The Known Unknown: A Regulator’s Perspective

Posted on May 4, 2026 by Editor

In the latest instalment of his guest series for XBRL International, Björn Fastabend, head of the XBRL collection and processing unit at BaFin, Germany's Federal Financial Supervisory Authority, shares a fascinating hands-on experiment in using AI to analyse XBRL data from the SEC's EDGAR database.

Björn built a proof-of-concept tool to query financial data using a large language model - and quickly ran into a surprising problem. Asking the same question five times produced five different answers. The culprit? Not hallucination, but semantic ambiguity: with 80 different revenue-related concepts in the SEC taxonomy, the LLM simply didn't know which one to use, and guessed differently each time.

His solution? A 'Financial Domain Intelligence Layer', designed to inject specialist domain knowledge into the querying process. This offers a compelling illustration of a broader truth: structured XBRL data and taxonomies are necessary but not sufficient for high-quality AI-driven analysis. Domain expertise matters too.

The piece is a thought-provoking read for anyone interested in the intersection of AI and regulatory data, and a timely reminder of the extraordinary promise and some of the current limits of AI in this space.

Read the post here.