Predictive Analytics for Accounts Receivable

If you work in a UK-based company that provides credit facilities to customers, you’re likely faced with one or more of these challenges. How to:

• provide credit facilities without risking the survival and growth of your company.
• gain real-time visibility of cashflow and build collaboration throughout the accounts receivable (AR) cycle.
• measure the creditworthiness of customers and spot credit risks early.
• improve your team’s productivity and collections strategy.
• confidently forecast cashflow and allocate budgets.

If this describes you, you're in the right place. We’ll show you how predictive analytics in AR helps you to solve these problems. You’ll also learn how to use Wise Business to receive local and international payments with ease.

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What is predictive analytics in accounts receivable and how does it work?

Predictive analytics in accounts receivable is the use of artificial intelligence, statistics, data mining, machine learning, and modelling to determine the future payment behaviour of customers who owe your business based on their previous behaviours and current trends.

Accounts receivable predictive analytics examples

Here's a predictive analytics example to show how it works in the AR function.

Imagine being a collection specialist at The Square Manufacturing Company, a Manufacturing company in Cardiff, Wales that offers goods to customers with a 30-day payment window. A slowdown in AR, limits liquidity and stalls the company's expansion into London and Belfast.

With thousands of invoices to manually follow up on, your team battles late payments, lack of clarity on which calls to prioritise, aging accounts receivables and an ever-reducing working capital.

These problems lead to payroll hitches and delayed vendor payments. You either lose the opportunity to scale or opt for external funding with high interest rates.

The solution would be to switch from manual data processing to using AR software with predictive analytics functionality.

Using predictive analytics will help your finance team to analyse customer behaviour, determine risk categories and visualise how current collection strategies and trends impact cashflow. Your team can then take corrective measures like reviewing credit terms and limits and assessing customer creditworthiness based on data.

Benefits of implementing predictive analytics in accounts receivable

Finding a balance between providing credit for customers while protecting the growth and fiscal health of a business takes skill and experience. But implementing predictive analytics in AR provides the insight and support to effectively achieve this.

With predictive analytics, you can:

• monitor changes in the credit risk of customers based on data from your records and external sources like credit risk intelligence platforms such as CreditSafe and credit insurance companies like Atradius UK. Using this, your team can accurately assess customer risk profiles to personalise credit policies and approvals and improve sales discussions by stating credit limits upfront.

• understand how your current AR is affecting cashflow. Thus improving your strategic decision-making and letting you boldly plan budgets based on more accurate cashflow predictions.

• know customers’ average days to pay and objectively forecast customer payment behaviour. This matters as research shows that 57% of SME businesses in the UK face increasing Day Sales Outstanding in 2025.¹ To avoid this, segment customers and build effective collection strategies.

• save resources by prioritising and pursuing high-value and high-risk invoices. This can improve collection rates or trigger promise to pay responses thus increasing available working capital.

• send personalised payment reminders based on customers’ predicted repayment behaviour leading to prompt invoice payments without hurting customer relationships.

Accounts receivable predictive analysis vs manual data processing

How to implement predictive analytics to accounts receivable?

Take the following steps to implement predictive analytics to accounts receivable:

• Assess your current accounts receivable processes and challenges: List the problems you’ve observed with your AR process. For example, a multi-national company with branches in 80+ countries with local sales and finance teams may have problems like lack of standardisation of credit policies and collections strategies.

• Identify your objectives: Why are you implementing predictive analytics in AR? Engage finance team members in this process to improve their participation.

  • What problems are you looking to solve?
  • What are your KPIs?
  • What will you predict and what goals will those predictions help you achieve?
  • What strategic decisions will these predictions influence?

• Research different options and match features to your goals: Search for keywords like “accounts receivable analytics software reviews” on Search engines. Make a list of the AR analytics software you find and visit their sites to explore features. Consider what software features or functionalities can achieve your team's goals.

  Also read customer reviews and ratings on sites like GetApp, G2, Trustpilot and Capterra to learn more.

  Compare prices and the cost of ownership by speaking with a sales rep. Then test the software with a free trial or demo before making financial commitments.

• Clean up data: Organize your data and ensure it doesn't have number format errors or missing values.

• Execute gradually: Upload data from your spreadsheets, link bank statements and add your actuals. Run pilot tests to get feedback and make corrections.

  Then link automated systems like your Enterprise Resource Planning software, Treasury Management System and data lake. Afterwards, run these in your predictive analytics accounts receivable software.

