Trade receivables are a fundamental concept in business finance and accounting. Understanding what they are, how they’re calculated, and how they’re reported can help CFOs, accountants and finance teams manage working capital more effectively. In this article, you’ll learn exactly what trade receivables are, see the formula to calculate them, understand where they appear in the financial statements, and explore how AI agents can transform their management.
Good working capital management, including trade receivables, is essential for optimizing capital employed and ensuring a business has liquidity to operate and grow. According to PwC, companies with strong receivables management see measurable improvements in liquidity and operational efficiency (PwC, 2025). Similarly, EY highlights that optimising receivables processes is closely linked to financial resilience and faster cash conversion cycles (EY, 2024).
What are trade receivables?
Trade receivables (often called accounts receivable) are amounts owed to a business by its customers for goods or services delivered on credit. In essence:
They represent short-term claims against customers.
They arise when sales are made without immediate cash payment.
They are a key component of working capital.
When a customer buys on credit, the business recognizes a receivable — a promise that cash will be received in the near future, usually within 30–90 days.
Trade receivables are not the same as notes receivable or other financial assets. They specifically come from normal business operations. For example, if you ship 100 units to a customer with payment due in 60 days, that amount due becomes a trade receivable.
How to calculate trade receivables
The basic formula for trade receivables is:
Trade Receivables = Opening Receivables + Credit Sales – Cash Collected – Write-offs
Here’s what each variable means:
Opening Receivables – The balance of trade receivables at the start of the period.
Credit Sales – Sales made during the period where payment has not yet been received.
Cash Collected – Cash received from customers during the period against receivables.
Write-offs – Amounts deemed uncollectible and removed from receivables.
This formula helps track how receivables change over time. If credit sales increase faster than collections, trade receivables grow, impacting your working capital.
To make this clearer, here’s a simple breakdown of each part:
Component | What It Means | Simple Example |
|---|
Opening Receivables | Money customers owed at the start of the period | £50,000 |
Credit Sales | New sales made on credit during the period | £20,000 |
Cash Collected | Payments received from customers during the period | £15,000 |
Write-offs | Amounts deemed uncollectible and removed from receivables | £1,000 |
By following this formula, you can see how the total money owed by customers changes over time and spot potential cash flow issues early. If new credit sales grow faster than collections, trade receivables will increase.
Example: Starting with £50,000 owed, adding £20,000 in new credit sales, collecting £15,000, and writing off £1,000 leaves £54,000 in trade receivables at month-end.Where trade receivables appear in financial statements
Trade receivables do not appear directly on the income statement. Instead:
They are reported on the balance sheet as a current asset.
Trade receivables reflect future economic benefits (expected cash inflows).
Revenue from credit sales does appear on the income statement, typically as sales or operating revenue at the time the sale is recognized.
How the accounting works:
Sale on Credit: When a sale is made on credit, revenue is recognized (income statement), and trade receivable is recorded (balance sheet).
Collection of Cash: When a customer pays, cash increases and receivables decrease.
Bad Debts / Write-offs: If an account is uncollectible, an expense (bad debt) may be recognized on the income statement and trade receivables reduced on the balance sheet.
This separation between the income statement and balance sheet is vital for accurate financial reporting and aligns with accounting standards (e.g., IFRS and US GAAP). Revenue recognition principles ensure sales are recorded when earned, while receivables reflect collectability.
Understanding trade receivables is also crucial when calculating broader metrics such as working capital (Current Assets – Current Liabilities) and capital employed (Total Assets – Current Liabilities, or sometimes Equity + Long-term Liabilities). Effective receivables management can strengthen both.
Where trade receivables appear in financial statements
Trade receivables do not appear directly on the income statement; they are recorded on the balance sheet as a current asset. Revenue from credit sales, however, appears on the income statement at the time of the sale.
Here’s how trade receivables flow through your accounts:
Sale on Credit: Revenue is recognised on the income statement; trade receivable is recorded on the balance sheet.
Cash Collection: When the customer pays, receivables decrease and cash increases — improving liquidity.
Bad Debts / Write-offs: Uncollectible amounts are removed from receivables and recorded as an expense.
This workflow ensures compliance with IFRS and US GAAP while helping finance teams track cash flow and working capital effectively.
