Why Finance Teams Are Adding Intelligence Layers on Top of ERPs

Enterprise resource planning systems have reached a plateau. Finance chiefs no longer expect them to drive innovation — and that's become an advantage. Customization creates expensive technical debt and complicates upgrades, so the industry has shifted its focus elsewhere.

Lee An Schommer, chief product officer at Billtrust, and Jen Ebert, director of finance at Papé Group, described how strategic value in finance is moving upward into intelligence layers that operate above corporate systems of record.

AR teams don't usually have a collection problem. They have a visibility problem, Ebert explained. The ERP was never architected to manage the full scope of modern accounts receivable operations. It can flag overdue accounts, but it struggles to answer the questions that drive cash flow: which customers should be prioritized, which are most likely to remit payment, and how current receivables activity will shape future forecasts.

AR isn't just about collecting money, it's about managing the liquidity of our business.

The challenge isn't system failure. Accounts receivable has simply evolved beyond transaction processing. Specialized AR software now serves as an operational intelligence layer positioned above the ERP.

Schommer cited research covering approximately 500 finance leaders showing companies run an average of three ERP systems. Some organizations operate far more. That fragmentation creates parallel infrastructure for everything: three invoice formats, three aging reports, three sets of exception logs.

The outcome is scattered data that forces AR teams to spend substantial time reconciling information rather than acting on it. Collectors export spreadsheets, reconcile reports, and search multiple systems just to determine next steps.

When collections spend their morning pulling data instead of talking to customers, we're no longer managing receivables. We're managing data extraction.

Every hour devoted to consolidating information delays collections activity, obscures risk visibility, and slows decision-making. The operational layer provides real-time insights and handles exception routing across multiple ERPs, Schommer said. The objective isn't disrupting the ERP — it's extending it. ERP systems answer what happened; AR platforms answer what happens next.

Finance leaders understand that ERP systems are fragmented, artificial intelligence is emerging, and AR automation exists. What they need are answers tailored to their specific business requirements.

Not every customer should be treated the same way, Ebert noted. A strategic national account or government entity requires a different approach than a high-risk customer or one operating on cash-in-advance terms. Those distinctions can originate in AR.

Organizations want tools that identify payment behaviors, predict outcomes, and automate decisions across fragmented environments. Schommer emphasized the importance of business continuity: when a company grows, acquires, or shifts strategy, it shouldn't need to replace its accounting software.

You just have to figure out how to complement and extend it.

For organizations beginning their AR modernization, Schommer recommended a practical first step: map every manual process that exists because the ERP cannot handle it natively.

When you map out those manual steps, you are going to have a gold mine. You are going to see that that's an opportunity to automate and use AR and really unlock cash.

She described the evaluation process through three priorities: connectivity, configurability, and control. The objective is creating a more intelligent, automated, and predictive receivables operation without disrupting the business through unnecessary innovation.

The goal isn't to have fewer decisions, Ebert said. It's to have better decisions.