CFOs See Month-End as the Front Line of Finance Automation

The month-end close remains one of the most labor-intensive processes in finance.

It is the ritual sprint that follows every reporting period. Spreadsheets proliferate, data is pulled from multiple systems, discrepancies are chased down, and reconciliations stretch late into the night. Despite years of enterprise digitization, the close process has remained manual and left many finance functions stuck in a cyclical war of attrition.

Payments platforms, enterprise resource planning systems, billing software, treasury tools and operational databases each produce their own records. Reconciling them requires finance teams to stitch together multiple sources of truth and can resemble a patchwork, and often stressful, exercise in data aggregation.

Even companies with sophisticated ERP deployments often rely on manual work during close. Transaction files are exported, reconciliations are conducted in spreadsheets, and exceptions are investigated across departments. Payment settlements, refunds, chargebacks and fees can frequently require separate tracking.

The result is a paradox of modern finance where companies increasingly generate more data than ever, yet finance functions can often struggle to trust it quickly enough to guide operations in real time.

See also: B2B Payments Go Digital and Boost Cash Flow Control

The Hidden Costs of Reconciliation Friction

Executives now expect finance teams to help steer the business during the reporting period, not simply report results afterward. That requires financial data that is reconciled, validated and accessible continuously.

“The office of the CFO is broadening its mandate,” Boost Payment Solutions founder and CEO Dean M. Leavitt told PYMNTS last month, adding that while decisions about how companies pay and are paid “were traditionally a secondary issue for most CFOs,” that legacy hierarchy is now changing as finance leaders come to recognize the working capital implications of strategic B2B payment design.

But when finance teams spend most of the close cycle reconciling data rather than analyzing it, the organization effectively loses days, or even weeks, of decision-making visibility. In complex environments with high transaction volumes or multiple payment rails, end-of-the-month frictions can compound rapidly.

While automation initiatives in finance are not new, many existing projects focus primarily on transactional efficiency rather than reconciliation integrity.

Instead of replacing core systems, chief financial officers are increasingly deploying automation layers that sit between them. These platforms ingest transaction data from payment systems, banks and internal applications, then reconcile the records automatically using rules, machine learning, or structured matching logic.

Read also: Why Businesses Are Replacing Checks With Virtual Cards and ACH

How Payments Complexity Is Driving the Urgency

Digital commerce, subscription models and global payment rails have increased transaction complexity, making manual reconciliation increasingly unsustainable.

PYMNTS Intelligence found in December that 66% of accounts payable teams saw an increase in manual workload over the prior year.

A single online purchase, for example, may involve an authorization record, a capture transaction, processor fees, settlement batches, and potential refunds or chargebacks. Each step may appear in different systems at different times.

Automation, in this context, becomes less a convenience than a necessity.

Data in the “2025-2026 Growth Corporates Working Capital Index: North America Edition,” a collaboration between PYMNTS Intelligence and Visa, revealed a widening performance gap between firms that have modernized their receivables and working capital infrastructure and those that continue to rely on manual, legacy processes.

Underlying the push toward automated close processes is also a broader shift in the role of the CFO. Finance leaders are no longer responsible only for reporting financial outcomes. They are increasingly expected to ensure the integrity of operational data that informs strategic decisions across the enterprise.

That expectation elevates the importance of reconciliation from an accounting task to a governance function. Reliable data is the foundation of every modern analytics initiative, from forecasting and budgeting to AI-driven insights. If underlying transaction records remain fragmented or inconsistent, those analytics lose credibility.

By automating reconciliation, finance teams are effectively building the infrastructure for decision-grade data, and that infrastructure allows finance to operate at the speed of the business.

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