AI Gives Finance Teams X-Ray Vision Into Customer Risk

Accounts receivable (AR) isn’t a corporate function typically known for its innovation.

The department has typically been known for ledger accuracy, sending overdue notices and chasing payments. Its mission has been to ensure that money owed is collected.

Eventually.

However, as global headwinds continue to squeeze cash flows, corporate finance is being reshaped to meet the uncertain environment’s new needs. Central to this reinvention is artificial intelligence, once the domain of flashier departments like marketing or supply chain analytics.

Findings in the July Digital Financial Services Tracker® Series report, “ AI Power: The Technology Transforming Accounts Receivable ,” a PYMNTS Intelligence collaboration with FIS , revealed that AI is transforming AR from a reactive, transactional function into a proactive, relationship-centered discipline, all while becoming the software engine powering the next generation of smarter financial performance.

Outdated Systems, Growing Risks

For finance leaders, the appeal of optimizing AR is simple. The business gets paid faster, with less friction, and without damaging customer relationships. But the path to that outcome has historically been paved with manual processes, aging enterprise resource planning (ERP) systems, and the blunt instruments of collections calls and reminder emails.

Manual processes can create a vicious cycle. Paper-based invoicing or email PDFs make real-time visibility impossible, and monthly AR reports, lagging indicators based on historical data, are ill-equipped to detect trouble early. That means finance teams may often miss behavioral red flags, such as gradual payment slowdowns or an uptick in disputes, which can precede a customer’s insolvency by months.

Now, AI promises a more predictive, customer-centric approach, transforming AR from a reactive back-office function into a strategic lever for growth.

Through predictive modeling, behavioral analytics and personalized outreach, AI-powered AR teams are finding themselves potentially not just reducing days sales outstanding (DSO) but also cultivating stronger, more resilient customer relationships. The result is becoming a discipline that’s as much about brand trust and customer loyalty as it is about cash flow optimization.

Read the report: AI Power: The Technology Transforming Accounts Receivable

Moving AR From Collections to Connections

AI also makes it possible to deliver high-touch communication at scale, something more challenging for AR teams constrained by headcount. Instead of sending a generic overdue invoice email to every account, AI systems can generate personalized messages based on payment history, relationship length and customer preferences.

Solutions like FIS Revenue Insight can rank customers by risk score, recommend tailored outreach and automate follow-up actions.

The effect is measurable with up to three-to-five-day reductions in DSO, 30% lower collection costs, and 12% fewer delinquencies and write-offs, the report said.

For finance chiefs, the return on investment is not just in faster payments but in operational scalability. AI systems integrate directly into ERP platforms, updating risk profiles in real time as new data flows in. That constant recalibration allows AR teams to focus on exceptions, rather than managing the bulk of accounts manually.

The technology is ready, but adoption is uneven. Large enterprises with mature digital infrastructures are integrating AI into their AR stacks at speed, while many mid-market and small- to medium-sized business players lag — often due to budget constraints or legacy system complexity. Yet the report’s findings showed that delaying adoption carries a greater cost in lost revenue, higher write-offs and missed opportunities for customer retention.

However, if the past decade was about digitizing finance, the next may be about humanizing it at scale through AI. AR will no longer be measured purely in terms of DSO, but in customer lifetime value and relationship strength.

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