“Structurally incorrect” is one of the most frustrating error messages Singapore SMEs encounter during XBRL filing.
Your numbers add up. The financial statements look right. Yet the submission is rejected — sometimes repeatedly — with little explanation beyond that phrase.
So what does “structurally incorrect” actually mean in the context of XBRL filing in Singapore?
The first thing to understand is this:
“Structurally incorrect” rarely means your financial figures are wrong.
In most cases, it means the structure of the data does not comply with XBRL taxonomy and validation rules required by ACRA. XBRL is not designed to read financial statements the way humans do. It reads data relationships, hierarchies, and logic.
Your profit number can be correct — but if it’s placed, linked, or tagged incorrectly, the system will still reject it.
Traditional financial statements are visual documents. XBRL, on the other hand, is a machine-readable data model.
When ACRA’s system flags a filing as structurally incorrect, it usually means one or more of the following:
These issues are invisible in PDFs or Excel files — but immediately visible to an XBRL validator.
For Singapore SMEs, structural errors often come from how data is prepared before XBRL tagging even begins.
Typical causes include:
Each manual step increases the risk that the underlying structure no longer matches XBRL expectations.
When faced with a “structurally incorrect” error, many teams try to fix it directly inside the XBRL filing tool — adjusting tags, re-mapping fields, or trial-and-error resubmissions.
This approach often leads to:
The issue isn’t just the XBRL file — it’s how the financial data was structured upstream.
The most reliable way to avoid structural errors is to ensure your financial data is already clean, consistent, and well-structured before XBRL generation.
That means:
Modern platforms like ccMonet are designed with this principle in mind. By combining AI-powered bookkeeping with expert review, ccMonet helps SMEs maintain structured, compliance-ready financial data — reducing the likelihood of structural issues surfacing during regulatory filings.
Rather than seeing the error as a failure, it’s more useful to see it as a signal. It’s telling you that while the numbers may be right, the system producing them isn’t aligned with regulatory data requirements.
As XBRL becomes a standard part of Singapore’s compliance landscape, SMEs benefit most from accounting setups that prioritize structure — not just accuracy.
If XBRL filing feels harder than it should, the problem often isn’t your accountant or your numbers. It’s the system in between.
👉 Learn how ccMonet supports structured, compliance-ready accounting for Singapore SMEs at https://www.ccmonet.ai/
.png)
.png)
