What if the Data You Trust Most is Failing You?

What’s the data you trust most—and how do you know it’s right?

In finance, confidence is critical, but overconfidence can be catastrophic. It’s easy to assume that your systems are working, your controls are solid, and your data is accurate. But what happens when the very processes you rely on are the ones quietly introducing risks?

Recent events remind us just how dangerous these assumptions can be. From overlooked adjustments to fraudulent entries, the costs of misplaced trust are real, and they’re growing.

Welcome To The Real World

Take Macy’s, for example. Over a three-year period, a single employee managed to hide $151 million in parcel delivery costs by creating incorrect accrual entries. These adjustments went unnoticed until late 2024, forcing Macy’s to delay its earnings report and revise its profit forecasts. This is a textbook example of a material weakness, where inadequate internal controls lead to major financial misstatements.

Or consider Super Micro Computer (SMCI). Earlier this year, the company delayed its 10-K filing to address internal control weaknesses, just days after a damning report flagged accounting red flags. This wasn’t just a procedural issue—investor confidence collapsed, wiping $55 billion off its market value.

Then there’s Nidec Corporation, where inadequate communication among teams led to misrecorded sales transactions between subsidiaries. These errors inflated revenue figures and revealed a material weakness in internal controls. The root cause? A lack of continuous monitoring, which could have caught the discrepancies early.

The Risks Lurking in Plain Sight

These examples highlight the risks that often go unnoticed:

• Manual adjustments that no one revisits: Assumptions around accuracy often mask deeper discrepancies.
• Fragmented communication between teams: Without clear coordination, critical errors go unchecked.
• Reliance on outdated processes: When systems aren’t equipped to adapt, blind spots emerge and grow.

What’s most troubling is that these issues don’t always appear as glaring mistakes. They surface as subtle discrepancies, small adjustments, or missed reconciliations that build over time. By the time they’re discovered, the damage is done.

How to Break the Cycle of Overconfidence

To protect your organization, you need to question more than just the data—you need to question how it’s being handled. Start by revisiting your processes and asking hard questions:

1. Are your systems truly integrated? Fragmented workflows create gaps that errors can slip through. Tools like data reconciliation platforms can help ensure consistency across systems.
2. Do you validate your data proactively? Relying solely on automation without manual oversight can lead to blind trust. Combining finance automation governance with human review ensures accuracy.
3. Is there real-time monitoring in place? Waiting until the close to identify discrepancies isn’t enough. Implementing automated reconciliation software allows you to catch anomalies as they occur.

The Bottom Line

The cost of overconfidence in your financial data isn’t just compliance—it’s trust. Trust with your investors. Trust within your team. Trust in the decisions that drive your business forward.

Recent events at Macy’s, SMCI, and Nidec serve as a warning: The greatest risks aren’t hidden in complexity, they’re hiding in plain sight, overlooked because they’re assumed to be under control.

When was the last time you truly questioned the data you rely on?