AI-Powered

AI-Assisted XBRL Tagging & Quality Control

Accelerate tagging, detect anomalies, and improve data quality with LLM-powered assistants. Human-in-the-loop, fully auditable.

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Key Takeaways

Reduce tagging time by 80% with AI-powered concept suggestions

Detect anomalies and inconsistencies before filing

Human-in-the-loop: AI suggests, you approve

Full audit trail for every AI recommendation

Works with ESEF, Solvency II, COREP/FINREP taxonomies

The XBRL Tagging Challenge

Manual XBRL tagging is time-consuming, error-prone, and requires deep taxonomy expertise. As taxonomies grow and evolve, the challenge compounds.

  • Taxonomies contain 10,000+ concepts - finding the right one is overwhelming
  • Taxonomy updates require re-mapping hundreds of tags each year
  • Human errors in tagging lead to filing rejections and delays
  • Expert XBRL knowledge is scarce and expensive

The Cost of Manual Tagging

35%
of first-time filings contain tagging errors
40h
average time to tag annual report
60%
of errors are consistency issues
€50K
average cost of delayed filing

AI-Powered Capabilities

Intelligent assistance at every step of the tagging workflow

Smart Auto-Tagging

LLM analyzes your financial statements and suggests appropriate taxonomy concepts based on context, not just keywords.

Contextual Suggestions

Get ranked concept recommendations with confidence scores and explanations for why each concept fits.

Anomaly Detection

Automatically identify outliers, sign errors, calculation mismatches, and year-over-year inconsistencies.

Continuous Learning

The AI improves over time, learning from your corrections and company-specific patterns.

Explainable AI

Every suggestion comes with reasoning. Understand why the AI made each recommendation.

Built-in Guardrails

AI operates within strict boundaries. Critical decisions always require human approval.

How It Works

A simple 4-step workflow

Step 1

Upload

Upload your financial statements (PDF, Excel, Word)

Step 2

Analyze

AI extracts facts and suggests taxonomy mappings

Step 3

Review

Review suggestions, accept or override with confidence

Step 4

Validate

Run full validation and export tagged file

Manual vs AI-Assisted Tagging

See the difference in efficiency and accuracy

Metric
Manual Tagging
AI-Assisted
Time to Tag
40+ hours
8 hours
First-Pass Accuracy
65-75%
90-95%
Year-over-Year Consistency
Variable
High
Effort per Report
Linear
Logarithmic

Use Cases

Where AI makes the biggest impact

First-Time ESEF Filing

New to XBRL? AI guides you through taxonomy selection, ensuring compliance from day one.

Taxonomy Version Updates

When taxonomies update, AI suggests how to remap your existing tags to new concepts.

Pre-Filing Quality Check

Detect anomalies and inconsistencies before submission. Catch issues auditors would flag.

Extension Taxonomy Creation

AI suggests base concepts and anchoring relationships for custom extensions.

Guardrails & Trust

AI is a powerful tool, but we've built safeguards to ensure you remain in control and every decision is auditable.

Human-in-the-loop: All AI suggestions require explicit approval
Confidence thresholds: Low-confidence suggestions are flagged for review
No black boxes: Every recommendation includes reasoning
Full audit trail: Track who approved what, when, and why

Audit-Ready

Decision Log

Complete history of AI suggestions and human decisions

Version Control

Track changes between tagging iterations

Export Reports

Generate PDF/Excel reports for auditors

Frequently Asked Questions

Does the AI replace human judgment?

▼
No. Xerify AI is designed as an assistant, not a replacement. All suggestions require human review and approval. The AI accelerates the process and catches errors, but you make the final decisions.

How accurate are the AI suggestions?

▼
Our AI achieves 90-95% accuracy on concept suggestions for common financial statement items. Complex or unusual items may require manual selection, which the AI learns from over time.

What data does the AI learn from?

▼
The AI is trained on public XBRL filings and taxonomy documentation. Your private data is used only within your organization's context and is never shared or used to train models for other customers.

Is this compliant with regulatory requirements?

▼
Yes. The AI assists with tagging but does not change how validation works. All filings are validated against the same standards, ensuring full regulatory compliance.

Can the AI work with custom extensions?

▼
Yes. The AI can suggest base concepts for extension elements and recommend anchoring relationships. It learns your extension patterns over time.

How does anomaly detection work?

▼
The AI compares current values against historical data, industry benchmarks, and internal consistency rules to flag potential errors like sign errors, magnitude issues, or missing relationships.

What taxonomies does the AI support?

▼
The AI supports all major taxonomies: ESEF (IFRS), Solvency II (EIOPA), COREP/FINREP (EBA), US GAAP (SEC), and custom extensions.

Can I disable AI features?

▼
Yes. AI features are optional. You can use Xerify purely as a validation platform and enable AI assistance when ready.

Related Resources

AI-Assisted XBRL Tagging Guide

Anomaly Detection Best Practices

XBRL Validation Platform

Ready to Accelerate Your Tagging?

Start using AI-assisted XBRL tagging today. Free trial available.

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