  It’s advisable to do a pilot test, receive feedback and make changes before full-scale implementation. For instance, a multinational company can implement predictive analytics in one region and then scale to all other countries.

• Upskill stakeholders and integrate the AR analytics software into workflows: Build a team of experts like data analysts, and data scientists and financial experts. Alternatively, your IT and finance department can work with the customer success team of your chosen AR analytics software brand.

• Monitor and improve AR analytics management: Continuously monitor how well your accounts receivable forecasts are working and modify the model going forward.

Receivables analytics software options

There’s an array of receivables analytics software you can choose from. The best brand for you should have features your team needs, responsive customer care, and be easy to use. Here are a few:

1. Sidetrade

Sidetrade is an AI-powered order-to-cash platform with a track record of 1 billion processed invoices.

Some of its features are:

• Credit risk management: This provides insight into customer risk profiles and lets you set personalised credit limits and insurance guarantees.²
• Payment Intelligence: It analyses customer and industry payment behaviours and predicts their Average Payment Period (APP).³
• Augmented invoice: This offers invoicing automation integrated with your business’ ERP.⁴

Pricing: Not available online.

2. Upflow

Upflow is a financial relationship management software designed to help finance teams maintain relationships with customers while improving their Day Sales Outstanding (DSO) and Collection Effectiveness Index (CEI). Its features include:

• B2B cash collection technology: This lets you create tailored payment reminders, manage all invoices in one place and segment customers.⁵
• Analytics dashboard: This provides insight into real-time Day Sales Outstanding (DSO) and Collection Effectiveness Index (CEI) reports, and measures collection rate and cashflow status.⁶
• A customer portal: It lets you monitor invoices in real time and digitally process payments.⁷

Pricing: Upflow offers a free trial. Its Grow and Scale packages are billed annually at $440/mo and $880/mo respectively.⁸

3. Blackline

Blackline is a financial operations platform that provides AR services.

Some of its features are:

• AR intelligence: This feature shows forecasted payment behaviours and how payment terms and customer compliance affect your cashflow.⁹
• Credit and risk management which assesses customer risk profiles and triggers real-time credit limit reviews.¹⁰

Pricing: Not available online.

4. Chaser

Chaser is an AR management software built with features like:

• Credit monitoring: This feature provides updated credit risk reporting and alerts.¹¹
• Payer rating: This ranks and groups customers by their payment behaviour.¹²
• Late payment predictor: It’s designed to forecast whether customers will pay you on time or not.¹³
• Revenue forecast: It predicts revenue using machine-learning models.¹⁴

Pricing: Starts at £33 per month (billed annually)¹⁵

FAQs on predictive analytics in accounts receivable

Here are some common questions and answers on this topic:

What are the benefits of using predictive analytics in accounts receivable?

Predictive analytics in AR helps finance teams to:

• predict possible credit repayment delays using historical data and data from other sources like credit risk intelligence platforms and credit insurance companies.
• visualise collection trends and forecast the future impact on cashflow
• personalise credit terms, limits and collection strategy based on customers’ average days to pay.

How can predictive analytics improve cash flow management?

• Predictive analytics provides more accurate cashflow predictions unlike manual forecasts and reduces reliance on inaccurate and manually collated data.
• It helps CFOs and finance teams have an up-to-date view of the liquidity and financial health of the business. With this information, they can review credit policies, collection strategies and budget allocation to boost business growth.

What tools can analyse accounts receivable?

Some accounts receivable analytics software are:

• Chaser
• Sidetrade
• Upflow
• Blackline
• High Radius

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Collections and credit management are matters of customer relationship and can have a huge impact on the growth of your business. Using predictive analytics in AR reduces the guesswork, provides strategic insights and lets your finance team prioritise activities that improve your company’s profitability.

With Wise Business, receiving payments from local and international customers is easy and hitch-free.

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Sources used:

Sources last checked on 10-January 2025.

Disclaimer: The UK Wise Business pricing structure is changing with effect from 26/11/2025 date. Receiving money, direct debits and getting paid features are not available with the Essential Plan which you can open for free. Pay a one-time set up fee of £50 to unlock Advanced features including account details to receive payments in 22+ currencies or 8+ currencies for non-swift payments. You’ll also get access to our invoice generating tool, payment links, QuickPay QR codes and the ability to set up direct debits all within one account. Please check our website for the latest pricing information.