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How to use Artificial Intelligence to forecast Accounts Receivable?

What you’ll learn


  • The importance of managing accounts receivable
  • The challenges in accounts receivable management
  • Tips to improve the accuracy of accounts receivable forecasting

What is accounts receivable and why is it important?

Accounts receivable (A/R) is the money owed to a company by its clients who buy items or services on credit.

It is crucial to monitor A/R since it is one of the key drivers of measuring a company’s liquidity. Failure to track accounts receivable leads to a high DSO. This negatively impacts the financial situation. Hence, companies should consider a suitable system for A/R forecasting.

What is the importance of managing accounts receivable?

Example:
Company A got $400,000 of its due money and needs to drain its bank account to meet its monthly payments. This left it $25,000 short on cash. The company could have reduced other expenditures or pursued low-interest loans if it predicted A/R beforehand. It realized that it needed more funds only days before its payments were due. This raised the demand for quick funding, which affected the bottom line.

To avoid such adverse scenarios, receivables management is crucial. Good accounts receivable management decreases bad debt and adds to a company’s profit. A/R management becomes easier with an AI cash flow forecasting system. Accurate A/R forecasting helps optimize liquidity for:

  • Distressed Businesses:
    • They can perform daily and accurate forecasting to estimate available cash
    • They can work with banks to make credit revolvers more flexible
    • They can adopt a collecting strategy that is aggressive for all clients
  • Cash Deficit Businesses:
    • They can borrow in advance with short-term forecasting
    • They can check the available balances in credit revolvers and commercial papers
    • They can adopt a more aggressive A/R collection strategy for high-risk consumers
  • Cash Surplus Businesses:
    • They can understand the accuracy of the industry’s benchmarks
    • They can help the CFO’s office make better quarter-end business decisions
    • They can use technology to identify and use excess cash for investments

Why is it challenging to forecast cash for accounts receivable?

Accounts receivable forecasting is difficult since it is dependent on the clients. Customers may not always stick to agreed-upon payment terms. This adds an element of uncertainty to the process. A/R is the most challenging category to forecast for treasurers.

What is the toughest cash flow category to forecast?

Accounts receivable management becomes increasingly difficult as a company grows larger. For an enterprise, it becomes complicated due to scattered data across many business units. Companies may face various issues, including poor receivables administration and time-consuming reporting processes. Several factors increase the unpredictability in A/R forecasting, leading to low accuracy.

Factors causing unpredictability in A/R

Factors causing unpredictability in A/R

Challenges in accounts receivable cash forecasting

  • Forecast inaccuracy due to spreadsheet restrictions and errors:
    There is room for human error in spreadsheets. It is also time-consuming to compile data from many spreadsheets to one master sheet.
  • Scattered data across various data sources:
    Manual data mining from sources like ERPs, banks, and FP&A systems makes data gathering tedious.
  • Economic volatility:
    The unpredictability of market dynamics creates inaccurate forecasts.
  • Inconsistent customer payment habits:
    Payment methods and market size vary across customers and businesses. Spreadsheets are unable to track several customer behaviors and patterns. Without adding many customer-specific variables, the forecast accuracy reduces. As a result, payments may not arrive as anticipated.

How Artificial Intelligence improves the accuracy of accounts receivable forecasting?

Spreadsheet-based cash flow projections only generate two-dimensional tabular reports. But, AI cash forecasting provides treasurers with a 360-degree view of the present, historical, and future data. This enables them to make informed business decisions.

How AI automates cash forecasting for accounts receivable for accurate forecasts

AI cash forecasting enables:

  • Real-time revision of cash forecasts
  • Granular visibility into A/R cash flows
  • Predicting payment date with accuracy

Tips to improve accuracy in A/R forecasting

  • Historical data analysis:
    A careful analysis of previous A/R forecasts helps identify patterns that are likely to continue in the future. A few key points while analyzing this data include:

    • Seasonality in the workplace, both a high-level overview and a more comprehensive report
    • Payment habits of the high-risk customers
  • Creating subcategories for accounts receivable:
    Based on historical data analysis, accounts receivable may be subdivided into subcategories. The sub-categorization aims to refocus improvement efforts on the error-prone areas. The following are examples of subcategories:

    • Date of payment
    • Terms of payment
    • Size of the client
    • Credit score of the customer
  • Observing and tweaking assumptions:
    To improve A/R forecasting, it’s necessary to test and change assumptions frequently. In a short period of time, monitoring, updating, and iterating processes convert a prediction from poor to high quality.
  • Using a fully automated A/R forecasting software:
    An automated cash flow forecasting software provides real-time data with high visibility. So, it gives more accurate results than manual forecasting methods.

Advantages of using HighRadius’ AI cash flow forecasting system to forecast cash for A/R

The following are the benefits of using HighRadius cash forecasting system:

  • Makes precise short and long-term cash forecasts
  • Compares historical cash flow data to current estimates and finds potential areas for improvement
  • Uses the best-fit algorithm to analyze many characteristics describing client payment behaviors
  • Improves accuracy up to 95% in predicting payment dates

Customer Success Story

How a billion-dollar construction firm tackled liquidity shortages for 1800+ projects

A billion-dollar construction company was facing the following challenges:

  • They followed a simplistic forecast model with low accuracy
  • Their A/R forecast derived from DSO
  • They had a completely manual and tedious process that made them spend up to 20 hours a week forecasting cash.
  • They didn’t perform variance analysis and had no control over data from their A/R and A/P teams.

HighRadius’ Cash Forecasting Cloud provided the following results:

  • Improved forecast accuracy by 40%
  • Increased workflow efficiency
  • Refined data collection from various teams
  • Increased accuracy achieved in A/R & A/P forecast by up to 95%
  • Introduced variance analysis which provided a project-level drill down to find fluctuations

Schedule a demo to learn how to use AI cash forecasting software to improve A/R forecasting accuracy.

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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.