due to the following reasons:

• Decreased interest expense
• Increased investment income
• Freeing up resource bandwidth