Scaling Cross-Border Accounting Research at Tilburg University
The Challenge Researchers at the Department of Accountancy at Tilburg University were conducting a large-scale empirical study on European financial reporting. They faced a significant logistical hurdle: they possessed a dataset of over 20,000 target firm-years across the continent but lacked the actual source documents to analyze them. Furthermore, they needed a strict filter—only English-language Annual Reports—to ensure comparability across diverse jurisdictions. Manually sifting through thousands of filings to discard local-language versions would have taken months of valuable research time.
The Solution FinancialReports executed a precise "List Matching" operation. We ingested the university's target list and cross-referenced it against our index.
- Intelligent Filtering: We identified and extracted 6,124 verified English-language Annual Reports, automatically filtering out over 5,500 non-English duplicates that would have otherwise created noise in their models.
- Dual-Format Delivery: We delivered a 43GB secure archive containing both the original source documents (PDF/HTML) for verification and machine-readable Markdown files for immediate NLP analysis.
- Metadata Enrichment: The final dataset was returned as an enriched CSV, linking the university's original identifiers directly to our filing metadata, ensuring zero data misalignment.
The Result The research team moved from data collection to analysis in days rather than months. By receiving a clean, English-only corpus pre-converted to Markdown, they bypassed the need for OCR and translation pipelines, accelerating their study on European corporate transparency.
"The ability to submit a specific list of firm-years and receive back a perfectly matched dataset—filtered for English and converted to Markdown—saved us an enormous amount of data engineering time. It turned a massive collection task into a simple download."
