From Reactive to Predictive: How AI Is Changing Accounts Receivable for UK Finance Teams

Finance teams are under pressure to protect cash flow, keep visibility over what is owed and support growth, often with the same number of people. At our recent webinar, Zeshan Ghulam, AR Automation Expert at Quadient, covered why late payments are still one of the biggest challenges for UK businesses. He also showed how automation and AI can move AR teams from chasing overdue invoices to getting ahead of risk. Here’s a summary of the key themes and practical takeaways from the session. 

The true scale of late payments in the UK 

Zeshan opened with figures that show how big the problem is: 

• Around £26 billion is owed in late payments in the UK. 

• Late payment is linked to around 14,000 business closures a year, roughly 38 every day. 

• UK businesses spend an estimated 133 million hours a year chasing payments. 

• 90% of UK businesses report experiencing payment delays, a higher share than in several European countries. 

For finance teams, the conclusion is clear. Waiting for invoices to become overdue before acting is no longer viable, and proactive AR management has become a necessity. 

The hidden cost of manual processing 

Manual work costs money, and it also takes up time that teams could spend on higher-value activity. Benchmark data shared during the session showed a wide gap between the best and worst performers: 

• Processing an invoice costs £1.55 for top-performing teams, compared with £7.50 for bottom performers. That is close to a fivefold difference. 

• Top performers spend 30% of their week on transaction processing. Bottom performers spend 55%. 

To put that in context, Zeshan estimated that a finance team handling 2,000 transactions a month could save around £68,000 a year by automating processing. Our ROI calculators can help you estimate the figure for your own team. 

Why finance teams are investing in automation 

Quadient’s recent survey of 311 finance professionals found three main reasons for investing in automation: 

1. Improving productivity (47%) 

2. Supporting business growth (45%) 

3. Improving visibility (41%) 

 “Teams want to scale without adding headcount. When your business doubles, you don’t want to go from two credit controllers to four. You want scalability.” – Zeshan Ghulam, Account Executive, Accounts Receivable, Quadient 

The AR visibility maturity model 

One of the most useful frameworks in the session was a three-stage maturity model for AR visibility: 

• Reactive: Teams chase overdue accounts after the fact. AP and AR sit in separate systems with little shared insight. 

• Visible: AP and AR data are connected, so teams work from a shared view of cash and agree on priorities. 

• Predictive: AI flags risk before accounts become overdue, forecasts cash positions and frees teams to focus on higher-value work. 

Most organisations sit somewhere between the first two stages. The opportunity, Zeshan argued, lies in reaching the third. 

What AI-powered AR looks like in practice 

In a live demo, Zeshan showed how Quadient AR supports that shift. He focused on three capabilities: 

• A unified dashboard: AP and AR data come together in one customisable view through Quadient’s Cash Dashboard. Teams see risk and cash position in one place instead of switching between systems. 

• Automated risk flagging: High-risk accounts are surfaced early, so teams can act before invoices slip past their due dates. 

• Cash forecasting: Instead of a month-end snapshot, teams get a real-time view of current, historical and projected cash positions. 

“They just make sure that your team spends the time on the right things.” – Zeshan Ghulam A day in the life: before and after automation Zeshan showed how this changes a credit controller’s day: 

• Before: Hours spent pulling data out of the ERP and building a collections priority list by hand, leaving little time for chasing payments. 

• After: AI-driven dashboards highlight the highest-risk accounts within minutes, so collections activity can start earlier in the day. 

Features that reduce manual work 

Beyond visibility, Quadient AR includes tools designed to cut repetitive tasks and improve the customer experience: 

• Task automation: Daily activities are assigned to credit controllers automatically, so no one has to create tasks by hand. 

• AI-assisted communication: AI drafts email responses to help resolve disputes faster. AI email agents that can draft and send replies autonomously are on the roadmap. 

• Personalised collection workflows: Teams can build collection paths in advance and tailor tone and frequency for new or long-standing customers. 

• Customer self-service portal: Customers can view statements and act on invoices without contacting the finance team, with integrated payment options including Stripe. 

AR automation works best when it connects with the rest of the finance function. Pairing it with accounts payable automation gives teams the joined-up view of cash coming in and going out that the “visible” and “predictive” stages depend on. What you can do now: a 30/60/90-day plan Zeshan finished with a practical rollout plan for teams starting out: 

• Days 1–30: Establish your baseline. Measure your current DSO, invoice processing costs and the time your team spends on manual tasks, so you can show progress later. 

• Days 31–60: Pilot where it matters most. Start automating in the areas with the heaviest manual workload, where the gains will be quickest and most visible. 

• Days 61–90: Prove the value. Report results in terms leadership cares about, such as improved cash flow, reduced DSO and capacity freed up for growth. 

Ready to explore what this could look like for your team? Request a personalised demo. Key takeaways 

• Late payments tie up around £26 billion in the UK and are linked to roughly 14,000 business closures a year. 

• Invoice processing costs range from £1.55 for top performers to £7.50 for bottom performers, close to a fivefold gap. 

• Automating 2,000 transactions a month could save around £68,000 a year. 

• AR maturity runs from reactive to visible to predictive, and AI is what makes the predictive stage possible. 

• Unified dashboards, risk flagging and cash forecasting help teams act earlier without replacing human judgement. 

• Connecting AR and AP automation gives finance teams a complete picture of working capital. 

• A phased 30/60/90-day plan helps you prove value quickly and build the case for scaling up. 

Want to explore further? Discover how Quadient helps teams automate finance operations, or browse upcoming webinars and events.