For many SMEs, Excel has long been the default tool for financial reporting. It’s familiar, flexible, and easy to start with. But when it comes to XBRL filing and regulatory compliance, Excel-based reporting quickly shows its limits.
As reporting requirements become more structured and data-driven, SMEs are finding that relying on spreadsheets creates more work — not less.
Excel is designed for calculation and presentation, not structured regulatory reporting. When SMEs rely on spreadsheets for financial data, several problems emerge during XBRL preparation.
Common issues include:
These issues make XBRL conversion slower and more error-prone.
XBRL is built on standardisation. Each figure must be mapped to a specific taxonomy element, and consistency across periods is critical.
Excel, by contrast:
What feels flexible during daily use becomes fragile during compliance.
Excel doesn’t just increase error risk — it increases time and cost.
SMEs often experience:
These costs are rarely visible upfront, but they add up every filing cycle.
AI-powered accounting platforms are designed for structured data from the start.
They help SMEs by:
Platforms like ccMonet turn XBRL from a conversion exercise into a natural reporting output.
Excel files are static snapshots. Modern systems provide live, continuously updated financial data.
This shift enables:
SMEs move from fixing errors to managing insights.
As regulators rely more on structured data, Excel-based workflows become increasingly risky for compliance-heavy processes like XBRL filing.
Moving on doesn’t mean abandoning spreadsheets entirely — it means no longer relying on them as the backbone of financial reporting.
Excel helped SMEs get started. But XBRL, compliance, and scale demand systems built for structure and consistency.
AI-powered accounting platforms like ccMonet help SMEs reduce manual work, improve accuracy, and approach XBRL filing with confidence.
👉 See how AI-powered bookkeeping helps Singapore SMEs move beyond Excel-based reporting at ccMonet