Why trade receivables matter for working capital
Trade receivables are a major component of working capital, which measures the liquidity available to run day-to-day operations:
Working Capital = Current Assets – Current Liabilities
If receivables are growing faster than collections, cash may be tied up, limiting your ability to pay suppliers, invest in growth, or respond to unexpected expenses. Monitoring receivables closely allows you to optimise capital employed and keep your business agile.
How AI agents can reduce trade receivables and improve cash flow
Trade receivables are often a large chunk of a company’s working capital and can become a drag on liquidity if not managed well. Gartner and EY both emphasize the importance of automating finance functions to reduce days sales outstanding (DSO) and improve cash conversion cycles.¹ AI agents — powered by machine learning and natural language understanding are now emerging as a highly effective tool for transforming accounts receivable (AR) operations.
Automating trade receivables workflows with AI agents
Traditional TR automation often focuses on:
Generating invoices
Sending payment reminders
Posting receipts
While helpful, these functions don’t address the complex communications and decision-making in collections. AI agents go much further by handling end-to-end receivables workflows with minimal manual intervention:
Intelligent customer interaction
AI can:
Send personalised reminders at optimal times based on customer behaviour.
Respond to inbound queries about invoices, due dates, or discrepancies.
Manage follow-ups and escalations until human intervention is needed.
Example: A large customer receives a personalised reminder 5 days before the due date and pays immediately, without your team manually chasing the payment.
Handling disputes and deductions
Delays often occur due to disputes or missing information. AI agents can:
Pull relevant documents and flag likely causes of disputes.
Suggest resolutions automatically, reducing resolution times from days to hours.
Example: AI identifies a missing purchase order and notifies the customer, resolving the dispute in 24 hours instead of 5 days.
Inbox and workflow management
Finance teams spend hours triaging emails, prioritising tasks, and tracking responses. AI agents can:
Categorise emails by intent (e.g., payment confirmation, dispute, credit note).
Assign follow-ups to the right team member automatically.
Track performance metrics and SLA compliance.
Impact: Companies using AI in AR see measurable improvements:
Reduced Days Sales Outstanding (DSO)
Improved cash flow predictability
Lower bad debt write-offs
Less manual effort for AR teams
According to EY, automating finance workflows with AI can reduce DSO by 10–20% while improving cash flow predictability (EY Cognitive Finance, 2025).
Measurable impact of AI agents on trade receivables
Companies that implement AI for trade receivables management often see significant, measurable improvements in cash flow, efficiency, and working capital. These benefits not only help daily operations but also strengthen broader financial performance, making it easier for finance leaders and executives to make strategic decisions.
1. Reduced Days Sales Outstanding (DSO)
AI agents accelerate collections by sending personalised reminders, responding to customer inquiries, and following up automatically. Faster payments mean lower DSO and more available cash for the business.
Example: A company with a DSO of 65 days may see it drop to 45 days after adopting AI-driven receivables workflows.
2. Improved cash flow predictability
Automating collections and standardising processes gives finance teams a clearer view of expected inflows, reducing surprises and enabling better planning for operations and investments.
Example: Finance managers can forecast monthly cash flow accurately, avoiding unexpected shortfalls.
3. Lower bad debt write-offs
AI identifies at-risk accounts early and resolves disputes proactively, preventing invoices from becoming uncollectible.
Example: Businesses may reduce annual bad debt write-offs by 30–40%, protecting working capital.
4. Less manual work for AR teams
By handling routine tasks such as sorting emails, chasing overdue invoices, and tracking responses, AI frees AR teams to focus on higher-value work like customer relationships and process improvement.
Example: Teams can save 10–15 hours per week per team member, improving productivity and morale.
5. Stronger working capital and financial metrics
Faster collections, fewer write-offs, and predictable cash flow improve key financial indicators, including working capital efficiency and return on capital employed (ROCE) — metrics closely watched by investors and executives.
Final thoughts
Trade receivables are more than just numbers on a balance sheet. They are key to a company’s cash flow and financial health. Understanding how to calculate and manage them allows finance teams to make smarter decisions and maintain liquidity. Using AI to automate collections, communicate with customers, and resolve disputes helps businesses get paid faster, reduce bad debt, and free up time for higher-value work. Companies that adopt these tools can improve working